DiSSCo Prepare Deliverable D1.2 - Report on Earth sciences use cases and user stories

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Title DiSSCo Prepare Deliverable D1.2 Report on Earth sciences use cases and user stories Author(s) von Mering, Sabine Petersen, Mareike Fitzgerald, Heli Juslén, Aino 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/0000-0003-2982-7792 https://orcid.org/0000-0001-8666-1931 https://orcid.org/0000-0002-6754-6409 https://orcid.org/0000-0001-9434-5250 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 Museum für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany 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/n3dk-ds60 Publication year 2021 Related identifiers https://doi.org/10.7479/17qp-ge55 (Data publication) https://doi.org/10.34960/xhxw-cb79 (D1.1) 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 von Mering, S., Petersen, M., Fitzgerald, H., Juslén, A., 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/n3dk-ds60 Abstract This Deliverable D1.2 from the project DiSSCo Prepare reports the results of Task 1.2 “Analyse Earth sciences use cases and user stories”. A total of 128 Earth sciences user stories and use cases was analysed with a special emphasis on the functional demands and required services for the DiSSCo Research Infrastructure. Use cases were gathered from surveys, publications and personal interviews, they were assigned to one out of seven stake-holder groups. For each use case up to five functional demand categories were assigned. Use case analyses revealed that the most important demands for Earth science collections were ‘Metadata on collection or record level’, ‘Advanced search functionality’, ‘Data integration’ and 'Tools for reporting & statistics’. The socio-economic importance of the use cases is discussed and recommendations for the related ongoing Work Packages and the DiSSCo services development in general are given in this report. Content keywords scientific Project reference DiSSCo Prepare (GA-871043) WP number WP1 Project output Deliverable Deliverable/milestone number D1.2 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 1.2 – Deliverable D1.2 Report on Earth sciences use cases and user stories WP Lead : Henrik Enghoff (UCPH) Task Lead : Mareike Petersen (MfN) Authors: Sabine von Mering (MfN), Mareike Petersen (MfN), Heli Fitzgerald (Luomus), Aino Juslén (Luomus), Frederik Berger (MfN), Tea von Bonsdorff-Salminen (Luomus), 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), Jiří Frank (NM), Tina Loo (Naturalis), Patricia Mergen (Meise BG), Patrick Semal (RBINS) Abstract Key words This Deliverable D1.2 from the project DiSSCo Prepare reports the results of Task 1.2 “Analyse Earth sciences use cases and user stories”. A total of 128 Earth sciences user stories and use cases was analysed with a special emphasis on the functional demands and required services for the DiSSCo Research Infrastructure. Use cases were gathered from surveys, publications and personal interviews, they were assigned to one out of seven stakeholder groups. For each use case up to five functional demand categories were assigned. Use case analyses revealed that the most important demands for Earth science collections were ‘Metadata on collection or record level’, ‘Advanced search functionality’, ‘Data integration’ and ‘Tools for reporting & statistics’. The socio-economic importance of the use cases is discussed and recommendations for the related ongoing Work Packages and the DiSSCo services development in general are given in this report. Collections, DiSSCo, Earth sciences, geosciences, geology, mineralogy, paleontology, gap analysis, 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 01 INTRODUCTION ........................................................................................................................... 4 02 APPROACH ................................................................................................................................... 4 Targeted Groups for additional surveys and interviews ................................................................. 5 Functional demands ........................................................................................................................ 5 Analysing the user stories ............................................................................................................... 6 Making the user stories available for future use............................................................................. 6 03 RESULTS ....................................................................................................................................... 7 Compilation of use cases and user stories ...................................................................................... 7 Functional demands for the user stories......................................................................................... 8 Analysing the user stories ............................................................................................................. 12 Making the user stories available for future use........................................................................... 14 04 DISCUSSION AND OUTLOOK ...................................................................................................... 16 Use cases and functional demands ............................................................................................... 16 Use cases and societal challenges in Europe 2020 strategy ......................................................... 16 05 RECOMMENDATIONS AND LINKS TO OTHER WORK PACKAGES ............................................... 18 06 REFERENCES .............................................................................................................................. 21 07 APPENDICES ............................................................................................................................... 22 Appendix 1. Table of user story compilations from previous projects and other source documents ..................................................................................................................................... 22 Appendix 2. Use cases and functional demands tables ................................................................ 22 Appendix 3. SYNTHESYS Transnational Access Analysis ................................................................ 22 Appendix 4. Target Groups for additional surveys and interviews ............................................... 22 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 Work Package 1, 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. 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...”. 5 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. 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. Some additional use cases were included from responses by scientists, colleagues and other stakeholder groups. Earth scientists (geoscientists) and broader stakeholders within the natural science collections community were contacted via mailing lists, directly (via email), targeted surveys, and interviews. In addition, a number of scientific associations/societies and interest groups were contacted. We also contacted federal or other government institutions such as geological services. Appendix 4 provides an overview of targeted groups that were contacted and asked for additional use cases. 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. 6 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. The ES demand categories that were not represented were excluded from the analysis, resulting in a matrix of 128 x 29 (rows & columns). 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). 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). 7 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. Figures 1 and 2 summarize the number of use cases collected per use case category for both Life sciences and Earth sciences. Figure 1. Number of use cases/user stories collected per category for Life sciences, total number of use cases n= 317. 14 Figure 7. Heatmap Earth Sciences user stories (n=128). Left cluster dendrogram corresponds to Fig. 6. The xaxis shows the 29 reported functional demands. Making the user stories available for future use To allow easy reuse, the user stories and use cases including the functional demands were made available in different formats. A data publication comprises the tables with the use case IDs, user group/use categories, descriptions of the use cases in the ‘epic format’, functional demand (sub- )categories plus the figures of the use case analysis (Fitzgerald et al. 2021). In addition, all use cases and user stories incl. functional demands were made available in a dedicated repository on the platform GitHub (https://github.com/DiSSCo/user-stories) as a “collection of user stories describing evolving requirements of stakeholders involved in managing and using natural science collections”. This facilitates future reuse of the whole compilation or selected use cases and allows referring to them separately or as a collection e.g. during the development of specific tools. Figure 8 shows two example use cases as presented in the GitHub repository. 15 Figure 8. Screenshot of two selected use case in GitHub repository, shows tags for functional demands / use categories etc. 16 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 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; 17 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 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. 18 Climate action, environment Well-documented natural history collections can be of great value for climate change research (Johnson et al, 2011). 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. 19 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 API would make reporting on life sciences collection access requirements more efficient, granular and 20 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 report. Especially those which require more than only one functional demand and those which can only contribute to our societal challenges with a comprehensive set of services linked to our Natural Science Collections. 21 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. Ethnobiology Ethnomedicine 5: 25. https://doi.org/10.1186/1746-4269-5-25 Borsch, T., Stevens, A.-D., Häffner, E., Güntsch, A., Berendsohn, W.G., Appelhans, M.S., Barilaro, C., Beszteri, B., Blattner, F.R., Bossdorf, O., Dalitz, H., Dressler, S., Duque-Thüs, R., Esser, H.-J., Franzke, A., Goetze, D., Grein, M., Grünert, U., Hellwig, F., Hentschel, J., Hörandl, E., Janßen, T., Jürgens, N., Kadereit, G., Karisch, T., Koch, M.A., Müller, F., Müller, J., Ober, D., Porembski, S., Poschlod, P., Printzen, C., Röser, M., Sack, P., Schlüter, P., Schmidt, M., Schnittler, M., Scholler, M., Schultz, M., Seeber, E., Simmel, J., Stiller, M., Thiv, M., Thüs, H., Tkach, N., Triebel, D., Warnke, U., Weibulat, T., Wesche, K., Yurkov, A. & Zizka, G. (2020). A complete digitization of German herbaria is possible, sensible and should be started now. Research Ideas and Outcomes 6: e50675. https://doi.org/10.3897/rio.6.e50675 Cech, E. A. & Blair-Loy, M. (2019). The changing career trajectories of new parents in STEM. Proc. Natl Acad. Sci. USA 116: 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, last accessed 2021-04-01. 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 Johnson, K.G., Brooks, S.J., Fenberg, P.B., Glover, A.G., James, K.E., Lister, A.M., Michel, E., Spencer, M., Todd, J.A., Valsami-Jones, E., Young, J.R., Stewart, J.R. (2011). Climate Change and Biosphere Response: Unlocking the Collections Vault. BioScience 61: 147–153. https://doi.org/10.1525/bio.2011.61.2.10 22 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 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: 16. https://doi.org/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 4. Target Groups for additional surveys and interviews 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 362 2 Collection manager check in which institutions certain collection categories are kept I can forward this information to a collection holder, I can forward a collection on offer to an institute that is interested details about geography and possibly wish lists for certain specimens Metadata on collection level 363 2 Collection manager connect a researcher to colleagues they can examine more collections to know which institute holds specific collections Metadata on collection level Data integration 364 2 Collection manager encourage remote curation of my collection through expert annotation I can improve the curation and value of the collection to receive and be able to easily incorporate annotated data Tools for annotation 365 2 Collection manager have the highest possible level of data security I can rest assured that nobody hacks the system, illegally modifies or extracts data strict focus on data security during the setup of DiSSCo Data security 366 2 Collection manager know which users are interested in which data I can meet the needs of as many users as possible information who the users are (e.g. citizens, scientists), where they are based (e.g. country, type of institution) and which data they are interested in (pictures, specific data categories e.g. vernacular names...) Tools for reporting & statistics 367 2 Collection manager measure the use of collections via citations I can understand the use of the collection and give evidence of its importance to track specimen identifiers and their citation Tools for reporting & statistics 368 2 Collection manager profile my collection I can show the importance of the collection to be able to highlight my institutional collection within the DiSSCo collection Metadata on collection level Tools for reporting & statistics 369 2 Collection Manager start a digitizing project I can digitize a certain group of my collection, can do this internationally because of funding to know where else there are collections of this group Metadata on collection level 370 2 Collection manager understand the needs of researchers I can make information available useful, and develop collections effectively to know what researchers need Metadata on collection level Tools for clustering requests 371 2 Collection manager, Director, Administrator know the situation with collection amounts I can plan ahead for future storage needs to know existing amounts of collections, and amount of new material coming in Tools for reporting & statistics 372 2Curator add annotated information from an Unified Curation and Annotation System (UCAS) to my collection management system (CMS) I can update infomation on my specimens in my CMS interoperability between my CMS and UCAS Interoperabili ty Tools for uploading Annotation tools 373 2Curator annotate all aspects of records, suggest improvements, and record logical connections between records I can provide duplicatefree, reliable, welldocumented data to end users an record-level annotation and communication system spanning across institutes Annotation tools Tools for data analysis 374 2Curator annotate digital specimens with updated determinations I can improve the curation of the collection to be able to annotate a digital specimen and pass that to the curating institute Annotation tools Images Interoperabili ty 375 2Curator answer multiple requests on a specified group of rocks, minerals / collector / geographic area I can follow conversation about a request communication thread by rock type etc. / collector / geographic area Advanced search functionality Tools for clustering requests 376 2Curator answer requests for specified objects I can search the collection and pull material to receive requests including all rock/mineral names involved Metadata on record level 377 2Curator attach and deliver geochemical data to rock and mineral specimen records I can retrieve specimens based on their geochemical signature a portal compatible or similar to the Earth Chem portal funded by NSF http://www.earthche m.org/ Tools for data discovery Biochemical or geochemical data Data integration Tools for uploading 378 2Curator be recognised as contributor I can apply for funding to digitise institutional collections contribution indicators (as contributor) Tools for reporting & statistics 379 2Curator check that the transcribed label data corresponds to the actual label information I can confirm collection details digital images of specimen labels Label images 380 2Curator compare an unidentified specimen with identified specimens to determine their identity I can identify the specimen digital images of specimens 2D images Annotation tools Tools for identification 381 2Curator cross-check data between specimens collected by the same collector on the same day I can confirm that all specimens have similar geographical coordinates, or correct coordinates where necessary to select all DiSSCo records by collector and date Metadata on record level Tools for georeferencing Advanced search functionality 382 2Curator curate a digital specimen (as it enters the DiSSCo data infrastructure) my collection management system (CMS) has curated specimens direct access to my digital specimens from the DiSSCo infrastructure Tools for data discovery Advanced search functionality Annotation tools 383 2Curator discover the type status of specimens I know how many type specimens are in the institutional collection digitised information on the description of species Advanced search functionality Data integration 384 2Curator enrich my collection with reliable annotation from specialists anywhere in the world I can increase the value of my collection a quality / reliability rating of annotators Annotation tools 385 2Curator images (old or modern photos or drawings of the complete specimen or of any microscopic technique applied on it) I can make the accurate identification These images are extracted from the original publications or requested from their authors and stored Tools for identification 2D images Interoperabili ty Data integration 386 2curator monitor and in specific cases restrict access to geographical coordinates of collection sites I can stop ruthless exploitation of fossils, certain minerals or sensitive sites 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 Advanced search functionality 387 2Curator publish my data online I can increase the value of the collection a user friendly collection management system (CMS) Tools for uploading Advanced search functionality 388 2Curator read untranscribed label data I can add specimen details to the record digital images of specimen labels Label images Annotation tools 389 2curator relate catalogue numbers of material in my collection to published scientific papers where they have been used I can estimate and present scientific value of my collection database with catalogue numbers of the specimens and the references of all scientific papers where they have been used Data integration Tools for reporting & statistics 390 2 Curator/collec tions manager increase the collections visibility for the general public I can motivate amateurs/citizen scientists based on the value of diversity specialized personnel to present parts of the collection in a story telling, yet scientifically sound, manner Metadata on collection level 391 2 Digitisation officer ensure digitisation serves research needs I can make effective use of resources to know what researchers require Advanced search functionality Tools for clustering requests 392 2 Digitisation officer produce digital specimens from a digitisation line I can store a specimen in my collection management system (CMS) an automated workflow minting persistent identifiers (PIDs) 2D images Label images Interoperabili ty Tools for uploading 393 2 Digitization officer link specimen & label images the corresponding occurence data I can make the images as publicly visible and usable as possible a (semi)automatic label data extraction & verification system Data integration Label images 394 2Director hire a curator with knowledge of specific groups I can be sure they have a background that includes knowledge of the main collection collection types, importance of collection gauged by size, scope, and time period of collection Metadata on collection level 395 2Director know how much my institution's collections is used and for what I can argue for the importance of my institution's collection to be able to extract information from DiSSCo based on # of views/downloads/ann otations etc. of my collection Tools for reporting & statistics Legal and policy framework Tools for downloading data/metadat a Metadata on collection level Annotation tools 396 2Historian find information on the history of objects and collections I can study the historical context of collections and objects historical data, like previous owners, links with other objects, data of arrival in collection, previous ownership etc. Metadata on collection level Metadata on record level 397 2Scientist compare an unidentified specimen with identified specimens to determine their identity I can identify the specimen digital images of specimens 2D images Annotation tools Tools for identification 398 2Scientist correct an identification and add an annotation I can file the specimen under the correct taxonomic name digital images and an annotation system Annotation tools Tools for identification 399 2Scientist cross-check data between specimens collected by the same collector on the same day I can confirm that all specimens have similar geographical coordinates, or correct coordinates where necessary to select all DiSSCo records by collector and date Advanced search functionality Metadata on record level Tools for georeferencing 400 2Scientist cross-check data between specimens of the same rock/mineral etc. I can flag outliers and correct record data where necessary to select all DiSSCo records from a certain rock/mineral etc. Advanced search functionality Annotation tools 401 2Scientist extract handwriting samples of a collector I can verify collection localities and collection dates of specimens of a collector to select all digitized labels from a specific collector Advanced search functionality Label images 402 3 Automatic identification systems developer know which collections are available to use as a reference (training data set) I can train my algorithms for automatic identification collections of target group (validated) Metadata on collection level Tools for identification 403 3IT support build and provide solutions and related services I can provide services to curators so that they 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 Tools for reporting & statistics Metadata on collection level Tools for data discovery 404 3 Software developer create new usages with the data and ways to add to the data, through apps or web interaction data is more accessible to the masses and different collections can be, for instance, cross-referenced. At the same time additional data can be added and fed back into the core databases. Geographic location will be involved as every man has GPS access today. The vantage point to access these 'big data' sources could be educational, entertaining, medical, historical and natural sciences Scope: Collection level, details: Specimen level Data integration Metadata on collection level Advanced search functionality Metadata on record level Annotation tools 405 3 Solution provider tap into the vast market of digital storage solutions for digital natural collections I can sell my services and consult predictable numbers on collection type, volume and progress in digitization Metadata on collection level Tools for reporting & statistics 406 4Association to gather information to have overall figures representative of partners' state-of-the-art we can showcase the relevance of the collections to policy makers and attract funds high-level figures that feature the collections as a whole Metadata on collection level Legal and policy framework Tools for reporting & statistics 407 4 Collection manager, Director, Administrator know what the situation is regarding collection size I can plan for new space/ storage needs I need to know existing size of collections, and amount of new material coming in. Also, I need to know the status/ condition (e.g. wet, dry) of existing material and collection health information Tools for reporting & statistics Metadata on collection level 408 4Director know the extent of the use of the organisation's collections across societal sectors I can take informed executive decisions related to future investments (both collections and HRs) metrics of the use of collections Tools for reporting & statistics Metadata on collection level Legal and policy framework 409 4Director to be able to underline the importance of Earth sciences and of scientific collections in understanding it I can help policy makers understand the consequences of their policies details of collections and related research Tools for reporting & statistics Metadata on collection level Legal and policy framework 410 4Director understand the relationship of our own collection to the collections of other institutions in our country I 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 Metadata on collection level 411 4 Director / administrator know what makes our collection unique I can effectively advertise/highlight the collections to improve usage Collection types, with size, locality scope, time, taxonomic scope, important collectors Metadata on collection level Tools for reporting & statistics Advanced search functionality Metadata on record level Data integration 412 4Policy maker find and reuse digital specimens from DiSSCo I can confirm the presence of a rock/mineral etc. for legal purposes fast access to the DiSSCo infrastructure Advanced search funcionality Legal and policy framework 413 4Policy maker find information on the contribution of DiSSCo to the international environmental policy agenda I can justify national level investments in its operation evidence that DiSSCo's activities align with (e.g.) Sustainable Development Goals Legal and policy framework Tools for reporting & statistics Data integration 414 4Policy maker know how well sampled my country is I can fund future biodiversity exploration and research an extractable list of specimens to understand which parts of my country are poorly known on an easy to see map Metadata on collection level Tools for reporting & statistics 415 4Policy maker know the use of the collections by other domains as a key indicator of its impact I 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 Tools for reporting & statistics Legal and policy framework 416 4Policy maker understand the value of DiSSCo I can justify the national level investments in its operations access to impact stories and/or assessments Tools for reporting & statistics Metadata on collection level 417 5 Curious person learn about the rocks/minerals/fossils that might be in my environment I can improve my knowledge on geology / mineralogy / palaeontology scientific names, common names, geographic coordinates, characteristics, images Metadata on record level Data integration 418 5 Exhibitions maker be able to find the location of specimens and information about species I 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 Metadata on record level 419 5 Science communicatio n officer know about the research being carried out in natural history collections I can organize a dissemination event information on research topics and the people behind them Data integration 420 5Student be able to identify the species in scientific field trips, without visiting the relative collections of NHMs I 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.) Tools for identification Advanced search functionality 2D images Morphologica l data Distribution data 421 5Student check my identification of a geological/palaeontoogical specimen I can test my knowledge about rocks/minerals/fossils and and learn more about a group I am studying image/characteristics, links to papers, collection metadata Tools for identification Images Metadata on collection level Data integration 422 5Student find a high resolution image I can perform morphological analysis as part of my coursework a reference to the higher resolution image and the clear procedure to retrieve it Tools for identification 2D image 3D image Tools for downloading data/metadat a 423 5Student find the referencing information for an image I can cite the source in a written report which includes the image a reference to the citation information for the image Metadata on record level Data integration 424 5Teacher be able to provide accurate scientific information about rocks/minerals and specimens I can educate students/the public about the natural world easily accessible and up-to-date information about the specimens in museum collections Metadata on record level Advanced search functionality 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.” Appendix 4. Target Groups for additional surveys and interviews. Given is the target group or contact point and a use case category where surveys contributed to or might contribute in future. Target Group / Contact Point Use Case Category Geo.X (Research Network for Geosciences) TDWG Palaeo & Earth Science Interest Group several PR team from DPP Partner Institutions 7. External Mediasphere for Nature Network with a focus on particular partners 6. Industry Educational sector from DPP Partner Institutions 5. Education Partners from Synthesys+ NA5 Survey (Engaging with the private sector: Experience of institutes) 6. Industry Geological Service / geological state agency 4. Policy ‘Umbrella Organization for Geosciences’ (Dachverband der Geowissenschaften , https://www.dvgeo.org/ several Federal Institute for Geosciences and Natural Resources (via personal contact) 1. Research 5. Education 1. Research 5. Education Different Industries / Companies (via personal contact) Film Academy 5. Education (e.g. Konrad Wolf University Babelsberg) 7. External 5. Education 7. External Lyme Regis Fossil Festival 5. Education CETAF Earth Sciences group experts 1. Research Broadcasting Company Geoand Paleo colleagues from DPP Partner Institutions 1. Research 6. Industry 4. Policy The German Mineralogical Society (via personal contact) The German Paleontological Society (via personal contact) 6. Industry