Deliverable: 7.5 Title: First update Data Management Plan

D7.5 1st update DMP I page 1 of 28 Deliverable: 7.5 Title: First update Data Management Plan Project information Project Title Networking for excellence in the development of innovative, consumer-oriented horticultural food products using the Living Lab approach Acronym: HortiFoodTrends Grant agreement: 101159293 Topic HORIZON-WIDERA-2023-ACCESS-02-01 - Twinning Bottom-Up Type of action Horizon - Coordination and Support Action Granting authority European Research Executive Agency Start date of the project 1 June 2024 Duration 36 months Project Coordinator Monika Mieszczakowska-Frąc Project Website www.hortifoodtrends.eu D7.5 1st update DMP I page 2 of 28 Deliverable information Deliverable title Data Management Plan Deliverable number 7.5 Deliverable version 1.0 Work Package WP7, Project Management Contractual date of delivery M17 – 31/10/2025 Actual date of delivery M17– 30/10/2025 Deliverable type: R – Document, report Responsible Partner InHort Authoring & Approval Authors Katarzyna Hołownicka, Jan Zdulski Reviewers Adam Kaźmierczak, Monika Mieszczakowska-Frąc, Michael Bom Frøst Approved for submission Monika Mieszczakowska-Frąc Dissemination level PU Public, fully open, e.g. web (Deliverables flagged as public will be automatically published in CORDIS project’s page) X SEN Sensitive, limited under the conditions of the Grant Agreement Classified R-UE/EU-R EU RESTRICTED under the Commission Decision No2015/444 Classified C-UE/EU-C EU CONFIDENTIAL under the Commission Decision No2015/444 Classified S-UE/EU-S UE/EU-S – EU SECRET under the Commission Decision No2015/444 Document History Version Date Description of Change V0.1 13/10/2025 First draft V0.2 15/10/2025 Second draft version incorporating review comments V0.3 29/10/2025 Final draft send to Coo V1.0 30/10/2025 Final version submitted to EC by the Coo Disclaimer This project has received funding from the European Union’s Horizon Europe Innovation programme under grant agreement No 101159293. Disclaimer: This report only reflects the views of the author(s) and do not necessarily reflect the official opinion of the European Union. The European Commission is not liable for any use that may be made of the information contained therein. Configuration Management: Document Location The latest version of this controlled document is stored in D7.5 First update Data Management Plan. D7.5 1st update DMP I page 3 of 28 TABLE OF CONTENTS EXECUTIVE SUMMARY ........................................................................................................... 4 TABLE OF ABBREVIATIONS AND ACRONYMS .......................................................................... 5 1 INTRODUCTION ............................................................................................................. 6 1.1 Changes provided to the DMP Plan after 17 months of the project implementation ............ 6 2 DATA SUMMARY ........................................................................................................... 7 3.1 Purpose of the data collection ................................................................................................ 7 2.1 Data types, formats and size ................................................................................................... 7 2.1.1 Data categories ............................................................................................... 8 3.2 Re-use of data .......................................................................................................................... 9 3.3 Origin/provenance of the data .............................................................................................. 10 3.4 Data utility ............................................................................................................................. 10 3 FAIR DATA .................................................................................................................. 14 3.1 Making data findable, including provisions for metadata ..................................................... 14 3.1.1 Globally unique persistent identifier ..................................................................... 14 3.1.2 Rich Metadata ........................................................................................................ 14 3.1.3 File naming ............................................................................................................. 15 3.2 Making data openly accessible .............................................................................................. 16 3.2.1 Repository: ............................................................................................................. 16 3.2.2 Data: ....................................................................................................................... 16 3.2.3 Metadata:............................................................................................................... 18 3.2.4 Open Access to Scientific Publications ................................................................... 19 3.3 Making data interoperable .................................................................................................... 19 3.4 Increase data re-use .............................................................................................................. 20 4 OTHER RESEARCH OUTPUTS ........................................................................................ 21 5 ALLOCATION OF RESOURCES ....................................................................................... 21 6 DATA SECURITY ........................................................................................................... 22 7 ETHICS ........................................................................................................................ 24 7.1 Ethical Procedures ................................................................................................................. 25 7.1.1 Recruitment Processes and Criteria ....................................................................... 25 7.1.2 Informed Consent Procedures ............................................................................... 25 8 DESCRIPTION OF THE TECHNICAL AND ORGANISATIONAL MEASURES THAT WILL BE IMPLEMENTED TO SAFEGUARD THE RIGHTS AND FREEDOMS OF PARTICIPANTS ........... 26 8.1 Data collection and storage ................................................................................................... 27 8.2 Using and sharing data .......................................................................................................... 27 9 CONCLUSIONS ............................................................................................................. 28 D7.5 1st update DMP I page 4 of 28 EXECUTIVE SUMMARY This deliverable, D7.5, is the second version of the HortiFoodTrends Data Management Plan (DMP) and replaces the first version. It is based on the Guidelines on the HORIZON EUROPE Data Management Plan Template Version 1.0 1 . The DMP specifies how data collected or generated in the course of the project will be handled during the HortiFoodTrends action and how it will be stored, published, cited and made Findable, Accessible, Interoperable, and Reusable (FAIR) beyond the project life. Moreover, the DMP details the standards and methodologies for data collection and generation that will be followed, how the research data will be preserved, and which datasets will be published for verification or reuse as open access. DMP is a “living document” that will be updated periodically as project activities progress. The DMP will establish consistent practices among partners to enhance the efficiency and robustness of data handling during project delivery. 1 https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/temp-form/report/data-management-plan_he_en.docx D7.5 1st update DMP I page 5 of 28 TABLE OF ABBREVIATIONS AND ACRONYMS Abbreviation Meaning CA Consortium Agreement CC Creative Commons Coo Project Coordinator DMP Data Management Plan DOI Digital Object Identifier GDPR General Data Protection Regulation ISO International Organization for Standardization FAIR Findable, Accessible, Interoperable and Reusable PID Persistent Identifiers WP Work Package D7.5 1st update DMP I page 6 of 28 1 INTRODUCTION The Horizon Europe Model Grant Agreement requires the establishment and regular updating of a data management plan (DMP). This DMP is based on the Data Management Template of the European Commission Horizon Europe, addressing the requirements for research data management of Horizon Europe as described in Article 17 of the Grant Agreement. It complies with the General Data Protection Regulation (GDPR), the FAIR principles, and the motto to share data ‘as open as possible, as closed as necessary’. The purpose of this DMP is to set general data management practices within the HortiFoodTrends project, specifically: • to provide relevant information on the nature of data to be collected and/or generated (purpose, type, format, expected volume, and origin); • to describe the management procedures to collect and/or generate data in HortiFoodTrends during and after the end of the project, serving as the key element of good data management; • To define how the collected and/or generated data will be made ‘FAIR’ (Findable, Accessible, Interoperable and Reusable. The deliverable is structured in 8 Chapters, as follows: • Chapter 1 introduces the objectives and structure of the DMP. • Chapter 2 describes the nature of the data (purpose, format, origin, expected size). • Chapter 3 explains how FAIR principles will be followed. • Chapter 4 presents other research outputs generated within the work plan of the project. • Chapter 5 defines the allocation of resources for the data management activities. • Chapter 6 refers to data security. • Chapter 7 discusses the relationship between data management and potential ethical considerations. • Chapter 8 provides a summary of the report. The DMP will be updated at the end of the project (M36). The DMP has been compiled collectively in response to consultation and iterative dialogue with the project partners regarding all project activities and outputs. Each partner on the specific project is responsible for implementing the project DMP steps and ensuring their data is managed in accordance with the project-level DMP. 1.1 Changes provided to the DMP Plan after 17 months of the project implementation • New position in Table 2: Table Data Overview; • Minor changes in repository description (3.2.1); • Detailed procedures that will guide the project in maintaining the highest ethical standards (7Ethics). D7.5 1st update DMP I page 7 of 28 2 DATA SUMMARY The Data Summary section deals with the purpose of the data to be collected and generated by the project HortiFoodTrends and its relationship with the project objectives, the types and formats of data that will be generated, the re-utilisation of existing data and how it will be implemented, the origin of the data, and to whom it may be useful (data utility). 3.1 Purpose of the data collection The purpose of data collection is closely linked to the objectives and planned outputs of the HortiFoodTrends project. The general purpose of collecting data is to develop and optimise products made from berries, fruits, and vegetables, with consumer input throughout the process. New data on end users' expectations, in the form of survey questionnaires containing indicator and descriptive data, will be developed in WP4 (Task 4.1). These data will be exploited in Task 4.2 to create innovative products based on berries, fruits and vegetables. The developed products will generate new data from the chemical and sensory analyses performed. Quantitative and qualitative characteristics of nutrients (including protein, fats, sugars, fibre, minerals) and bioactive components (vitamins, phenolic compounds including anthocyanins and other antioxidants) and sensory quality indicators. WP4 will also produce data correlated with processing (process parameters, technological methods, critical control points, etc. Qualitative data will influence the selection of products for consumer evaluation in 3 countries: Denmark, France and Poland. Consumer research data will be key to developing communication procedures with the industry and determining commercialisation and economic value. The purpose of collecting consumer data is to understand their preferences and differences across consumer segments (e.g., gender, age, country, and/or region). WP5 will upscale WP4 results, defining the future of the implemented innovations. Financial and economic incentives will be analysed as part of the value proposition. WP5 develops a strategy based on the Living Lab approach and, in particular, a roadmap for effective communication with end users. In WP6, we will collect contact data from stakeholders to develop a network of producers and other relevant stakeholders. Also in WP6, we collect data from end-users in focus groups with consumers (reaching the target of 40% of women) to explore their level of acceptance of the new products. Lastly, expert interviews will be conducted to inform decisions on the human, social, and material aspects of responsible innovation. Videos and pictures (in the sense of non-research data) are generated and used to communicate and disseminate the project and its results via the project’s media channels and to illustrate methods for internal protocols. Personal data are not collected for research purposes, but are needed to contact persons (e.g., researchers, members of the Multi-actor forum) and to ask specific questions in questionnaires. Personal data will be used in accordance with the GDPR and only with the consent of the persons concerned. In short, persons are informed about the use of their data and have the right to see what has been collected and stored regarding their personal data. They can request deletion, and this request will be followed up on. Information about this is included in section 6. 2.1 Data types, formats and size The HortiFoodTrends project follows a multi-actor approach by co-creating activities that are deeply interconnected with businesses' and end-users’ needs. Thus, HortiFoodTrends will generate data of different types, including measurements summarising the results of sensory and consumer tests and food D7.5 1st update DMP I page 8 of 28 processing experiments (WP4), as well as questionnaires from consumer research and laboratory and process analysis measurements (WP4). Data regarding stakeholder evaluation of innovation implementation will be collected from stakeholders (WP5, WP6). End-user product expectations from focus groups (WP6). 2.1.1 Data categories Datasets that will be collected/generated during the HortiFoodTrends project are categorised into four main categories: Confidential Dataset: contains sensitive data that cannot be shared. Access to this data is restricted to authorised personnel only, and it is kept securely to ensure confidentiality. Please refer to sections 5 and 6 for more information on how GDPR and Ethics guidelines are applied in the project, as well as an initial Consent Form procedure. Core Dataset: includes the project’s deliverables, dissemination materials, and essential training materials. These datasets are mandatory for running and reporting on the project as they are the backbone of its activities and outcomes. Stakeholder Dataset: includes data collected from SMEs and other related stakeholders (such as national and international bodies/ institutions/organisations related to HortiFoodTrends) in the food sector through various means such as surveys, interviews, visits, online and onsite meetings and questionnaires. Apart from those, all the data received from third parties will be considered SD. The data in this category is essential for identifying the challenges and developing practical solutions. Produced and Collected Dataset: includes the academic publications and lab results that are generated by the HortiFoodTrends staff. The data in this category is crucial for demonstrating the project’s research capacity and potential impact on the food industry. A schematic table questionnaire was submitted to the partners to ask what kind of data would be produced. The complete list of data types is reported in Table 2: Table Data Overview. Data types and formats are included in Table 2 (columns 4 and 8). These formats are compatible with many computer programs and should be used by all partners. Other data formats may be used by individual partners, but must be converted to the standard formats before uploading to allow proper data exchange. Table 1: The recommended and acceptable formats for various types of data Type of data Recommended formats Acceptable formats Tabular data with extensive metadata variable labels, code labels, and defined missing values • SPSS portable format (.por) • delimited text and command ('setup') file (SPSS, Stata, SAS, etc.) • structured text or mark-up file of metadata information, e.g. DDI XML file • proprietary formats of statistical packages: SPSS (.sav), Stata (.dta), MS Access (.mdb/.accdb) Tabular data with minimal metadata column headings, variable names • comma-separated values (.csv) • tab-delimited file (.tab) • delimited text with SQL data definition statements • delimited text (.txt) with characters not present in data used as delimiters • widely-used formats: MS Excel (.xls/.xlsx), MS Access (.mdb/.accdb), dBase (.dbf), OpenDocument Spreadsheet (.ods) D7.5 1st update DMP I page 9 of 28 Textual data • Rich Text Format (.rtf) • plain text, ASCII (.txt) • eXtensible Mark-up Language (.xml) text according to an appropriate Document Type Definition (DTD) or schema • Hypertext Mark-up Language (.html) • widely-used formats: MS Word (.doc/.docx) • some software-specific formats: NUD*IST, NVivo and ATLAS.ti Image data • TIFF 6.0 uncompressed (.tif) • JPEG (.jpeg, .jpg, .jp2) if original created in this format • GIF (.gif) • TIFF other versions (.tif, .tiff) • RAW image format (.raw) • Photoshop files (.psd) • BMP (.bmp) • PNG (.png) • Adobe Portable Document Format (PDF/A, PDF) (.pdf) Audio data • Free Lossless Audio Codec (FLAC) (.flac) • MPEG-1 Audio Layer 3 (.mp3) if initially created in this format • Audio Interchange File Format (.aif) • Waveform Audio Format (.wav) Video data • MPEG-4 (.mp4) • OGG video (.ogv, .ogg) • motion JPEG 2000 (.mj2) • AVCHD video (.avchd) Documentation and scripts • Rich Text Format (.rtf) • PDF/UA, PDF/A or PDF (.pdf) • XHTML or HTML (.xhtml, .htm) • OpenDocument Text (.odt) • plain text (.txt) • widely-used formats: MS Word (.doc/.docx), MS Excel (.xls/.xlsx) • XML marked-up text (.xml) according to an appropriate DTD or schema, e.g. XHMTL 1.0 Source: https://www.openaire.eu/data-formats-for-preservation/ Data sizes are included in Table 2 (column 9). However, it is not possible to estimate the size of some of the items included. The information will be completed as the project progresses. Many datasets will be produced, but none will be overly large, allowing them to be collected in spreadsheets for easy accessibility. Just raw data derived from consumer analyses of prototype berry products conducted in 3 countries will require significant storage space for statistics and informatics. 3.2 Re-use of data Data will also be derived from the collection of existing databases (e.g. from the USDA database, EFSA Food consumption data, EFSA Database of health claims), outcomes from previous and ongoing European and national projects (e.g., OPTIFEL, ISAFRUIT, etc.), literature review (sources: Zenodo, PubMed, SCOPUS, Web of Science, ScienceDirect, etc.), as well as reports and technical documents. They will be reused to: • develop and implement innovative products and technologies that reduce production costs and improve product quality, thus maintaining the high competitiveness of Polish producers (WP4). • increasing awareness of the general public about the importance of healthy eating, which is facilitated by increased consumption of fruit and vegetables, especially super fruits, regarding improving the health of citizens and reducing the problem of obesity (WP4, WP5, WP6); and • horizontal mapping review of existing European, national and regional policy incentives and nudges contributing to supporting and promoting good practice (WP5). D7.1 DMP I page 16 of 28 [Free] Free text field for internal communication purposes, at the end of the file name, immediately before the extension (e.g., initials of reviewer). This field should not be included in the name of published files. [Extension] File extension These minimum metadata schemas can be extended with arbitrary terms from a taxonomy or controlled vocabulary, as described in the Zenodo API documentation. 3.2 Making data openly accessible 3.2.1 Repository: All datasets supporting publications will be made publicly available in the Zenodo repository upon publication of the manuscripts. For this, the Community “HortiFoodTrends” has been created. Zenodo is always available, and no special arrangements are required. Zenodo assigns a DOI (when the resource does not have a DOI) for every published record in the repository. Only data gathered by partners outside the project work plan and protected by IPR, or inside the work plan but containing confidential information (e.g., related to personal interviews or stakeholders’ contact information), will be kept confidential for privacy reasons. The data will be made available to work package members on an ongoing basis as it is generated, using SharePoint. Furthermore, when a dataset becomes openly accessible, it will be announced on the HortiFoodTrends project website, where a link to the dataset on Zenodo will be available. 3.2.2 Data: The HortiFoodTrends dataset will be both public (data access policy unrestricted) and accessible via: • Project website • Partners database (personal computer, or on an institutional secure server of the data owners) • HortiFoodTrends Community Zenodo • Open access journals • Other platform if needed All data deposited on Zenodo will be accessible to the public without restriction. For other data, potential users must contact the Coordinator or the data owner to gain access. If necessary, an appropriate procedure (such as a non-disclosure agreement) will be used, including the conditions of use, access criteria, and acknowledgements, to ensure proper data sharing. D7.1 DMP I page 17 of 28 In general, until the dataset is fully finalised and ready for publication, the project's default repository— the FIZZ programme database, nextCloud.groupe-esa.com, and the SharePoint platform—will be used to exchange data between project partners. Accessibility status will be specified in the Data Register, including any reason why a specific dataset is not being made available to download, e.g., ethical, containing personal data, intellectual property protection, commercially sensitive information, privacy-related, and/or security-related. Also, transparent access and use conditions will be made available. Private, sensitive data will be restricted and partially available after applying aggregation and anonymisation procedures. The project will ensure respondents' anonymity through an informed consent form, as described in the Ethics and Gender Guidelines (D7.4). If anonymised interview data were to be made publicly available, each respondent would have to sign a second informed consent form for this step. Key information will be collected in the Data Register for each dataset by the lead beneficiary responsible for the dataset, using the template provided in Table 3. Table 3: Data Register TOPIC DESCRIPTION Dataset identifier HFT_[ShortTitle]_ v[Version]_[Type] Dataset name Dataset description Dataset DOI Dataset version history Key contact (Partner) Dataset file format and size Associated WPs/Tasks/ Deliverables/ Milestone Accessibility [Not yet considered – with who is responsible for the decision[ [Open – with reasoning, date of decision and who is responsible for the decision] [No Open – with reasoning, date of decision and who is responsible for the decision] Repository(-ies) Keywords Licence [Default: CC BY-4.0] Useful for whom? Key data sources The HortiFoodTrends consortium will make every effort, where possible, to make research data available as open data or via open services. However, it is essential to note that, due to the low maturity of this document and some existing uncertainties about the data collected in the project. As the project progresses, further information on making data openly accessible will be provided in subsequent versions of the DMP. In particular, information on the methods or software tools needed to access the data and how access will be provided in the event of restrictions. The data will be available as soon as the publishable version is available. Nevertheless, this aspect should be assessed using datasets generated during project implementation. D7.1 DMP I page 18 of 28 The HortiFoodTrends Consortium Agreement states that prior notice of any planned publication shall be given to the consortium parties at least 30 calendar days before the submission for publication. This time is allocated to assess whether the protection of the objecting party's results or background would be adversely affected, or the objecting party's legitimate interests in relation to its results or background would be significantly harmed, or the proposed publication includes confidential information of the objecting party. A publication delay of maximally 90 days can be requested in case of an objection. All HortiFoodTrends data used and/or generated will be accessed using open (no barriers), free (no costs), and standardised communication protocols (TCP/IP, HTTP) for individuals and machines. Using standardised communication protocols contributes to better accessibility of the data (with authorisation and authentication procedures when necessary). During project completion, different levels of access will be defined based on accessibility levels (user profiles) to ensure the ability to work on data and open access to aggregated data, with relevant permissions. At the end of the project, all data (with the authorisation from project partners) is publicly shared. For restricted-access data, a well-documented authorisation procedure must be established to grant access to the data (define who grants access). Upon authorisation, the second step is authentication, which provides secure access (e.g., registration via username & password). The procedure will be valid during and after the project. Ascertaining the identity of the person accessing the data is related to the access protocol. There is a comprehensive plan to address data security concerns at both the database and platform levels. In summary, users will be categorised as 'internal' or 'external.' External users, typical platform visitors, will have limited data access. Internal users, integral to our project, will be assigned a unique project partner ID, granting them broader data access based on our three-tiered data protection strategy. There is a data protection protocol in place (included as Annex). Small excerpt: Data protection comprises three layers that vary depending on user type. These layers include: • Public (Option 1): The data is publicly available. This option applies to most HortiFoodTrends (final) products. • Private - Confidential to partner (Option 2): This option applies when data are shared only between specific partners in the consortium (e.g., data involved in collaborative work, sharing of intermediate or incomplete products, data expected to be included in patent applications). • Private - Confidential to consortium (Option 3): This option applies to data underlying publications that may not yet be published in peer-reviewed scientific papers or that are planned to be published before becoming publicly available. For the moment, there is no need for a data access committee, as the project database contains no personal or sensitive data. In some work packages, partners generate sensitive data, which is anonymised before being shared with the project database. 3.2.3 Metadata: The metadata of deposited publications will be licenced under Creative Commons Public Domain Dedication (CC0) or equivalent (to the extent legitimate interests or constraints are safeguarded), in line with the FAIR principles (in particular machine-actionable) and provide information at least about the following: • datasets (description, date of deposit, author(s), venue and embargo), D7.1 DMP I page 19 of 28 • Horizon Europe funding, • grant project name, acronym and number, • licensing terms, • persistent identifiers for the dataset, • the authors involved in the action and, • if possible, for their organisations and the grant. Where applicable, the metadata will include persistent identifiers for any research outputs or other tools and instruments needed to validate the publication's conclusions. The metadata will be collected and stored in the database (and data platform) to enable the data to be searchable. There may be restrictions on licensed secondary data and private company data. The availability of the data and metadata is ensured through the HortiFoodTrends project website (which remains reusable for as long as the project's resources and infrastructure allow) in the Zenodo open repository. However, the availability of data and metadata needs to be further assessed as the project progresses. The metadata will include the reference to the software needed to access and read the data. 3.2.4 Open Access to Scientific Publications Open science HortiFoodTrends practices will include sharing research data and publishing under Gold Open Access (OA), with complete PDFs freely available on the HortiFoodTrends Community of the OpenAire repository Zenodo, on the project website, and on social media, to reach a broader target audience, including citizens. The HortiFoodTrends partners must ensure open access to peer-reviewed scientific publications relating to their results. In particular, they must ensure that: • at the latest at the time of publication, a machine-readable electronic copy of the published version or the final peer-reviewed manuscript accepted for publication is deposited in Zenodo • immediate open access is provided to the deposited publication via the repository, under the latest available version of the Creative Commons Attribution International Public Licence (CC BY) or a licence with equivalent rights; for monographs and other long-text formats, the licence may exclude commercial uses and derivative works (e.g. CC BY-NC, CC BY-ND) and • information is given via the repository about any research output or any other tools and instruments needed to validate the conclusions of the scientific publication. Beneficiaries (or authors) must retain sufficient intellectual property rights to comply with the open access requirements. Only publication fees in full open-access venues for peer-reviewed scientific publications are eligible for reimbursement. 3.3 Making data interoperable The depositors will strive to use metadata commonly and internationally used in their field of research, since no widely accepted, specific metadata vocabularies exist. Data variable names and units will be consistent with those commonly accepted by the international scientific community and the International System of Units. The vast majority of the datasets will be made available as spreadsheets, .xlsx format, and to a lesser extent as R files, FIZZ files, geotiff files, and .img, .asc extensions, so that potential users can fully use them. D7.1 DMP I page 20 of 28 In addition, the Data Management Team will ensure that data held on the HortiFoodTrends data repository is provided in commonly used data formats and file types (Tables 1 and 2). These formats have been used because they are widely accepted standards, and because the software needed to handle them is widely available. The files will be converted to open file formats where possible for long-term storage. Maximum effort will be taken to use the available standard vocabularies for all data types present to maintain interdisciplinary interoperability. However, when suitable standard vocabularies are not available, suitable controlled vocabularies will be created. Connections to already existing ontologies and public databases will be assured. A qualified reference is a cross-reference that explains its intent. For example, X is a regulator of Y is a much more qualified reference than X is associated with Y, or X sees also Y. The goal, therefore, is to create as many meaningful links as possible between (meta)data resources to enrich the contextual knowledge about the data (Source: https://www.go-fair.org/fair-principles/i3-metadata-include-qualified-referencesmetadata/). This will be assessed at a later stage of the project. 3.4 Increase data re-use Partners are encouraged to publish research data as supporting material with their publications to facilitate data archiving for future re-use by other projects or research initiatives. New data will be announced on the HortiFoodTrends website and across the different profiles on social media, with links to the dataset page on Zenodo. Internally, all partners will be informed by email about the availability of new datasets, including the link to Zenodo. The metadata will be richly described, containing, at minimum, the mandatory terms of DataCite (but strongly recommended to include other recommended terms) and Zenodo enrichments. The project intends to make as much data as possible reusable for third parties. The restriction will apply only when privacy, IPR, or other exploitation grounds are in play. Where this is the case, agreements will be made based on the individual data sets. Requests to use the data by external parties will be approved by the project consortium. When possible, the dataset will be licensed under an Open-Access license. Specifically, the project will use the CC-BY 4.0 free cultural works license. The license applicable to each dataset will be decided on an individual basis, though the recommendation will be either CC-BY or CC-BY-SA. The data produced in the HortiFoodTrends project will be usable under the selected license (CC0, CC-BY, CC BYNC, CC BY-ND) and uploaded to the open repository Zenodo (ensuring their availability after the project). The dataset published on Zenodo will be retained for the lifetime of the repository, which is currently indicated as indefinitely. Uploaded data files and metadata are backed up on a 12-hourly basis, as well as replicated in multiple copies in the online system. Where relevant, the dataset will be made available through the HortiFoodTrends website, which will remain online at least 5 years after the end of the project. The metadata includes information about the study —such as its purpose, methods, results, and conclusions; the title and abstract of the research; authors and contributors; keywords; research design; results (findings, statistical analysis, trends, patterns); conclusions; funding sources; data availability; and access. In addition to these metadata types, it will include the software or tools used, relevant citations, and details about data processing and analysis. It will be based on FAIR metadata standards. Data quality checks are the responsibility of the partners who generate the dataset. A peer-review process at publication will support them, conducted in accordance with the procedure set out in point 4.3 of D7.1 (Project Management Guidelines). D7.1 DMP I page 21 of 28 Data quality in the HortiFoodTrends project will be ensured throughout the lifecycle of the data, including (where applicable): • Accuracy; • Relevance, data meeting the requirements for its intended use; • Completeness, no missing values or records; • Timeless, updated data; • Consistency, data format, and cross-referenceable. The data quality assurance includes three moments: • Before data collection takes place – in this stage, the researcher must ensure the data collection process is correct, well understood and appropriate collection methods are adopted. • During the data collection process, the researcher must make sure that the process goes smoothly, have a shared understanding and make sure no fake information is provided. • After data collection, in this stage, data cleaning (removing null values, special characters, replacing abbreviations with whole words or using the same word, formatting) and storage (the original data). 4 OTHER RESEARCH OUTPUTS This section of the plan will be further developed as the project progresses, with due consideration given to the type of output generated, always in line with FAIR principles. 5 ALLOCATION OF RESOURCES Public project deliverables and datasets will be published on the Zenodo repository. These activities will be free of charge. The HortiFoodTrends website can host deliverables and datasets, or links to them. The HortiFoodTrends website has been in operation for 3 years, and InHort covered the website's costs. Before the end of the project, the web page will be extended for the forthcoming years. InHort will cover the cost arising from the extension of the period. Partners will use their own budgets to archive personal data in their own repositories, It should be noted that the cost of making the data FAIR includes the fees for publishing scientific articles containing the project data in open-access journals and for operating the project website. The Grant Agreement (Annex 5, page 166) states that "only publication fees in full open access venues for peerreviewed scientific publications are eligible for reimbursement." It is also highlighted to partners that the EC offers a no-cost, open-access service after open-science peer review. Publications can be submitted for no cost here: https://open-research-europe.ec.europa.eu/. Fees for the open-access publication of the data will be the responsibility of the data partner, in accordance with the Grant Agreement. The HortiFoodTrends project has a data management team to ensure project data is shared and stored effectively. It consists of at least 1 member selected by each partner (see Table 4). The project coordinator has the ultimate responsibility for the data management in the project. Data file quality will be checked by the Management Team, who will also be responsible for submitting them to the repositories. Each Work Package Leader is responsible for the datasets used for research within the project. This responsibility can be delegated to the Task leader or researcher accountable for data collection. Table 4: The data management team members Partner Data Management Team InHort Jan Zdulski D7.1 DMP I page 22 of 28 UCPH Michael Bom Frøst ESA GROUPE Ronan Symoneaux LYFE Agnès Giboreau Long-term preservation of the data will be ensured through the following: • in the open-source repository Zenodo indefinitely (no costs added, all research data under open– access); • in all partners' archives for at least 5 years after project completion (all research and non-research data and documents produced in the framework of the HortiFoodTrends project, costs incurred by the partner organisations); • in the project website for the duration of the project (all research and non-research data and documents produced in the framework of the HortiFoodTrends project, based on the level of sensitivity/publicness). 6 DATA SECURITY Data protection is an essential topic for the HortiFoodTrends project consortium. Each partner is individually responsible for data security. Encryption and backup are recommended to maintain data consistency throughout the project's lifetime and beyond. If the file gets lost and/or corrupted, it will be replaced with the correct one. Data, metadata, and documents will be shared among HortiFoodTrends project partners via Teams and SharePoint Online libraries on the O365 platform. Microsoft provides data protection services to prevent data loss within the InHort institutional account. For any dataset produced, the responsible partner will provide for the measures to be adopted to ensure data security, privacy and ethical considerations. Table 5: Information about storage procedures at the individual partners Partner Procedure InHort relies on a SharePoint drive with an account-based permission system that restricts access to only consortium members who need it. InHort also stores data on its intranet, which provides access controls and automated data backups. UCPH All research data will be collected using digital methods that are safe and compliant with the EU GDPR. The only person with access to the collected data is the data collector, Michael Bom Frøst. After collecting data, it is transferred to a password-protected UCPH-Security drive. Following pseudonymization, all data will be stored on a personal PC with a password set and kept safely so that no one other than the user can access it. All collected research data will be shared in accordance with HortiFoodTrends guidelines after publication. ESA GROUPE All files are stored and managed on an internal server, "nextCloud.groupe-esa.com," based on the Nextcloud solution. An annual backup copy is made on an external hard drive dedicated to research project backups and stored in the laboratory's safe, accessible by code. Video files are stored on the Noldus server and on an external hard drive kept at ESA due to their large size. D7.1 DMP I page 23 of 28 Personal data is collected for consumer tests and trained panels in accordance with ESA's personal data policy and the GDPR. Participants provide informed consent in writing when they register to take part in the test. Only the personal data necessary for the project will be collected and stored on the servers of ESA, with secure access to the data protected by a username and password. Files containing participants' contact information (name, first name, email, phone) will be collected in a recruitment file. This file will be kept separate from the test result data and will not be shared among project partners or externally. Participants will be identified by an alphanumeric code in the project data file, ensuring their data remains anonymous. Video data is stored on hard drives kept in secure facilities, accessible only by authorised personnel at ESA. LYFE All files are backed up daily and stored on the Institut LYFE's local server. An annual backup copy is made on an external hard drive dedicated to research project backups. Personal data is collected for consumer tests and trained panels in accordance with LYFE's personal data policy and in compliance with the GDPR. Informed consent is provided in writing by participants when they register to take part in an audiovisual recorded test. Only the personal data necessary for the project will be collected, if needed and stored after pseudonymization on the LYFE server with secure access to the data protected by a username and password. Raw data will be curated with appropriate metadata, statistically/bioinformatically analysed, maintained by relevant project partners in appropriate media (in-house servers or cloud-based), and regularly backed up and recovered. Data, metadata, and document sharing between HortiFoodTrends project partners & third parties will be handled through non-disclosure agreements (NDAs) & material transfer agreements (MTAs) to address confidentiality issues during exchanges. All personal data obtained in the project will be held strictly confidential and will not be shared with or disclosed to third parties external to the consortium without the knowledge and permission of any concerned data subjects, unless the consortium is legally required to do so. (E.g. by the European Commission or for law enforcement purposes). Personal data will be stored on secure servers and will be accessed only by authorised and assigned members of the project. Each partner is responsible for implementing and executing safe practices for sensitive data. The HortiFoodTrends project recommends the following restrictions to the storage and transfer of sensitive data: • For information in digital format: o Must be stored only on hard drives with encryption, such as BitLocker. o Transfer of sensitive data to occur only via Microsoft SharePoint, by encrypted email, or an equivalently safe transfer method. • For information in paper format: o To be stored in a locked cabinet or office, with only a restricted, known number of people having access to it. Additionally, HortiFoodTrends partners will ensure data security following standard guidelines: • Store data in at least two different locations to prevent data loss: o Back up data in the secondary/alternative open repository. D7.1 DMP I page 24 of 28 o Back up data in the respective institution database (or space) and external hard disks. • Enabling firewalls in computers/laptops and regularly updating antivirus/malware software. • Limit the use of flash drives (i.e. USB). Label files systematically to ensure consistency of the final dataset. All data (including restricted, confidential, and sensitive data) will be stored safely in the open science data repository (Zenodo) and published in open-access journals. Research data stored in Zenodo is securely stored on CERN premises. Each file copy has two replicas located on different disk servers. 7 ETHICS The research activities that require experimental procedures and possible ethical considerations are listed in Table 6. The table includes information about data collection methods and the source of the data. Table 6: Information from each experimental task regarding data collection and from whom the data is collected Task Data collection methods Originating from T4.1 Online survey with consumers using appropriate recruitment channels to obtain representative samples. In each country (PL, FR, DK), data will be collected from approximately 300 individuals (with equal gender and age distribution). T4.2 Sensory analysis of developed products using digitised data collection tools (Fizz). Sensory analysis: data from a trained sensory panel of around 10 persons (aiming for reasonable gender and age distribution) T4.2 Consumer sensory and acceptance test with consumers using appropriate recruitment channels to obtain representative samples. In each country (PL, FR, DK), data from approximately 100 individuals (with a reasonable gender and age distribution) will be collected. T4.3 Expert opinions of the developed products collected in group interviews. In PL, views from around 10 food experts involved in the supply chain (aiming for reasonable gender and age distribution). T6.3 Focus group as the driving force in acceptance of finished products. In PL data up to 15 persons (aiming for a minimum of 40% women and a reasonable age distribution) will be collected. T6.3 Interviews with investors regarding based of human, social, material aspects of responsible innovation. In PL opinions from around 10 product experts (aiming for a minimum of 40% women). HortiFoodTrends activities will be carried out in accordance with national and EU rules, ensuring that the principle of proportionality, the right to privacy, the right to the protection of personal data, the right to physical and mental integrity of a person, the right to non-discrimination and to the need to ensure protection of the environment and high levels of human health protection are duly implemented in the project (Ethical guidelines of Horizon Europe). HortiFoodTrends activities will be carried out in accordance with national and EU legislation, ensuring that the principle of proportionality, the right to privacy, the right to the protection of personal data, the right to physical and mental integrity of the person, the right to non-discrimination and the need to ensure the protection of the environment and a high level of human health are duly implemented in the project. Activities will be designed so that human participants face no greater risk of harm or risk when running experiments than would typically be encountered in everyday life. In particular, when planning their D7.1 DMP I page 25 of 28 studies, the partners will evaluate their designs in light of the kinds of risks that might arise in the course of social science and humanities research. Such risks might include, but are not limited to: risks to expectations of privacy, such as location tracking or internet usage; collection of sensitive or personally identifying data; and any social or physical stress or discomfort. Studies evaluated to involve such risks will be referred to the relevant National Committee on Research Ethics. InHort is responsible for the appropriate management of all ethical aspects, and most specifically for: 1. Ensuring the proper management of all ethics procedures. 2. Supervising all actions related to users. In addition, LYFE's Data Protection Officer will provide ethics advice and recommendations to all partners. 7.1 Ethical Procedures In this document, the procedures are described in general terms. At the project level, they will be refined and integrated according to the specific context of each project activity, its validation plan, and the national regulatory framework. Where necessary, the opinions/approvals of ethics committees and/or competent authorities regarding research involving humans will be submitted in accordance with the national legislation of the country concerned and, once obtained, will be kept on file. Therefore, the project team must plan in advance every action to ensure ethical research across all aspects of the process. 7.1.1 Recruitment Processes and Criteria In the project, the research activities will exclusively involve voluntary adults able to give informed consent. Participants will be identified and recruited by the relevant channels in the three countries. For consumer studies, standard procedures for obtaining representative samples will be used, with specific quotas for age and gender. Participants will be identified and recruited in France, Denmark, and Poland through social networks, project and partner websites, mailing lists, pamphlet distribution, and word of mouth (presentations to community groups or face-to-face meetings). In some cases, recruitment may be conducted by external agencies. They must perform the recruitment in a manner consistent with ethical considerations: • Respect for autonomy for privacy. • Any coercion or perceived pressure must be avoided. Potential participants will be given adequate time to ask questions and freely consider whether to take part in the study to ensure that their participation is indeed voluntary. Volunteers may withdraw from participation at any time without consequences, and they will be reminded that participation is voluntary. • Accurate and precise description of the project. • Unbiased presentation of the project. The partners will recruit trained sensory panelists. Standard guidelines (ISO 8586, 2023) for screening and selecting panellists are applied. Only voluntary adults are used. 7.1.2 Informed Consent Procedures To protect the autonomy and welfare of the participants, free and fully informed consent will be obtained before the beginning of each research, using adapted information templates.