DiSSCo Prepare Deliverable D1.1 - Report on life sciences use cases and user stories

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Title DiSSCo Prepare Deliverable D1.1 Report on Life sciences use cases and user stories Author(s) Fitzgerald, Heli Juslén, Aino von Mering, Sabine Petersen, Mareike Raes, Niels Islam, Sharif Berger, Frederik von Bonsdorff, Tea Figueira, Rui Haston, Elspeth Häffner, Eva Livermore, Laurence Runnel, Veljo De Smedt, Sofie Vincent, Sarah Weiland, Claus Identifier of the author(s) https://orcid.org/0000-0002-6754-6409 https://orcid.org/0000-0001-9434-5250 https://orcid.org/0000-0003-2982-7792 https://orcid.org/0000-0001-8666-1931 https://orcid.org/0000-0002-4329-4892 https://orcid.org/0000-0001-8050-0299 https://orcid.org/0000-0001-8400-3337 https://orcid.org/0000-0001-6066-5256 https://orcid.org/0000-0002-8351-4028 https://orcid.org/0000-0001-9144-2848 https://orcid.org/0000-0001-6448-5826 https://orcid.org/0000-0002-7341-1842 https://orcid.org/0000-0001-5198-8678 https://orcid.org/0000-0001-7690-0468 https://orcid.org/0000-0002-4012-0571 https://orcid.org/0000-0003-0351-6523 Affiliation Luomus - Finnish Museum of Natural History, Helsinki, Finland Contributors Schulman, Leif Järvi, Jani Frank, Jiři Loo, Tina Mergen, Patricia Semal, Patrick Publisher Identifier of the publisher Resource ID https://doi.org/10.34960/xhxw-cb79 (D1.1.) Publication year 2021 Related identifiers https://doi.org/10.7479/17qp-ge55 (Data publication) https://doi.org/10.34960/n3dk-ds60 (Deliverable D1.2) Relation type Another reference document Is it the first time you submit this outcome? No Creation date 01/04/2021 Modification date 22/04/2021 Summary of modification Version Minor changes to the text of Appendix 3. 1.1. Citation Fitzgerald, H., Juslén, A., von Mering, S., Petersen, M., Raes, N., Islam, S., Berger, F, von Bonsdorff, T., Figueira, R., Haston, E., Häffner, E., Livermore, L., Runnel, V., De Smedt, S., Vincent, S., Weiland, C. (2021). DiSSCo Prepare Deliverable D1.1 Report on Life sciences use cases and user stories. https://doi.org/10.34960/xhxw-cb79 Abstract This Deliverable for D1.1 from the Horizon 2020, INFRADEV-02-2019-2020 project DiSSCo Prepare reports the results of Task 1.1 “Analyse Life sciences use cases and user stories”. The complemented corpus of Life sciences user stories and use cases was analysed with a special emphasis on the functional demands for DiSSCo and its services, as well as their socio-economic importance. Based on recognized functional demands recommendations for the related ongoing Work Packages and DiSSCo services development in general are given. Content keywords scientific Project reference DiSSCo Prepare (GA-871043) WP number WP1 Project output Deliverable Deliverable/milestone number D1.1. Dissemination level Public Rights License CC0 1.0 Universal (CC0 1.0) Resource type Text Format pdf Funding Programme H2020-INFRADEV-2019-2 Contact email [email protected] 36 DiSSCo Prepare WP 1 task 1.1. – Deliverable: D1.1 Report on life sciences use cases and user stories WP Lead: Henrik Enghoff (UCPH) Task Lead: Aino Juslén (Luomus) Authors: Heli Fitzgerald (Luomus), Aino Juslén (Luomus), Tea von Bonsdorff-Salminen (Luomus), Sabine von Mering (MfN), Mareike Petersen (MfN), Niels Raes (Naturalis), Sharif Islam (Naturalis), Rui Figueira (U Lisboa), Elspeth Haston (RBGE), Eva Häffner (BGBM), Laurence Livermore (NHM), Veljo Runnel (UT), Sofie De Smedt (Meise BG), Sarah Vincent (NHM), Claus Weiland (SGN) Contributors: Leif Schulman (Luomus) Jani Järvi (Luomus), Frederik Berger (MfN), Jiří Frank (NM), Tina Loo (Naturalis), Patricia Mergen (Meise BG), Patrick Semal (RBINS) Abstract Key words This Deliverable for D1.1 from the Horizon 2020, INFRADEV-02-2019-2020 project DiSSCo Prepare reports the results of Task 1.1 “Analyse Life sciences use cases and user stories”. The complemented corpus of Life sciences user stories and use cases was analysed with a special emphasis on the functional demands for DiSSCo and its services, as well as their socio-economic importance. Based on recognized functional demands recommendations for the related ongoing Work Packages and DiSSCo services development in general are given. Biology, collections, DiSSCo, life sciences, cluster analysis, research, use cases, user requirements, user stories, functional demands, service development framework, societal challenges H2020, socio-economic impact/indicators Grant Agreement number: 871043 — DiSSCo Prepare — H2020-INFRADEV-2018-2020 / H2020-INFRADEV-2019-2 INDEX Contents ................................................................................................................................................................. 4 01 INTRODUCTION ........................................................................................................................... 4 02 APPROACH ................................................................................................................................... 5 Targeted Groups for additional surveys and interviews ..................................................................... 6 Functional demands ............................................................................................................................ 6 Analysing the user stories ................................................................................................................... 6 Making the user stories available for future use ................................................................................ 7 03 RESULTS ....................................................................................................................................... 7 Compilation of use cases and user stories .......................................................................................... 7 Functional demands for the user stories ............................................................................................ 9 Analysing the user stories ................................................................................................................. 12 Making the user stories available for future use .............................................................................. 13 04 DISCUSSION AND OUTLOOK ...................................................................................................... 14 Use cases and functional demands ................................................................................................... 14 Use cases and societal challenges in Europe 2020 strategy ............................................................. 15 Health, demographic change and wellbeing ................................................................................. 15 Food security ................................................................................................................................. 16 Inclusive, innovative and reflective societies ................................................................................ 16 Climate action, environment ......................................................................................................... 17 05 RECOMMENDATIONS AND LINKS TO OTHER WORK PACKAGES ............................................... 17 06 REFERENCES .............................................................................................................................. 20 07 APPENDICES ............................................................................................................................... 21 Appendix 1. Table of user story compilations from previous projects and other source documents ........................................................................................................................................................... 21 Appendix 2. Use cases and functional demands tables .................................................................... 21 Appendix 3. SYNTHESYS Transnational Access Analysis .................................................................... 21 4 01 INTRODUCTION The Distributed System for Scientific Collections (DiSSCo) aims to provide a one-stop-shop for Natural Science Collections objects and associated information in Europe. The planned Research Infrastructure (RI) will be an important source of information for scientists from natural science disciplines but also other users from the sectors education, culture, society, politics, and economy. In order to meet the requirements of all potential stakeholders, the planning and construction of the DiSSCo RI is strongly user driven, especially in the Project DiSSCo Prepare. DiSSCo Prepare WP1, Tasks 1.1 and 1.2 examined the needs of different stakeholder groups for the information that natural science specimens and collections contain and the requirements these needs set for the services to be provided by DiSSCo. More closely, within Tasks 1.1 “Analyse Life sciences use cases and user stories” and 1.2 “Analyse Earth sciences use cases and user stories”, we built on existing studies and compilations covering DiSSCo-related use cases and user stories. Task 1.1 and Task 1.2 were complementary to each other, focussing on the two domains Life sciences and Earth sciences, respectively. While Task 1.1 dealt with biological collections (entomological, other zoological, botanical and mycological collections), the focus of Task 1.2 was on collections of fossils, rocks, sediment structures, minerals, and extra-terrestrial material (meteorites). This report is part of the Deliverables D1.1 “Report on Life sciences use cases and user stories, with recommendations to WP5 and WP6” and D1.2 “Report on Earth sciences use cases and user stories, with recommendations to WP5 and WP6”. The complemented corpus of Life sciences and Earth sciences user stories and use cases was analysed with a special emphasis on the functional demands for DiSSCo and its services, as well as their socio-economic importance. 5 02 APPROACH As a first step, existing user stories and use case compilations and other resources were collected in a project-wide collaborative effort. All DiSSCo Prepare WP and task leaders as well as the partner institutions working on Tasks 1.1 and 1.2 were contacted and asked to add surveys, presentations, and other sources for user stories to a shared document. An overview of the resources gathered is given in Appendix 1. From this large compilation, a table of user stories and use cases was generated. It was built mainly on results from the ICEDIG (Innovation and consolidation for large scale digitisation of natural heritage, https://icedig.eu/) effort (van Egmond et al. 2019), but other sources of use cases were added as well (see Appendix 1 for details). To collect and present the use cases, we decided to use the epic story format used e.g. in requirement management and adopted by van Egmond et al. (2019) as well. This format contains the following four parts: “As a [position]… I want to… So that I can… For this I need...”. The compiled table was then adjusted to fit the task’s focus on Life sciences or Earth sciences. Accordingly, a number of strictly Life science or Earth science related use cases were removed and others adapted to fit the respective domain focus. Next, duplicates were removed (user stories from different sources that were the same) and near-duplicates (e.g., differing by only one of the stages of the epic story format) were fused without losing information. Incomplete user stories, with no text in ‘So that I can...’ or ‘For this I need...’ parts, were also removed. Subsequently, the uses cases were grouped into the seven user groups or use categories, which were also adopted from the ICEDIG project (van Egmond et al. 2019): 1. Research (academic, non-academic incl. Citizen Science) 2. Collection management 3. Technical support (IT & IM) 4. Policy (institutional, national & international) 5. Education (academic & non-academic) 6. Industry 7. External (media & empowerment initiatives) The collected information was then evaluated, especially regarding existing gaps related to certain stakeholder groups. Once gaps were detected, information on user communities and stakeholders that might help to fill the gaps were collected. This approach was supplemented by over 15 years of data derived from the SYNTHESYS Transnational Access programme. The programme’s record of facility and collection usage requirements and formally published research outputs was clean, refactored and analysed to aid quantification and prioritisation of the user stories previously described. The detailed approach is described in Appendix 3 and summarised in the main discussion and outlook section. 6 Targeted Groups for additional surveys and interviews To extend the compilation of use cases and to fill existing gaps, we reached out to all task partners to identify potential users/user groups and stakeholders that should be approached. In a first step, public relations and marketing teams of a number of partner institutions were contacted. Few additional use cases were included from responses by scientists, colleagues and other stakeholder groups. Functional demands During a joint session on "Use cases and user stories" during the virtual All Hands Meeting of DiSSCo Prepare in January 2021, members of both task groups worked together to further analyse the collection of use cases and user stories. The working session focussed on the functional demands these use cases will put on the DiSSCo research infrastructure (RI) and its services. Some user requirements were already known from the epic user story format part "For this I need". However, the information given there is in many cases rather general and unspecific and functional demands for the DiSSCo Research Infrastructure had to be specified. All task partners worked collaboratively on categorization and harmonization of functional demands resulting from the use cases. Categories and subcategories for functional demands were listed and short definitions explaining what a category or subcategory comprises were included. Up to five functional demand categories or subcategories were allocated for each use case. Further steps were also discussed during a consultation with project partners from WP5 “Common Resources and Standards” and WP6 “Technical Architecture & Services provision”, and with the DiSSCo Technical Team. Analysing the user stories Up to five functional demands were identified for each of the 443 Life science (LS) and Earth science (ES) user stories and converted into a presence/absence matrix. The LS and ES user stories were analysed separately, some user stories applied to both domains. For each category, it was scored how often it was scored for the use cases/user stories. The dissimilarity matrix was calculated for the LS and ES presence/absence matrices separately using the function vegdist from the R-package ‘Vegan’ (Oksanen et al. 2020). As a measure of dissimilarity the Jaccard index was selected and data were subjected to presence/absence standardization. The dissimilarity matrices were further analysed with a hierarchical cluster analysis using an UPGMA (average) cluster algorithm and visualized using the ‘Dendextend’ R-package (Galili 2015). A heatmap visualisation was conducted to assess which similarities in demands result in clusters of user stories. The R-script used in the analysis of the user stories is available in the GitHub repository for the user stories (Raes 2021). 7 Making the user stories available for future use All use cases and user stories were imported to GitHub using a semi-automatic import routine. In the repository, the use cases are available as separate “issues” and linked also to the use categories, i.e. the user or stakeholder groups. The functional demand categories scored for each use case were added as separate tags, thus allowing easy filtering. In addition, the tables comprising all use cases (Life sciences and Earth sciences together as well as separately) were also made available as csv files in a data publication (Fitzgerald et al. 2021). In these tables, numbers were added as simple identifiers (IDs) to identify the different use cases and user stories for later re-use and reference (Appendix 2; Fitzgerald et al. 2021). 03 RESULTS Compilation of use cases and user stories The selected, adapted, and sorted user stories and use cases were compiled in a table containing all use cases plus separate tables for Life and Earth sciences (Fitzgerald et al. 2021). The separate tables for both domains are also attached as a supplement to this Deliverable report (Appendix 2). For Life sciences, a total of 597 user stories were collected (Fitzgerald et al. 2021). The categories “Research” and “Collection management” were the categories with the highest numbers recorded (271 and 173 user stories, respectively). Of the 597 user stories, 33 were gathered from the literature (Vissers et al. 2017, Borsch et al. 2020) and from the Final report of the GBIF Task Group (Krishtalka et al. 2019). After deduplication and removal of incomplete user stories, the number of use cases was 317 (Fitzgerald et al. 2021). A total of 122 user stories applicable to Earth sciences were collected. The total number of user stories and use cases for Earth sciences after de-duplication and addition was 128 (see Appendix 2; Fitzgerald et al. 2021). With 38 and 48 user stories respectively, the categories “Research” and “Collection management” were also the categories with the highest numbers recorded. While the high number of user stories in the “Research” and “Collection management” categories was not unexpected, the number of use cases collected in some of the other categories were fewer than expected. The largest potential gaps were detected in the categories “External (media & empowerment initiatives)”, “Industry” and Technical support”. For the categories “Education”, “Technical support” and “Policy”, smaller numbers of use cases were also collected. Figure 1 and 2. summarizes the number of use cases collected per use case category for both Life sciences and Earth sciences. 14 Figure 8. Screenshot of selected use case in GitHub repository shows tags for functional demands / use categories 04 DISCUSSION AND OUTLOOK Use cases and functional demands The categories of use “Research, Collection Management, Technical support, Policy, Education, Industry, and External” were represented, the far most use cases representing Research and Collection Management. The societally wide-ranging needs for the use of scientific collections came to the fore (Figure 1.). For instance high-quality metadata descriptions and images are highly needed (Figure 3 and 4.) and serve stakeholders from research to industry (Fitzgerald et al. 2021). The recognition and description of functional demands at appropriate and useful levels required several rounds of refinement to optimise usefulness for the further development within DiSSCo (see Table 1). The analysis of use cases and 15 recognition of functional demands create basis for and support further RI DiSSCo development, e.g. recognition of digitisation prioritisation criteria (task 1.3.) and set the service development framework. Data derived from records of recent collection-based projects and their outcomes can be used to augment and quantify the user stories gathered. The majority of projects submitted under existing (inperson) collection access schemes require the use of both collection material and local analytical facilities such as molecular labs, microanalysis and 2D/3D imaging suites, and geochemical identification (see Appendix 3 for details). For facilities/services that can be delivered remotely, this information is key to developing robust, appropriately scaled digital services and workflows. Use cases and societal challenges in Europe 2020 strategy The analysis of user stories, including its functional demands, provides important information for the identification of socio-economic impact of DiSSCo. The framework for this analysis (under development in DiSSCo Prepare Task 1.4) will link the impact of uses and applications of DiSSCo and related activities to a set of major objectives, defined by the ESFRI Working Group on monitoring RI performance (ESFRI 2019). These include:  Enabling scientific excellence  Delivery of education and training  Enhancing transnational collaboration in Europe  Facilitating economic activity  Outreach to the public  Optimising data use  Provision of scientific advice  Facilitating international co-operation  Optimising management These can also be arranged within four major areas - scientific excellence, economy and innovation, society, and policy - contributing to the following H2020 societal challenges (Societal Challenges, Horizon 2020):  Health, demographic change and wellbeing;  Food security, sustainable agriculture and forestry, marine and maritime and inland water research, and the bioeconomy;  Climate action, environment, resource efficiency and raw materials;  Europe in a changing world - inclusive, innovative and reflective societies; We identified user stories, which directly or indirectly address some of the societal challenges, which are outlined in Horizon 2020 strategy documents. We also took into account the user stories from (van Egmond et al. 2019) earlier DiSSCO findings from the ICEDIG project. The user stories are summarized as follows. Health, demographic change and wellbeing Occurrence data of virus/bacterial disease vector species (mosquitoes, bats, etc.) can be obtained from collection databases to support control of zoonotic diseases. Comprehensive, connected collection management systems can make remote working easier for researchers, minimizing the risks 16 associated with pandemics. Biodiversity data from collections can be linked to health data so that health impact of variables such as vegetation cover, deforestation or species diversity can be modelled. Future distributions of allergenic species can be modelled by linking collection and occurrence data with e.g., climate data/environmental data, helping to predict and mitigate health problems arising from allergies. Collection-based research can support ethnobotanical research, as seen in an investigation of natal diets (de Boer & Lamxay 2009). Food security Genomic data from collections can be used to analyse food plant diseases, see Essakhi et al’s study of Phaeoacremonium species (hyphomycetes fungi) and their association with esca disease in cultivated grapevines (e.g. Essakhi et al. 2008). Specimens can support the identification, conservation and use of crop wild relatives. They can also provide occurrence and associated environmental data, which can contribute in investigating genetic control of agriculturally relevant traits in crop wild relatives. Locating the origin of food pest species and modelling their future distribution by e.g. linking occurrence data with climate data. Support crop diversification and green infrastructures to increase sustainability of farming practices, investigate genetic control of agriculturally relevant traits in crop wild relatives. Inclusive, innovative and reflective societies Digital species information such as images, trait descriptions, etc., can help citizen scientists to identify species and facilitate citizen science projects. Digitally opening up natural history collections for education and public knowledge can facilitate engagement with underrepresented citizen groups in citizen science. Runnel et al. (2019) studied the role of natural history collections in improving the digital skills of citizens. In natural history museum educational programs, the use of digital content (including digitized specimens) was considered underdeveloped with a high potential for increased use and effectiveness (Runnel et al. 2019). They propose that enhancing data search and building public interfaces for collection digital content could lead toward more effective use of natural history digital content in society and broader acknowledgment of the value of natural history collections. Including citizen scientists in museum-based citizen science projects (particularly digitisation tasks) can also lead to involvement of participants in decision-making regarding environmental topics in society (Runnel et al. 2019). As implied by Runnel & Wijers (2019), citizen science attribution in crowdsourcing project outcomes needs to be improved, often the published data lacks the information about citizens involvement . Private natural history collections are historically and practically an important part of biological research. In some cases, private collections are donated to museums or other collection holding institutions, but often their scientific value is lost due to loss or deterioration of the collections. If private collection holders are invited to share the specimen data, the impact to science will be achieved quicker and also the handling of collections in case of donations will me much smoother. Opening collection data management systems to private collectors can also put greater emphasis on the value of citizen science and its part in academic research. Willemse et al. (2020), analysed the perspective of private collectors and proposed tools and recommendations for the DISSCO consortium. 17 Climate action, environment Access to historical data of species distributions, abundance and habitats can help to understand climate change. Metadata (sampling methodology, etc.) is crucial for specimen data useability and applying statistical approach. Easy and comprehensive data access can also facilitate innovative data solutions for visualisation of species loss and environmental degradation and have an impact on policy making. Digital specimen data will allow aggregation of specimen data to other data types, such as climate and weather data and land-use data will allow new types of analysis serving e.g. climate change mitigation at ecosystem level. Digital specimen trait data can be used to study links between species morphology and climate change (Salinas-Ramos et al, 2020). 05 RECOMMENDATIONS AND LINKS TO OTHER WORK PACKAGES The use cases and functional demands can help prioritize developments in the Technical Work Packages of DiSSCo Prepare. All identified use cases were imported into GitHub, the main repository for technical developments in DiSSCo Prepare and related projects (DiSSCo/user-stories). Therewith, they are easily accessible for the developmental teams and can be taken into consideration when setting up developmental plans for the DiSSCo technical architecture, the prioritization of services and setting up or shaping pilots in DiSSCo Prepare. The results of WP 1 provide a valuable resource for WP 3, which develops the specifications for a digital maturity self-assessment tool in task 3.1. The analysis of user stories of WP1 may indicate areas where digital maturity of consortium members will be needed to underpin the success of the DiSSCo services. Furthermore, it has to be presumed that any assessment referring to actual user needs potentially experiences a higher acceptance during implementation. In a first attempt to identify areas that provide information about digital maturity a subset of 127 user stories from WP1.2 were categorized and described in a similar approach as the one adopted to identify functional demands. As a first result, a non-exhaustive list of areas to be covered was derived from the dataset. According to this interpretation of user needs the following areas are of primary interest and should therefore be considered, when assessing digital maturity of institutions or infrastructure.  Availability of data at collection and specimen level  Data standards and quality assurance  Licensing  Open data policies and processes (links to WP2)  Availability of data types e.g. 3D  Progress of digitisation, plus workflows, best practices, etc.  Infrastructure including collections management systems  Persistent identifiers  Analytics and monitoring  Availability of tools and processes e.g. annotation, transcription, AI, etc. It is planned to extend the analysis of WP3 to the whole set of user stories and to take the functional demands categories and sub-categories into account. This would lead to a higher degree of standardization. However, it has to be evaluated, if the functional demands define useful categories for the specifications of a digital maturity assessment tool. 18 For the development of “Common resources and standards” (DiSSCo Prepare WP5) the following recommendations should be taken into account: DiSSCo Knowledgebase (Task 5.1): Identified functional demands should contribute to the content in the DiSSCo Knowledgebase. Here, e.g. compilation of necessary (meta) data standards on object and collections level should be available, relevant policies should be presented and described (ongoing collaboration with Task 7.3 DiSSCo Policies), and available tools to address user needs should be listed and instructions need to be given. In addition, reporting on collections-based research but also use cases from other stakeholder groups could be documented here. Not all identified functional demands are directly linked to DiSSCo’s central architecture (Core Digital Object) but rather to services and products (e.g. for data publication, reference systems) linked to it. The starting Task “Technical infrastructure for science data mobilisation and publication” (Task 5.4) need to consider the identified requirements for development plans of e.g. Catalogue of Life and GeoCASe. The development of “Technical Architecture and Service Provision” (DiSSCo Prepare WP6) should consider the identified functional demands, translate them into a more technical language, and use them for prioritization in the technical development of the architecture. For example the list of required tools for end users (compare Table 1) should be harmonized with current concepts of the DiSSCo RI. However, not all services and tools might be a necessary development under DiSSCo and we recommend WP6 partners to make clear which tools and services are already available or planned in associated RI (Task 6.4 “Embedding Embedding DiSSCo in the technical landscape”). The use cases and functional demands will directly contribute to Task 6.1 “CMS systems interoperability and harmonisation”. Within this task, which involves harmonization, specifications and agreements for local collection facilities to achieve interoperability with DiSSCo’s emerging core infrastructures, a modeling framework adopting the EventStorming format was created to capture main events in the life cycle of a Digital Extended Specimen (DES). Based on a lightweight common description model - “a command causes an event, which can lead to a reaction” - more formal representations of DES-related processes and activities like initial digitization, assignment of PIDs, further (sub)sampling for genomic analysis or taxonomic revisions were developed. These representations will now be used in the context of Task 6.1 for the implementation of event data in a common specification like CloudEvents to provide interoperability across DiSSCo-linked services, platforms and systems, but should also be connected to corresponding use cases and user stories. Aim is the establishment of a common notation to gain a unified understanding of needs as well as “responding” technical solutions following the aforementioned “Command -> Event -> Reaction” scheme. The utilization of such a unified and consistent framework for requirements, objectives and services will substantially support the full implementation of the DiSSCo service architecture. In addition, the DiSSCo system design should anticipate future reporting on impact metrics: consistent, ongoing categorisation of collection usage/data access requests and the implementation of data quality controls on downstream research output metadata such as peer-reviewed publications will facilitate linkages to existing data sources in the wider scholarly publications ecosystem, improving the reliability and usefulness of impact metrics. Data integrity and interoperability would be improved by incorporating existing, discipline-specific digital services in the development of further digital collection systems. For example, incorporating vocabularies derived from taxonomic name lookup and resolution services such as the GBIF Species 19 API would make reporting on life sciences collection access requirements more efficient, granular and repeatable. It would also facilitate identification of data gaps and feed into transnational digitisation prioritisation and planning. The use of more standardised data and related system linkages will also support the creation of visual analysis and decision-making tools such as dashboards: if such interfaces are to be intuitive and understandable by stakeholders external to the natural sciences community, collection usage and impact data must be optimised suitable for high-level aggregation and visualisation. Data from in-person access schemes (like Transnational Access in SYNTHESYS) can be used as a benchmark from which we can assess progress towards increased engagement by under-represented groups. If remote access to equivalent collection data and services overcomes barriers to inclusion, this should be measurable in changes to the demographic profile of the user base. This type of datadriven service design would require demographic data on system end-users to be recorded, where appropriate. More inclusive categories of complex demographic variables such as gender identity should also be incorporated: if these are not in the data, the engagement and scientific impact of these groups cannot be measured, reported on or incorporated into ongoing system design and development activities. In order to track and better understand our users and how they need/want to use our facilities in the future, we should consider providing solutions for the following: (i) Enabling scientific excellence, (ii) Delivery of education and training, (iii) Enhancing transnational collaboration in Europe, (iv) Facilitating economic activity, (v) Outreach to the public, (vi) Optimising data use, (vii) Provision of scientific advice, (viii) Facilitating international co-operation, and (ix) Optimising management. Many tools and services are already available and meet at least partly the requirements of known and new users of Natural Science Collections. However, there is still potential for improvement, especially in linking services from different RI and making tools interoperable. The DiSSCo RI need to accept this challenge and provide solutions for use cases identified and described in this deliverable. Especially those which require more then only one functional demand and which can only contribute to our societal challenges with a comprehensive set of services linked to our Natural Science Collections. 20 06 REFERENCES de Boer, H. & Lamxay, V. (2009). Plants used during pregnancy, childbirth and postpartum healthcare in Lao PDR: A comparative study of the Brou, Saek and Kry ethnic groups. J. 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The changing career trajectories of new parents in STEM. Proc. Natl Acad. Sci. USA 116 (10): 4182-4187. https://doi.org/10.1073/pnas.1810862116 DiSSCo user-stories (2021). DiSSCo/user-stories: Collection of user stories describing evolving requirements of stakeholders involved in managing and using natural science collections. GitHub https://github.com/DiSSCo/user-stories Accessed ### van Egmond, E., Willemse, L., Paul, D., Woodburn, M., Casino, A., Gödderz, K., Vermeersch, X., Bloothoofd, J., Wijers, A. & Raes, N. (2019, March 31). Design of a Collection Digitisation Dashboard (Version 1.0). Zenodo. http://doi.org/10.5281/zenodo.2621055 ESFRI (2019). Report of the ESFRI Working Group on monitoring RIs performance | www.esfri.eu. https://www.esfri.eu/latest-esfri-news/report-esfri-working-group-monitoring-ris-performance Essakhi, S., Mugnai, L., Crous, P.W., Groenewald, J.Z. & Surico, G. (2008). Molecular and phenotypic characterisation of novel Phaeoacremonium species isolated from esca diseased grapevines. Persoonia 21: 119–134. https://doi.org/10.3767/003158508x374385 Fitzgerald, H., von Mering, S., Juslén, A., Petersen, M., Berger, F., von Bonsdorff-Salminen, T., De Smedt, S., Figueira, R., Frank, J., Häffner, E., Haston, E., Islam, S., Järvi, J., Livermore, L., Loo, T., Mergen, P., Raes, N., Runnel, V., Schulman, L., Semal, P. & Vincent, S. (2021). Compilation of use cases and user stories, functional demands and their analyses for the RI DiSSCo – DiSSCo Prepare Tasks 1.1 & 1.2. [Dataset]. Data Publisher: Museum für Naturkunde Berlin (MfN) - Leibniz Institute for Evolution and Biodiversity Science. https://doi.org/10.7479/17qp-ge55 Galili, T. (2015). dendextend: an R package for visualizing, adjusting, and comparing trees of hierarchical clustering. Bioinformatics 31: 3718–3720. https://doi.org/10.1093/bioinformatics/btv428 Krishtalka, L. (2016). Accelerating the discovery of biocollections data. Copenhagen: GBIF Secretariat. Available online at: http://www.gbif.org/resource/83022 Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Szoecs, E. & Wagner H. (2020). vegan: Community Ecology Package. R package version 2.5-7. https://CRAN.R-project.org/package=vegan 21 Raes, N. (2021). R-script used for analysis of user stories and functional demands. GitHub https://github.com/DiSSCo/user-stories/blob/17315c736931a5c8ce6fb1837f143a7ca6e07658/RaesN_DPP_T1-1_T1-2.R Runnel, V., Hardy, H., Sanghera, H., Robinson, L., Shennan, V., Livermore, L. & De Smedt, S. (2019). Natural history collections and digital skills of citizens. Zenodo. https://doi.org/10.5281/zenodo.3364541 Runnel, V. & Wijers, A. (2019). Improving the detection of collection-based citizen science projects. Zenodo. https://doi.org/10.5281/zenodo.3364519 Salinas-Ramos, V.B., Agnelli, P., Bosso, L., Ancillotto, L., Sanchez-Cordero, V., Russo, D. (2020). Body Size Variation in Italian Lesser Horseshoe Bats Rhinolophus hipposideros over 147 Years: Exploring the Effects of Climate Change, Urbanization and Geography. Biology (Basel). 10(1):16. doi: 10.3390/biology10010016 Societal Challenges, Horizon 2020. European Commission. Available online at: https://ec.europa.eu/programmes/horizon2020/en/h2020-section/societal-challenges#Article Vissers, J., Van den Bosch, F., Bogaerts, A., Cocquyt, C., Degreef, J., Diagre, D., De Haan, M., De Smedt, S., Engledow, H., Ertz, D., Fabri, F., Godefroid, S., Hanquaert, N., Mergen, P., Ronse, A., Sosef, M., Stévart, T., Stoffelen, P., Vanderhoeven, S. & Groom Q. (2017). Scientific user requirements for a herbarium data portal. PhytoKeys 78: 37–57. https://doi.org/10.3897/phytokeys.78.10936 Willemse, L., Runnel, V., Saarenmaa, H., Casino, A. & Gödderz, K. (2020). Digitisation of private collections. Zenodo. https://doi.org/10.5281/zenodo.3598303 07 APPENDICES Appendix 1. Table of user story compilations from previous projects and other source documents Appendix 2. Use cases and functional demands tables Appendix 3. SYNTHESYS Transnational Access Analysis Appendix 1. Overview of existing user surveys, presentations, and other sources collaboratively collected by project partners. Author(s) (publication year) Title URL van Egmond, E., Willemse, L. & al. (2019) Design of a Collection Digitisation Dashboard https://icedig.eu/sites/default/files/deliverable_d2.3_icedig__design_of_a_collection_digitisation_dashboard_v1.0.pdf Raes, N. (2019) DiSSCo user stories collection https://dissco.teamwork.com/#/files/8287666 Raes, N. (2019) DiSSCo user stories presentation https://dissco.teamwork.com/#/files/8146993 Collection Description Interest Group (2020) Use Case Analysis https://docs.google.com/spreadsheets/d/1SsfwogZ88TgouDJ7EoDqXJFoleVs7aYdFx504qJNzc/edit#gid=0 Collection Description Interest Group (2020) Use Cases https://github.com/tdwg/cd/tree/master/reference/use_cases Anonymous (2020) User stories for SYNTHESYS Plus T2.2 dashboard https://docs.google.com/spreadsheets/d/1weWdM_5wCAdr49-rH8c5fgOrTTb8yYwnHsGpCw_oMo/edit#gid=2125639734 inspired from CETAF Earth Sciences group discussions (2020) User story for geological specimens Example of species page: https://www.mindat.org/min-4322.html GeoCase Portal http://www.geocase.eu/access DiSSCo user stories (2020) ordered user stories incl. ICEDiG Survey and ELViS Survey user stories https://github.com/DiSSCo/user-stories/projects/1 TDWG CD user cases use cases for collection descriptions https://github.com/tdwg/cd/tree/master/reference/use_cases Addink W., Belknap G. & al. (2017) DiSSCo Design Study Report unclear where published but study is known to the community Borsch & al. (2020) A complete digitization of German herbaria is possible, sensible and should be started now https://riojournal.com/article/50675/ Vissers, J., Bosch, F. van den & al. (2017) Scientific user requirements for a herbarium data portal https://phytokeys.pensoft.net/article/10936/ Petersen, M., Hoffmann, J. & Glöckler, F. (2019) Access to Geosciences – Ways and Means to share and publish collection data https://riojournal.com/article/32987/ Krishtalka L., Dalcin, E. & al. (2016) Accelerating the discovery of biocollections data http://www.gbif.org/resource/83022 ID CAT AS (POSITION) I WANT TO ... SO THAT I ... FOR THIS I NEED ... FUNCTIONAL DEMAND 1 FUNCTIONAL DEMAND 2 FUNCTIONAL DEMAND 3 FUNCTIONAL DEMAND 4 FUNCTIONAL DEMAND 5 1 1 Researcher, Scientist visit a collection and annotate additional information of specimens through an Unified Curation and Annotation System (UCAS) can capture information on geographical coordinates, locality, scientific name, accession number, collector name, and relevant measurements of specimens a CMS independent annotation system Annotation tools 2 1 Citizen Scientist curate and add untranscribed labels can contribute to the overall project, perhaps particularly on particular species groups a curation interface Physical access 3 1 Researcher, Scientist find out what is in the collection but not been digitised know whether its available for me to use a high level description of the collection Metadata on collection level 4 1 Researcher, Scientist look at a specimen that has been sequenced can confirm the identification before downloading the sequence from genbank a link from genebank to the specimen and a fully databased record with a high quality image of the specimen Interoperability Data integration Tools for identification 5 1 Researcher, Scientist examine a specimen that occurs in a GBIF record can confirm the identification and the geographic co-ordinates a link to the specimen from GBIF and a high quality image of the specimen and an image of the label data Metadata Interoperability 2D images Label images Tools for identification 6 1 Researcher, Scientist download a collection of images with a resolution of 400 dpi in jpeg 2000 format can use them as inputs for training a neural network designed to classify similar images a method to query and download image collections according to a set of parameters Tools for data discovery Metadata Images Tools for downloading data/metadata 7 1 Researcher, Scientist find out if there are additional images available from a particular specimen include different views of a specimen in a written report a reference to related images for a particular specimen Tools for data discovery 2D images Data integration 8 1 Researcher, Scientist find out if there is an alternative image available with a resolution of 300 dpi and in png file format select the appropriate image for including in a paper according to the publisher requirements a reference to the alternative image formats available Tools for data discovery 2D images Data integration 9 1 Researcher, Scientist retrieve the licensing information of an image know if I can use the image I want to include in a paper a reference to the image license Tools for data discovery 2D images Data integration 10 1 Researcher, Scientist Measure the specimen can compare the measurement differences between taxa/populations a scale/ruler in the digital image or a measurement tool for the image Tools for data analysis 2D images Tools for identification 11 1 Researcher, Scientist study morphological variability of a taxa can generate descriptions with extreme and median values a tool extracting morphological information, and statisticaly represent this information Tools for data analysis Morphological data 12 1 Researcher, Scientist find all marker sequence linked to a taxa and obtain statistic on spatial and taxonomic distribution of all specimens can build reference database a tool that parse correctly taxonomic data, spatial information Tools for data analysis Data integration Appendix 2. Use cases and Functional demands Life science 89 1 Researcher, Scientist know in which botanic garden a specific plant can be found as a living collection study its chemical traits list of living plants in collections Tools for data discovery 90 1 Researcher, Scientist know in which seed bank seeds of a specific plants are stored study its germination list of species stored as seeds in seed bank collections Tools for data discovery 91 1 Researcher, Scientist get a data dump on all institutions and their collections that can be sorted by Location (country, city, state), Institutional name, Domain name, Type of institution (public, private non-profit, private forprofit, museum, herbarium, etc.), Type of collection preservation (dry/room temperature, liquid/room temperature, cryogenic), size of collection Metadata on collection level 92 1 Food Security Official find herbarium specimens of a plant disease. compare genomes to modern day disease outbreaks. location of collections, genomic data (if existing), date. Metadata on collection level 93 1 Public health official compare sequences of anthrax identify the strain used in terror caused by sending anthrax letters location of museum specimens to be used for genetic studies / sequences of those specimens Tools for data discovery Metadata on collection level Data integration 94 1 Researcher, Scientist, Public Health Official locate museum specimens (eg. Egg shells) for study taxa study the effects of environmental contaminants location of museum specimens, number of specimens, location, date Tools for data discovery Metadata on collection level Data integration 95 1 Researcher, Scientist look for basic information about particular collection within an institution / a particular museum/herbarium/other biorepository institution Location: country, state, city; Institutional name, Institutional acronym, domain name, a webpage I can browse / webservice response Metadata on collection level 96 1 Researcher, Scientist compare the community compositions in water samples based on metabarcoding data can assess the impact of abiotic and anthropogenic drivers on community compositions metabarcoding sequence data Interoperability Molecular data 97 1 Citizen Scientist find specific info can use it in blogs, publications etc. metadata and photos Metadata Advanced search functionality 98 1 Researcher, Scientist do biographical research on specific collectors contribute to cultural history (e.g. colonial history) names of collectors and places of origin of specimens Metadata on collection level Data integration 99 1 Researcher, Scientist explore where specimen were found and at which time they lived there analyse spatio-temporal turnover in relation to environmental drivers nice visualisation tools of all specimen, which can be filtered by organism group or specimen Tools for data discovery Tools for data visualization 100 1 Anthropologis t Ethnoecology understand object's temporal context evaluate changes in the making of objects object measurements, historic owners Tools for data analysis Metadata on record level 101 1 Researcher, Scientist know the newest occurences of a certain alien species provide an impact assesment for decision makers occurence data, date, location, observations verified, number of individuals, timing & frequency of observations, uncertainty, distribution of a species Tools for data analysis Distribution data 102 1 Historian/rese archer know where plants from the genus Solanum are being cultivated based on botanical collection data can study the impact of introduction of Solanum plants to traditional agriculture occurrence data of Solanum plants within countries where they have been introduced, list of introduced Solanum species per country Tools for data analysis Distribution data 103 1 Researcher, Scientist get the data for Agrimonia eupatoria occurences create a species distribution model occurrence data of the plant: location, date, other metadata linked to observations/specimens, observations to be verified Tools for data analysis Distribution data 104 1 Researcher, Scientist see the where species from a certain genus occur can create a distribution map of each species occurrence data, location, date Tools for data analysis Distribution data 105 1 Researcher, Scientist, Public Health Official know where a mosquito species occurs / where it has been collected predict risk of new infections based on its distribution occurrence data, location, date Tools for data analysis Distribution data 106 1 Researcher, Scientist know all species occurring in an area and their population status create a red-list occurrence data, location, date, number of individuals, timing and frequency of observations, uncertainty Tools for data analysis Distribution data 107 1 Anthropologis t, Archaeologist, Paleontologist use digitized information on skeletal lesions investigate the type of work done and formulate hypotheses about the economy, lifestyle, and division of labor within ancient societies osteologic collections as an anthropologic archive Tools for data analysis Morphological data 108 1 Anthropologis t, Archaeologist, Paleontologist find macroscopic, histologic and radiographic studies of lesions on a skeleton. trace diseases affecting past populations and understand their origin and diffusion through identification of bacterial DNA osteologic collections as an anthropologic archive Tools for data analysis Morphological data 109 1 Anthropologis t, Archaeologist, Paleontologist find genetically determined characteristics (structure of dental tubercles and non-metric skeletal) study origin of populations and relations between them osteologic collections as an anthropologic archive Tools for data analysis Morphological data 110 1 Forensic Facial Reconstructio nist Facial 3D Modeling can bring a face from the past alive (famous historical figures, archaeological dig). Determine if two skulls from same family or population osteologic collections as an anthropologic archive, DNA, and photos. Tools for data analysis Morphological data 111 1 Anthropologis t, Archaeologist, Paleontologist Human Evolution access their catalogues, digital pictures and drawings (for old collections) as well as any other useful information for my research such as diaries, notes, and letters use fossil bones and lithic collections in museum and university collections upon which my research relies part description, place of collection or georeferenced locality, date of collection, object measurements, photos (scientific) Tools for data discovery Metadata on record level 112 1 Historian Geospatial Science understand historical disseminations of plants and animals, and long-term human influence on these; as well as how these collections have been constructed in a colonial/imperial/globalization context part description, place of collection or georeferenced locality, date of collection, collector Tools for data discovery Metadata on record level 113 1 Art Historian identify organic materials used in art (wood frames, paints) identify species and age of art materials provides temporal, social context reference collection, expertise, or DNA fingerprint Metadata on record level Molecular data Tools for identification 114 1 Paleontologist , Earth & Life Scientist access well preserved representative collection specimens to score morphological characters to take samples for genetic and genomic research better understand the evolution of organisms scientific name, part description, place of collection or georeferenced locality, collector, DNA, tissue sample Tools for data discovery Molecular data Morphological data Distribution data 115 1 Paleontologist , Earth & Life Scientist access to type materials link taxon names to clades scientific name, part description, place of collection or georeferenced locality, collector, DNA, tissue sample Tools for data discovery Molecular data Morphological data Distribution data 116 1 Anthropologis t, Ethnobotanist Medicinal and ritual plants have access to field notes or accession books as the information is often not written on object labels or not digitized from labels. compare plant uses scientific name, part description, place of collection or georeferenced locality, date of collection, collector, photos (scientific), historic owners, DNA Tools for data discovery Molecular data Morphological data Distribution data Images related to collections 117 1 Anthropologis t, Ethnobotanist Medicinal and ritual plants have access to associated data which are often not mentioned on the labels or digitized from the labels. study historic rice specimens scientific name, part description, place of collection or georeferenced locality, date of collection, collector, photos (scientific), historic owners, DNA Tools for data discovery Molecular data Morphological data Distribution data Images related to collections 118 1 Anthropologis t, Archaeologist, Historian, Linguist / Languages Spatial Humanities track the collection, use and dissemination of the resource, and understand its cultural value. investigate the historical exploitation of resources scientific name, part description, place of collection or georeferenced locality, date of collection, object measurements Tools for data discovery Morphological data Distribution data 119 1 Anthropologis t, Archaeologist Long-term humanenvironment, especially human-animal interaction, during preColumbian and early Historic Era times quantify the species' presence across sites, create chronological context, and conduct morphological comparisons across individuals understand the human impact on the spatial, temporal and cultural distribution and use of a species scientific name, part description, place of collection or georeferenced locality, date of collection, object measurements, DNA, isotopes, absolute or relative date of specimen life (not age or date of collections) Tools for data discovery Molecular data Morphological data Distribution data 120 1 Botanist Cross-cultural Ethnobotany verify and comprehensively compare my data with authentic online easily available resources scientific name, part description, place of collection or georeferenced locality, preparation, photos (scientific) Metadata on record level Morphological data Distribution data 2D images 121 1 Botanist Cross-cultural Ethnobotany have access to a comprehensive stock of online resources collect ethnobotanical data and specimen, and be able to compare the data with previous literature scientific name, part description, place of collection or georeferenced locality, preparation, photos (scientific) Metadata on record level Morphological data Distribution data 2D images Images related to collections 122 1 Paleontologist Evolution and Systematics of Ungulates know the species present in a locality (for zooarchaeological studies), the age of the site, and the environment study the evolution of animals in Prehistory scientific name, place of collection or georeferenced locality, (I) weight and body length of live specimen. Information available in a public catalogue. The objects label in the collection, should help identify the specimen and protect it against being mislaid. Metadata on record level Morphological data Distribution data 123 1 Paleontologist , Geologist Taphonomy identify substrate level preferences of genera analyze the impact of climate change on generic diversity, paleocommunities, and substrate affinity scientific name, place of collection or georeferenced locality, collector, object measurements, photos (scientific), stratigraphic and geological age attributes Metadata on record level Morphological data Distribution data 124 1 Anthropologis t Ethnoecology use reference collection objects, online resources and associated archives (photos) to identify a species determine the natural species used in the construction of objects scientific name, place of collection or georeferenced locality, date of collection, collector, photos (scientific) Metadata on record level Morphological data Distribution data 2D images Tools for data discovery 125 1 Anthropologis t Ethnoecology have physical or online access to similar collections including data and photos compare objects between our collections and similar collections in other institutions scientific name, place of collection or georeferenced locality, date of collection, collector, photos (scientific) Metadata on record level Morphological data Distribution data 2D images Tools for data discovery 126 1 Anthropologis t Ethnoecology check the existence, date of sampling, local names, description of uses, etc. of date palms in collections confirm presence and use of plants (date palms for instance) scientific name, place of collection or georeferenced locality, date of collection, collector, photos (scientific), DNA Metadata on record level Morphological data Distribution data Molecular data Tools for data discovery 127 1 Historian Cultural Heritage look up archival resources using data on the object label establish the history of science (taxonomy in the 19th century) scientific name, place of collection or georeferenced locality, date of collection, collector, preparation Metadata on record level Morphological data Distribution data Tools for data discovery 128 1 Historian locate all specimens and objects associated with a particular expedition or exhibition. investigate the collection of a particular species of crocodile from an expedition to Borneo around 1841 scientific name, place of collection or georeferenced locality, date of collection, collector, preparation, photos (scientific), historic owners, cause of death Metadata on record level Morphological data Distribution data Tools for data discovery 129 1 Historical Ecologist / Environmental Historian obtain occurrence and abundance data in the past reconstruct biodiversity in the past scientific name, place of collection or georeferenced locality, date of collection, object measurements, cause of death Metadata on record level Morphological data Distribution data Tools for data discovery 130 1 Historian Cultural Heritage access archives using data on the object label trace the origin, movement and history of collections scientific name, place of collection or georeferenced locality, date of collection,collector, historic owners Metadata on record level Morphological data Distribution data Tools for data discovery 131 1 Paleontologist , Earth & Life Scientist access collection catalogues, accession books, literature, or where provenance is unclear, biographic material, field notes, and historical maps understand what previous researchers meant by a specific taxon name scientific name, place of collection or georeferenced locality, date of collection,collector, historic owners Metadata on record level Morphological data Distribution data Tools for data discovery Images related to collections 132 1 Anthropologis t Ethnoecology check all mentions of plants (with date, attribution) used, collected, traded, etc. in a given area analyze the evolution of agriculture in an oasis scientific name, place of collection or georeferenced locality, date of collection,collector, photos (scientific), historic owners Metadata on record level Morphological data Distribution data 2D images Tools for data discovery 133 1 Anthropologis t, Historian History of Science know exactly where and when collected, what kind of data (e.g., vernacular names, uses) was collected, and subsequent movements of the specimens including public display in galleries where this occurred understand how a group of ethnobotanical specimens was collected and what this tells us about (a) the source community and (b) the motivations of the collectors and subsequent institutions scientific name, place of collection or georeferenced locality, date of collection,collector, photos (scientific), historic owners Metadata on record level Morphological data Distribution data 2D images Tools for data discovery 134 1 Anthropologis t, Historian History of Science check historic plant resources to enable me to determine what was available in the region and what it looks like. check identification of plant material in an ethnographic object scientific name, place of collection or georeferenced locality, date of collection,collector, photos (scientific), historic owners Metadata on record level Tools for identification Morphological data Distribution data 2D images 135 1 Historian The history of natural history ascertain all relevant historical information on an object write an object biography of an important object from a natural history museum scientific name, place of collection or georeferenced locality, date of collection,collector, photos (scientific), historic owners Metadata on record level Tools for data discovery Morphological data Distribution data 2D images 136 1 Historian locate digitized specimen collection records, associated photos and archives describing the collecting event. investigate the collection of a particular species of crocodile from an expedition to Borneo around 1840 scientific name, place of collection or georeferenced locality, date of collection,collector, photos (scientific),historic owners. Other: societal context of object at the time of collection. Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 137 1 Geologist fill-in data gaps regarding specimens and collections with limited (species name and locality) data scientific name, place of collection or georeferenced locality Metadata on record level Distribution data Tools for data discovery 138 1 Anthropologis t, Historian, Philosopher, Sociologist Science fiction, Datafication of nature follow the epistemic life of an object as it is involved and shapes research practices scientific name, sex / age part description place of collection or georeferenced locality, date of collection, photos (scientific), DNA, geological references Metadata on record level Tools for data discovery Morphological data Distribution data Molecular data 139 1 Anthropologis t Physical Anthropology check the accession books, field notes or diaries, and possibly correspondence and notes study the history of collections scientific name, sex / age part description, place of collection or georeferenced, locality, collector cause of death Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 140 1 Anthropologis t, Archaeologist Long-term humanenvironment, especially human-animal interaction, during preColumbian and early Historic Era times quantify target taxa across a site(s), determine age and sex to create mortality and demographic profiles of the taxa, conduct aDNA to assess impacts of human influence on population genetic diversity, and use isotopic analysis to assess diet. identify patterns of animal management or incipient domestication scientific name, sex / age, DNA, isotopes Metadata on record level Tools for data discovery Isotopic data Distribution data Molecular data 141 1 Anthropologis t Physical Anthropology Identify the field notes and drawings of the archaeologist reconstruct a prehistorical population scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, historic owners, cause of death Tools for data discovery Metadata on record level Morphological data Distribution data Images related to collections 142 1 Anthropologis t, Archaeologist, Paleontologist Human Evolution compile information such as scientific name, dating, geographic information on the localities where they were found, basic quantitative and qualitative description. Field notes, illustration (drawings and photos), and any other useful information about them that was published or unpublished. research fossils and prehistoric stone tools scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, object measurements, photos (scientific), Tools for data discovery Metadata on record level Morphological data Distribution data Images related to collections 143 1 Ethnobotanist Biocultural Heritage use information from historical collections that have information to be integrated. infer about the history of biodiversity in the area of the Brazilian Amazon scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, preparation, object measurements, photos (scientific) Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 144 1 Classicist, Linguist, Languages Literature, Digital Philology make augmented text searches; establish georeferenced localities connect realia to encyclopedic information for historical documents (e.g. WWI & WWII documents or ancient Greek documents) scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, preparation, object measurements, photos (scientific), historic owners Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 145 1 Anthropologis t, Historian, Philosopher, Sociologist Science fiction, Datafication of nature understand the transforming objectivities [sic] of specimen in natural history collections, and trace them across different media and databases scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, preparation, object measurements, photos (scientific), historic owners, cause of death Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 146 1 Historian History of Sciences, Scientific Illustrations, History of Photography use all available resources, for example, a specimen's sex, age and date of collection is relevant for identifying a possible bias of the collectors/collection during a certain period of time put a collection in socio-historical context scientific name, sex / age, part description, place of collection or georeferenced locality, date of collection, collector, preparation, object measurements, photos (scientific), historic owners, cause of death Metadata on record level Tools for data discovery Morphological data Distribution data Images related to collections 147 1 Historian History of Sciences, Scientific Illustrations, History of Photography Use all available sources of information, images, text (publications, correspondence, notes, etc.) audio, or moving image of an object / subject fully understand/trace an object or subject's history (how an object came to the institution, provenance, circumstances of collecting event) scientific name, sex / age, part description, place of collection or georeferenced, locality, date of collection, collector, preparation, object measurements, photos (scientific), historic owners, cause of death, provenance form of acquisition Metadata on record level Data integration Morphological data Distribution data Images related to collections 148 1 Sociologist Cultural policy scientific name, sex / age, place of collection or georeferenced locality, date of collection Metadata on record level Tools for data discovery Morphological data Distribution data 149 1 Researcher, Scientist find specimens matching a DNA sequence I have generated can identify collected material similar to my sample (and thereby identify my sample) searchable records of DNA sequence linked to collected material Tools for data discovery Molecular data 150 1 Public health official look for viruses found in animal tissues in collections identify an unknown vector for a disease sequence data, links between collections Metadata on record level Data integration Molecular data 151 1 Paleontologist , Geologist Taphonomy easily discover specimen-related literature and speed data recovery single database interface linking specimens with their literature or metadata Metadata Data integration 152 1 Paleontologist , Geologist Taphonomy access georeferenced modern and fossil occurrence data for species throughout their geographic distributions in the Atlantic Verify taxonomy of each species occurrence and pair with temperature and salinity measurements study how climatic changes drove thermophilous mollusk species migrations during the Pleistocene single database interface linking specimens with their literature or metadata Metadata on record level Data integration 153 1 Researcher, Scientist previouly collected specimens with their taxon and geographical area the relevance of additional studies can be determined specimen taxa and location of collection Tools for data discovery Distribution data 154 1 Data Scientist create novel views of the data get added value out of linking different types of information, e.g. collection data with phylogenetic trees, sequence data, literature citations, travel reports etc stable, reliable identifiers of collections and collection objects (specimens) Tools for data discovery Data integration 155 1 Researcher, Scientist query when and where one or more species have been recorded, and their characteristics, and the institutions that archive specimens can collect more specimens, or borrow collections taxonomic fields, geographic coordinates, date Tools for data analysis Morphological data Distribution data Ecological data Data integration 156 1 Researcher, Scientist query when and where one or more species have been recorded, what their characteristics are, and which institutions archive the specimens can use more specimens, or borrow collections from other institutes taxonomic information, geographic coordinates, date of collecting Tools for data analysis Morphological data Distribution data Ecological data Data integration 157 1 Food Security Official see reference specimens for pests can identify origins of newly found pest populations and study possible bioterrorism temporal and geographic range of existing specimens Metadata on record level 158 1 Researcher, Scientist use samples from zoological specimens in museums and zoos can use this information for genetic management of ex-situ conservation breeding programmes and can develop science-based conservation action plans for endangered species tissue samples, DNA, and/or sequence data, taxonomic information Interoperability Morphological data Molecular data Physical access Data integration 159 1 Researcher, Scientist have an overview of the geographic/spatial coverage of a certain taxonomic part of a collection can assess the need for gathering further data or evaluate the usefulness of a certain collection for a certain analysis to be able to filter specimens by collection, area and taxonomic identity Metadata on collection level Tools for data discovery 160 1 Researcher, Scientist to find type specimens can verify and understand its taxonimic concept to be sure this name is understood uniformerly Tools for data discovery 161 1 Researcher, Scientist find which pathogens share geographic distributions with a taxon of interest can filter potential pathogens that cause a disease to combine different data sources of species occurrences Tools for data analysis Distribution data 162 1 Researcher, Scientist find which pollinators share geographic distributions with plants can construct plant-pollinator networks to combine different data sources of species occurrences Tools for data analysis Distribution data 163 1 Researcher, Scientist study the details of the organs can identify the specimen as with a binocular to download images with a resolution of 600 dpi minimum (300 dpi is insufficient). 2D images Tools for downloading data/metadata Tools for identification 164 1 Researcher, Scientist destructively sample for pollen, anatomy and DNA can construct phylogenies and understand evolution to know policies associated with each specimen. Legal and policy framework 165 1 Researcher, Scientist know where the specimens are kept in the collection can find them in the collection to know the number of the boxes where the specimens are kept Metadata on record level 166 1 Researcher, Scientist get data from specimens of species from which I obtained trait data through EOL Traitbank can study geographical patterns of (functional) traits to query DiSSCo through EOL traitbank selections Tools for data discovery Interoperability Ecological data 167 1 Researcher, Scientist get data from specimens from which I obtained sequence data through genbank can study geographical patterns of genetic variation to query DiSSCo through Genbank accessions Tools for data discovery Interoperability Molecular data 168 1 Researcher, Scientist extract data on the variation in specimens of the same species can study trait variation within a species to select trait data from specimens Tools for data discovery Ecological data 169 1 Researcher, Scientist extract species occurrence data in a particular location or area see whether data exist in the first place and if exist use it for analyses of spatial/temporal variation in biodiversity tool to define the extracting and data retrieval system Tools for data analysis Distribution data 170 1 Researcher, Scientist extract trait data, which might include phenology and morphology can analyse the phenology or trait variation within species trait data of species, either from the specimens or from EOL traitbank Tools for data discovery Interoperability Ecological data Morphological data Tools for data analysis 171 1 Researcher, Scientist search for all type specimens of a certain genus verify that a species I think is new to science is really that type specimens digitized with highresolution images, annotations, synonyms, species characters, genetic data, phytochemistry Tools for data discovery Label images 2D images Morphological data Molecular data 172 2 Collection Manager make a locality check or search for old and correct names for labeling (historic) maps Metadata Images related to collections Tools for data discovery 173 2 Digitization Officer link specimen & label images the corresponding occurence data can make the images as publicly visible and usable as possible a (semi)automatic label data extraction & verification system Tools for downloading data/metadata Distribution data Label images 2D images Data integration 174 2 Collection Manager receive information on the GeneBank numbers and analysed molecular data can link this back to specimens, tissue or DNA samples a connection of genetic data (e.g. shared genetic libraries) which are interlinked with specimen database entries at my home institution Advanced search functionality Data integration Interoperability 175 2 Curator attach and deliver geochemical data to rock and mineral specimen records retrieve specimens based on their geochemical signature a portal compatible or similar to the Earth Chem portal funded by NSF http://www.earthchem.org/ Advanced search functionality Tools for uploading Biochemical or geochemical data Data integration 176 2 Curator monitor and in specific cases restrict access to geographical coordinates of collection sites stop ruthless exploitation of strictly protected species a possibility to personally evaluate every request for a combination of certain data categories, and the possibility to modify the answer to a data request Tools for limiting access to data 177 2 Curator enrich my collection with reliable annotation from specialists anywahere in the world can increase the valua of my collection a quality / reliability rating of annotators Tools for annotation 178 2 Curator publish my data online can increase the value of the collection a user friendly collection management system (CMS) Tools for uploading 179 2 Collection Manager be able to access information about storage conditions/status for specimens can optimise the storage of my own collections and plan for future acquisitions access to storage/status information of specimens Tools for data discovery Metadata on collection level 180 2 Citizen Scientist add label information to the specimen records can contribute to scientific data access to the DiSSCo portal Tools for annotation Tools for uploading 181 2 Museum Preparator know how old specimens are prepared in other collections When restoring historical specimens we need as much information as possible about how they were prepared accession books, collection catalogues, field notebooks / diaries, correspondence Metadata on collection level Images related to collections 182 2 Collection Manager access unique information such as orginal descriptions, pictures or species drawings can ID (exotic) species in the collection accession books, rare books / special collections, photos Metadata on record level Images related to collections 183 2 Collection Manager document the backlog (uncatalogued collections) of a cross-disciplinary notfor-profit museum. to prioritize areas in need of digitization accession records Metadata on record level 184 2 Digitization Officer produce digital specimens from a digitisation line can store a specimen in my collection management system (CMS) and can upload the images to a customer's CMS an automated workflow minting persistent identifiers (PIDs) Tools for uploading Data integration 185 2 Citizen Scientist know where a certain collector was on a certain day can help to transcribe a specimen an existing transcription of a specimen that was collected around the same time by the same collector Metadata on record level Advanced search functionality 186 2 Curator annotate all aspects of records, suggest improvements, and record logical connections between records (link museum samples to corresponding occurence records) can provide duplicate-free, reliable, well-documented data to end users an record-level annotation and communication system spanning across institutes Annotation tools Data integration 187 2 Collection Manager have a tool to estimate undigitized backlog hidden collections can be revealed, estimate the remaining effort for digitization collection name, collection id, storage/preservation type, number and kinds of items, geographic scope, time, taxonomic scope, possibly list of taxon / species names, important collectors, thematic interest focus, digitization status Tools for reporting & statistics Metadata on collection level Morphological data Distribution data Ecological data 188 2 Curator answer multiple requests on a specified taxon / collector / geographic area can follow conversation about a request communication thread by taxon / collector / geographic area Tools for clustering requests 189 2 Curator be recognised as contributor can apply for funding to digitise institutional collections contribution indicators (as contributor) Tools for reporting & statistics 190 2 Curator attach relevant references to the specimen record document curatorial decisions custom downloadable references Tools for uploading 262 4 Association To gather information to have overall figures representative of partners' state-of-the-art we can showcase the relevancy of the collections hold to policy makers and attract funds High-level figures that feature the collections as a whole Legal and policy framework Tools for reporting & statistics 263 4 Conservation Planner cross-check species identification against reliably identified specimens create a checklist of species images, sequence data, georeferences, traits 2D images Molecular data Morphological data Metadata on collection level Distribution data 264 4 Biomonitoring Planner cross-check species identification on diatoms against reliably identified specimens create water quality assesment indicator values, digitized microscopic collections 2D images Tools for reporting & statistics 265 4 Policy maker know the use of the collections by other domains as a key indicator of its impact can distribute resources and allocate them in alignment to the strategic priorities of the government that I represent information on access to the collections, virtually and physically, from different types of users Legal and policy framework Tools for reporting & statistics 266 4 Director understand the relationship of our own collection to the collections of other institutions in our country. can explain the scientifc value and unicity of our collection to policy makers information on collection type, size and taxonomic breadth of other institutes. Tools for reporting & statistics Legal and policy framework 267 4 GBIF Node Manager manage collection metadata in a national scale catalog, while being aware of overlaps and possible conflicts with descriptions held/curated in other places (e.g. IH). can maintain an overview of our national holdings and can provide relevant and up-to-date information to my constituents, and can spot conflicts with such duplicates to see that they are resolved or highlighted institutional metadata (name, institution id, physical address, website, contacts); collection name, collection id, storage/preservation type, number and kinds of items, geographic scope, time, taxonomic scope, important collectors, thematic interest focus, digitization status; links to related objects (collection metadata entry) in other parts of the catalogue; editing trail (who, when, what action), link assertion (duplicate of, older version of, etc). Metadata on collection level Tools for reporting & statistics 268 4 GBIF Node Manager, Collection Manager register a core description of collections under my domain. the existence of the collection is publicly visible next to others, its potential value can be made explicit, and there is motivation for the linking, capture and publication of additional descriptive information (specimen records, checklists, image data, sequences, etc). I can also use this to argue the need for funding of both maintenance and further digitization of the collection itself. institutional metadata (name, institution id, physical address, website, contacts); collection name, collection id, storage/preservation type, number and kinds of items, geographic scope, time, taxonomic scope, important collectors, thematic interest focus, digitization status. Metadata on collection level Tools for reporting & statistics 269 4 Policy maker keep track of all specimens collected in National Parks inventories and collection assesments can be made up location at which specimens are collected Advanced search functionality Distribution data 270 4 Director know the extent of the use of the organisation's collections across societal sectors. can take informed executive decisions related to future investments (both collections and HRs) metrics of the use of collections Metadata on collection level Tools for reporting & statistics 271 4 Researcher, Scientist easily identify which genetic resources I can directly request from a natural history collection can fullfill my due diligence obligations under the EU ABS regulation when requesting tissue or DNA-samples from an ex-situ situation inside Europe not only information on the sample, but also on the status and reference on the access status (without legal doc scan in the www!) Legal and policy framework Metadata on collection level Tools for data discovery 272 4 Policy maker (law enforcement) find quality indicators of an herbarium decision can be made on granting permissions (e.g. CITES permit) number of type specimens of the collection, total number of specimens, number of researchers attached to the institute, level of digitalisation... Metadata on collection level Legal and policy framework 273 4 Law Enforcement find back specialists in a specific domain request identification of unknown specimens (e.g. at customs) people connected to an herbarium with their respective expertises. Metadata on collection level Tools for identification 274 4 Policy maker, Collection Manager track changes in collections over time (name changes, merges, ) there is a unique way to reference to collections (e.g. linking specimens to the correct collections after a collection merge or split) stable collection identifier, collection names Metadata on collection level Data integration 275 4 Policy maker, Collection Manager know nested relationships between collections In case of collection merges or splits, it is possible to trace back the origin of a collection sub-collections Metadata on collection level 276 4 Collection Manager, Director, Administrator know the situation with collection amounts can plan ahead for future needs for new space and storage to know existing amounts of collections, and amount of new material coming in. Also, need to know status / condition (wet, dry, ...) of existing material. Also collection health information. Metadata on collection level Tools for reporting & statistics 277 4 Collection Manager start a digitisation project can digitize a certain group of my collection; I like to do this internationally because of funding to know which other institutes hold collections of this group Metadata on collection level Tools for data discovery Data integration 278 5 Teacher find out if there is a printable version of a 3D model with a high resolution 3D model can create a 3D physical model for study in class and can use a hologram projector for inspection of the specimen in class a reference to the available 3D models 3D images Tools for data discovery 279 5 Student find the referencing information for an image can cite the source in a written report which includes the image a reference to the citation information for the image 2D images Label images Data integration 280 5 Student find a high resolution image can perform morphological analysis as part of my coursework a reference to the higher resolution image and the clear procedure to retrieve it Advanced search functionality 2D images 281 5 Teacher to be able to have accurate physical models of animals and plants can use them in my lessons to illustrate the biology of life-forms access to taxonomic information, photographs, measurements etc of specimens Advanced search functionality 2D images Label images 282 5 Teacher show that organisms have restricted geographical distributions can teach on biodiversity and biogeography distribution data of organisms Tools for georeferencing Tools for data visualization Distribution data 283 5 Student do autonomous exercises linking multiple types of data gain a deeper understanding of biodiversity and its evolution; understand the purpose, power and limits of collection data DNA sequence link, taxon interactions, morphology, location, taxon concept Molecular data Morphological data Distribution data Ecological data Data integration 284 5 Teacher be able to provide accurate scientific information about species and specimens can educate students/the public about the natural world easily accessible and up-to-date information about the specimens in museum collections Advanced search functionality Tools for data discovery 285 5 Head, Educational Development browse all digitized collection data in our institute could use this for context rich, digital educational activities. In which we not only focus on biological concepts, but also on the cultural historic aspect of our collection and research. This fits well with our goals to enhance science literacy. field notebooks / diaries, correspondence, (historic) maps drawings, photos, paintings, audio, video Tools for data discovery Images related to collections Data integration 286 5 Digital Collection Manager, Citizen Scientist browse all digitized data linked to an expedition create online and in-house exhibitions focused around expeditions where specimens and cultural objects tell a story of what was collected and what existed along their expedition path, their field notes (from Archives) describe their daily activities in a way which cannot be gleaned through the scientific record of collection and publication and add a humanities angle to the expedition, the literature that arose from specimens found on the expedition can be sourced from the library. field notebooks / diaries, correspondence, (Historic) maps,drawings, photos, paintings, audio, video Tools for data discovery Images related to collections 287 5 Student check my identification of a specimen can test my bioliteracy and and learn more about a taxon/ecosystem I am studying image/morphology, links to papers / protologue, collection metadata (habitat, taxon interactions) Tools for data discovery 2D images Images related to collections 288 5 Exhibition Designer be able to find the location of specimens and information about species. can design and realise interesting and accurate exhibitions and if required, loan specimens from otgher institutions information about the location and status of specimens in museum collections. Metadata on collection level 289 5 Science Communicatio n Officer know about the research being carried out in natural history collections can organize a dissemination event information on research topics and the people behind them Metadata on collection level 290 5 Teacher find out extant relatives of fossil plants in a living collection of a botanic garden teach palaeontology for my students list of living plants in collections, links their relative extinct species, digitized specimens of extinct species Advanced search functionality Metadata on collection level 291 5 Teacher show morphological and genetic diversity within a taxon can explain basic concepts in evolution, systematics, taxonomy, ecology etc. overview of comparable data (image, DNA sequence link, location) for multiple specimens from taxonomic group Molecular data Morphological data Distribution data 2D images 292 5 Teacher learn about the variety of life and the relationships among species and their environment teach my students that we are all inter-connected and that Homo sapiens is not the "best" species on Earth species names, images, distributions, habitats, needs, behaviour, ecological niches, relationships 2D images Morphological data Distribution data Ecological data 293 5 Curious person learn about the species that might be in my environment can improve my bioliteracy taxonomic fields, common names, geographic coordinates, species characteristics, images Advanced search functionality 294 5 Student be able to identify the species in scientific field trips, without visiting the relative collections of NHMs save time and money, by avoiding the physical travelling to those NHMs to have access to the NHMs' digitalised species' identities (morphometric characters, names, distributions, etc.) 2D images Morphological data Distribution data 295 6 Developer find a 360 degree view or a 3D model of a specimen can use it in the creation of interactive content for use with augmented reality educational software a reference to the available 3D models 3D images 296 6 Publisher include a digital image from a collection in a scientific paper can illustrate the publication access to the digital images and copy rights to use the image 2D images Tools for downloading data/metadata 297 6 Digitisation Officer produce digital specimens from a digitisation line can upload the images to a customer's CMS an automated workflow minting PIDs Tools for uploading 298 6 Mining Company Official know where a species occurs based on museum collections and occurences map the distribution of a wanted mineral through a metallophyte (plant indicating presence of a mineral) collections digitized, observations, location, date Advanced search functionality Distribution data 299 6 Automatic identification systems developer Which collections are available to use as a reference (training data set) can training my algorithms for automatic identification collections of target species (validated) Interoperability Advanced search functionality Metadata on collection level 300 6 Collection Manager look up herbaria that have complementary collections specimens can be exchanged collector data, geographical regions of collection items, taxon data Metadata on collection level Tools for data discovery Data integration 301 6 Collection Manager look up the correct shipping address of other herbaria address shipping boxes for loans and other exchanges of specimens contact metadata of institutions Metadata on collection level 302 6 Software developer develop new usages of the data and ways to add information to the data, through apps or web interactions can make the data easier accessible to the general public and facilitate that different collections can be, for instance, cross-referenced. At the same time the additional data can updated in the core databases. Addition of geographic locality data as most users hold an handheld GPS device. detailed collection level information Metadata on collection level Tools for data discovery 303 6 Software developer train my image recognition software can use it for taxon recognition images, digitized specimen data 2D images Morphological data 304 6 Systems developer know information on which collections are available to use as a reference (training data set) can train my algorithms for automated identification information on validated collections of target species Metadata Tools for identification 305 6 Solution Provider build and provide solutions and related services the curators and scientists can work better and easier with their collections at less financial costs information on volumes, locality data, physical storage volumes, plus an insight on what is digitally represented and what is not. Institution digitisation priority list. Metadata on collection level Tools for data discovery 306 6 Collection Manager have a metric on reliability of other herbaria decide over loan requests number of type specimens of the collection, total number of specimens, number of researchers attached to the institute, level of digitalisation... Metadata on collection level Tools for data discovery 307 6 Collection Manager look up individuals with a specific expertise can request identification or evaluation of a specimen people attached to instutute and their respective expertise Metadata on collection level 308 6 Project Leader identify participants and resources the relevant people/institutions are included in the project possible data elements are: - herbaria that contain type specimens - location of the herbarium - expertise of an herbarium Advanced search functionality Metadata on collection level 309 6 Solution Provider tap into the vast market of digital storage solutions for digital natural collections can sell my services and consultancies predictable numbers on collection type, volume and progress in digitization Tools for reporting & statistics Tools for data discovery 310 6 Solution provider tap into the vast market of digital storage solutions for digital natural collections can sell my services and consult predictable numbers on collection type, volume and progress in digitization Tools for reporting & statistics Tools for data discovery 311 6 Crop Breeder know where crop wild relatives (phylogenetic related species) are growing select species that are adapted to certain environmental conditions to combine phylogenetic information with species occurrence data Tools for data discovery Tools for data analysis Tools for georeferencing Distribution data Ecological data incl. traits 312 6 Editor use Index Herbariorum codes / unique identifiers of collections identify the place of deposition of a specimen and specimens can be cited correctly and unique identifiers of collections IH(-like), specimens connected to a collection Metadata on collection level Interoperability Data integration 313 6 Solution Provider build and provide solutions and related services the keepers and scientists can work better and easier with their collections for less cost volumes, locations and physical sizes plus an insight on what is digitally represented and what not. Institutions priority as to what needs to be digital first. Metadata on collection level Tools for data discovery 314 7 Journalist link to primary source data (scientific literature, museum collections databases, etc.) my readers can learn more about the topic of an article collections database records Tools for data discovery Tools for data analysis Tools for downloading data/metadata 315 7 Saxophonist, Composer, Producer, Educator map the nucleobase and amino acid sequences that comprise the orchid’s DNA codes to form individual movements for each of the five evolutionary families of the genus compose an étude (Orchidées) on the evolution of the genus Orchidaceae DNA sequences Molecular data 442 7 Public relations officer / Press officer visualize what is currently stored in the collections and how it has developed and is developing over time using maps or other graphical representations I can use it for self-marketing or for public information to be able to sum up certain data categories from the collections and to export these data to be able to use them in special data visualization tools Tools for reporting & statistics Tools for downloading data/metadata Tools for data visualization 443 7 Marketing officer have infographics presenting information and data on the collection incl. geographical or temporal visualization of numbers and sums, connections, relations, and correlations I can offer these infographics to newspapers or use them for self-marketing to be able to sum up certain data categories from the collections and to export these data to be able to use them in special data visualization tools Tools for reporting & statistics Tools for downloading data/metadata Tools for data visualization CAT (Category based on ICEDIG T6.2) 1. Research (academic & non-academic, including citizen science) 2. Collection management 3. Technical support (IT & IM) 4. Policy (institutional, national & international) 5. Education (academic & non-academic) 6. Industry 7. External (media & empowerment initiatives) 1 Appendix 3. SYNTHESYS Transnational Access Analysis In addition to surveys and approaching (potential) new users of the DiSSCo research infrastructure, NHMUK analysed the SYNTHESYS Transnational Access (TA) programme. As of September 2020, the TA dataset covers over 4,450 funded visits totalling over 54,000 researcher days to 26 collectionholding institutions in 14 countries with c. 12,300 self-reported research outputs. The full report includes background information and context, methodology (database review, standardisation, schema analysis and modelling, analysis database construction, data cleaning and enhancement), analysis (preparation of a publishable analysis database with removal of personally identified information (PII), DOI matching). The report will be submitted as a formal publication before June 2021. A summary of the results for demographics, functional demands on collections and facilities, and socio-economic impact is given below. The SYNTHESYS Transnational Access data was harder to analyse than we had anticipated. When the access database was originally created it was not designed to analyse outputs. There was no verification of outputs by an administrator so the data quality is variable and contains user errors. Manual verification of the entire output dataset is time consuming – designing future systems that track the research outputs associated with collections or specific facilities should utilise automated validation or using controlled vocabularies. This would make subsequent analysis easier. Future analysis could study the authors and their collaborators to understand their research fields and backgrounds. Data mining acknowledgements to study co-funding sources would potentially give an insight into cross-disciplinary work. Studying publications with the highest downstream citations would give an alternative metric for understanding impact of research but comes with its own limitations. In terms of functional requirements for facility and collection access, further work could be usefully carried out on the relationships between collection access requirements and facility access requirements. One promising area of investigation would be to analyse any trends between collection type and analysis facility usage: does more than one installation per project reflect a dependency between collection access and availability of analysis facilities, or is the cause of this overlap driven by more pragmatic factors around availability of access to collections/facilities during a SYNTHESYSfunded visit? These kinds of questions may be useful for DiSSCo when trying to anticipate the needs of its future users. The absence of a controlled vocabulary around the types of collection users wish to access makes it difficult to get more granular data around demand for, and usage of, these collections. Time permitting, more detail could potentially be extracted by running a Named Entity Recognition algorithm over unstructured data fields that are likely to contain useful information, e.g., project title and anticipated research benefits. For future tracking of outputs across DiSSCo partners and in SYNTHESYS successors we recommend using a more sophisticated system that would support text mining and automated analysis. Tracking outputs from facility and collection usage is an important metric but poorly supported by the systems and data we currently have to hand. Demographics As of late 2019, 64% of applications submitted to the SYNTHESYS TA programme were made by men, 36% by women. 2 Figure A3.1. Proportion of applications by gender and age at point of application (F - female, M - male). Women were most likely to apply during the postgraduate stage of their career (44% of all applications by women), whereas the dominant career stage recorded by male applicants was 'experienced' at 37% of the total (see Figure A3.1). Overall, 34.5% of applications were made by postgraduates, 31% by postdocs, and 31% by 'experienced' career-stage researchers. Technical applicants comprised 1.5% of overall applicants and undergraduates 2.5%. The most common age bracket for applicants at the point of application is 25-34 years of age (43.6% of all applications submitted), followed by 35-44 years (27.4%). The prevalence of younger, earlier-career applicants in the TA scheme is not surprising: established researchers are more likely to have additional avenues of funding available for a research trip. The drop-off in numbers of female applicants after their early 30s seems likely to reflect a paucity of time, rather than funding (Cech & Blair-Loy 2019). Functional demands The functional requirements for all applications were investigated in order to derive a more accurate overview of functional demands for institutional collections and services independent of TA Programme's administrative practices, which exist in part to ensure that demand for a particular category of service or collection does not overwhelm available host capacity. At the national level, institutions in the UK received the most access requests through the SYNTHESYS TA scheme (30% of total), followed by France (11%) and the Netherlands (10%). Approximately 60% of all access requests are made to collections and the remaining 40% are targeted towards analytical facilities. The majority (58%) of applicants requested access to more than one collection and/or analysis facilities within a single project application. Request distribution over the different access categories has stayed consistent over time (see chart below, Figure A3.2). SYNTHESYS Round 4 data is incomplete because it is still ongoing, so the increase in imaging requests visible in this round may not be sustained throughout. 3 Figure A3.2. Chart showing distribution of request count by category of host facility or collection. Round 1 (n = 8.5k), Round 2 (n = 5k), Round 3 (n = 6.2k), Round 4 (Incomplete: n = 2.8k). User discipline diversity and socio-economic importance CrossRef records were found for 2,780 articles (22.6%) of the 12,280 self-reported research outputs provided by users after removing duplicates. Of these, 2,431 were identified by searching for the title and authors using the CrossRef API's search functionality, 672 (20.7%) had a user-provided DOI, and the remainder were identified from DOIs extracted from other user-provided data. These CrossRef article records were then checked for potential discipline diversity and socio-economic impact using two approaches: 1. Automated journal subject tagging – looking for atypical subject tags that were neither life sciences or earth sciences 2. Manual title checks - looking for papers of more immediate societal relevance From the automated journal subject tags we counted the number of non-Life/Earth Sciences research outputs in each subject tag category (see Figure A3.3). The majority fell into general medicine with a fairly broad distribution across 28 other categories. While this was a useful summary it did not provide enough information to make any judgements on socioeconomic importance. 4 Figure A3.3. Subject tags of non-Life/Earth Sciences research outputs. Manual title checks were the most reliable way of checking whether a research output mapped to one of the seven H2020 Societal Challenges which we were using as a proxy for socioeconomic importance. We manually checked each of the 2,780 publication titles and verified if the paper cited SYNTHESYS in either the acknowledgements or funding metadata. This resulted in 199 outputs that mapped to a societal challenge of which 49 acknowledged SYNTHESYS. The majority (37) mapped to the “Climate action, environment, resource efficiency and raw materials” and depending on how strictly you consider the “environment” component of the challenge then many more of the 2,780 could be assigned here. Six outputs were assigned to the “Food security, sustainable agriculture and forestry, marine and maritime and inland water research, and the Bioeconomy” with the final six evenly distributed into “Health, demographic change and wellbeing”, “Europe in a changing world – inclusive, innovative and reflective societies” and “Secure societies – protecting freedom and security of Europe and its citizens.”