100+ datasets found
  1. d

    Data Management Plan Examples Database

    • search.dataone.org
    • borealisdata.ca
    Updated Sep 4, 2024
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    Evering, Danica; Acharya, Shrey; Pratt, Isaac; Behal, Sarthak (2024). Data Management Plan Examples Database [Dataset]. http://doi.org/10.5683/SP3/SDITUG
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    Dataset updated
    Sep 4, 2024
    Dataset provided by
    Borealis
    Authors
    Evering, Danica; Acharya, Shrey; Pratt, Isaac; Behal, Sarthak
    Time period covered
    Jan 1, 2011 - Jan 1, 2023
    Description

    This dataset is comprised of a collection of example DMPs from a wide array of fields; obtained from a number of different sources outlined below. Data included/extracted from the examples include the discipline and field of study, author, institutional affiliation and funding information, location, date created, title, research and data-type, description of project, link to the DMP, and where possible external links to related publications or grant pages. This CSV document serves as the content for a McMaster Data Management Plan (DMP) Database as part of the Research Data Management (RDM) Services website, located at https://u.mcmaster.ca/dmps. Other universities and organizations are encouraged to link to the DMP Database or use this dataset as the content for their own DMP Database. This dataset will be updated regularly to include new additions and will be versioned as such. We are gathering submissions at https://u.mcmaster.ca/submit-a-dmp to continue to expand the collection.

  2. d

    University of Arizona Data Management Plan Exercise Example

    • search.dataone.org
    Updated Dec 5, 2021
    + more versions
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    Liza Brazil (2021). University of Arizona Data Management Plan Exercise Example [Dataset]. https://search.dataone.org/view/sha256%3A55477a755bfa837d3fe344a69a256acfd39be98dc260c0f7975ddea25afaae4f
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    Dataset updated
    Dec 5, 2021
    Dataset provided by
    Hydroshare
    Authors
    Liza Brazil
    Description
  3. W

    Data from: Africa RISING - Data Management Plan

    • cloud.csiss.gmu.edu
    • open.africa
    • +1more
    pdf
    Updated Jul 15, 2021
    + more versions
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    Open Africa (2021). Africa RISING - Data Management Plan [Dataset]. https://cloud.csiss.gmu.edu/uddi/fa_IR/dataset/ee3f7108-e69f-48d0-984f-3ccd8f1e93d3
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    pdfAvailable download formats
    Dataset updated
    Jul 15, 2021
    Dataset provided by
    Open Africa
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The data management plan is developed to provide guidance on data management practices and standards for research institutions and teams working on Africa RISING program. The document is organized as follows:

    • Section 2 discusses open data access, Africa RISING Program data sources and types, metadata management, and data standardization.
    • Section 3 discusses Program data management and access tools.
    • Section 4 discusses internal and external diffusion of Program data.
    • Section 5 discusses data storage and transmission.
  4. Z

    Example dataset

    • data.niaid.nih.gov
    • zenodo.org
    • +1more
    Updated Jun 23, 2021
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    Mario Merino (2021). Example dataset [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4884774
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    Dataset updated
    Jun 23, 2021
    Dataset authored and provided by
    Mario Merino
    Description

    Example dataset

    This is merely an example dataset, intended only for illustration purposes. It is used as an example in the Data Management Plan of the ERC-ZARATHUSTRA project, hosted at https://github.com/ep2lab/zarathustra-dmp

    It contains the README template proposed by the Data Management Plan at its 3.0.0 version.

  5. Data Management for Qualitative Research (OSU)

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated May 30, 2023
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    Sebastian Karcher (2023). Data Management for Qualitative Research (OSU) [Dataset]. http://doi.org/10.6084/m9.figshare.6852908.v1
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Sebastian Karcher
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Workshop at the Ohio State University, July 23rd 2018 A hands-on workshop on the dos and don’ts of data management with a focus on qualitative social science data. The data management plan is at the core of this workshop and participants will either develop their DMP or learn how to develop existing DMPs throughout the workshop. We will cover topics throughout the data lifecycle, from planning data management to sharing the data, with a focus on practical, hands-on advice.

  6. e

    EXC IntCDC - Data Management Plan Template for Research Projects - Dataset -...

    • b2find.eudat.eu
    Updated Oct 22, 2023
    + more versions
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    (2023). EXC IntCDC - Data Management Plan Template for Research Projects - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/2fb8266c-709a-5413-b2a0-8c2cf01f014b
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    Dataset updated
    Oct 22, 2023
    Description

    This Data Management Plan describes the data management life cycle for the data, a Research Project of EXC IntCDC will collect, process and/or generate. Moreover, it describes whether and how this data is being used and/or made publicly available for verification and re-use and how the data will be curated and preserved after the end of the project. This is the generic Data Management Plan template for a research project of EXC IntCDC.

  7. D4.2 Data Management Plan (Initial version)

    • figshare.com
    pdf
    Updated Apr 5, 2016
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    STARS4ALL Project (2016). D4.2 Data Management Plan (Initial version) [Dataset]. http://doi.org/10.6084/m9.figshare.3153976.v1
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    pdfAvailable download formats
    Dataset updated
    Apr 5, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    STARS4ALL Project
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is the initial version of the STARS4ALL Data Management Plan

  8. D

    ERIM Data Management Plan Template

    • dataverse.nl
    • narcis.nl
    docx
    Updated Aug 16, 2025
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    Miriam Braskova; Miriam Braskova (2025). ERIM Data Management Plan Template [Dataset]. http://doi.org/10.34894/1RJCXD
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    docx(23157)Available download formats
    Dataset updated
    Aug 16, 2025
    Dataset provided by
    DataverseNL
    Authors
    Miriam Braskova; Miriam Braskova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is an in-house ERIM template for the research data management plan. It was created using the Digital Curation Centre (DCC) template and adjusted to better reflect local needs. Privacy aspects of personal data, in line with the EU-based General Data Protection Regulation Act (GDPR), are also included. Always consult your local data management support when filling in the template.

  9. d

    LNWB Ch03 Data Processes - data management plan

    • search.dataone.org
    • hydroshare.org
    Updated Dec 5, 2021
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    Christina Bandaragoda; Bracken Capen; Joanne Greenberg; Mary Dumas; Peter Gill (2021). LNWB Ch03 Data Processes - data management plan [Dataset]. https://search.dataone.org/view/sha256%3Aa7eac4a8f4655389d5169cbe06562ea14e88859d2c4b19a633a0610ca07a329f
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    Dataset updated
    Dec 5, 2021
    Dataset provided by
    Hydroshare
    Authors
    Christina Bandaragoda; Bracken Capen; Joanne Greenberg; Mary Dumas; Peter Gill
    Description

    Overview: The Lower Nooksack Water Budget Project involved assembling a wide range of existing data related to WRIA 1 and specifically the Lower Nooksack Subbasin, updating existing data sets and generating new data sets. This Data Management Plan provides an overview of the data sets, formats and collaboration environment that was used to develop the project. Use of a plan during development of the technical work products provided a forum for the data development and management to be conducted with transparent methods and processes. At project completion, the Data Management Plan provides an accessible archive of the data resources used and supporting information on the data storage, intended access, sharing and re-use guidelines.

    One goal of the Lower Nooksack Water Budget project is to make this “usable technical information” as accessible as possible across technical, policy and general public users. The project data, analyses and documents will be made available through the WRIA 1 Watershed Management Project website http://wria1project.org. This information is intended for use by the WRIA 1 Joint Board and partners working to achieve the adopted goals and priorities of the WRIA 1 Watershed Management Plan.

    Model outputs for the Lower Nooksack Water Budget are summarized by sub-watersheds (drainages) and point locations (nodes). In general, due to changes in land use over time and changes to available streamflow and climate data, the water budget for any watershed needs to be updated periodically. Further detailed information about data sources is provided in review packets developed for specific technical components including climate, streamflow and groundwater level, soils and land cover, and water use.

    Purpose: This project involves assembling a wide range of existing data related to the WRIA 1 and specifically the Lower Nooksack Subbasin, updating existing data sets and generating new data sets. Data will be used as input to various hydrologic, climatic and geomorphic components of the Topnet-Water Management (WM) model, but will also be available to support other modeling efforts in WRIA 1. Much of the data used as input to the Topnet model is publicly available and maintained by others, (i.e., USGS DEMs and streamflow data, SSURGO soils data, University of Washington gridded meteorological data). Pre-processing is performed to convert these existing data into a format that can be used as input to the Topnet model. Post-processing of Topnet model ASCII-text file outputs is subsequently combined with spatial data to generate GIS data that can be used to create maps and illustrations of the spatial distribution of water information. Other products generated during this project will include documentation of methods, input by WRIA 1 Joint Board Staff Team during review and comment periods, communication tools developed for public engagement and public comment on the project.

    In order to maintain an organized system of developing and distributing data, Lower Nooksack Water Budget project collaborators should be familiar with standards for data management described in this document, and the following issues related to generating and distributing data: 1. Standards for metadata and data formats 2. Plans for short-term storage and data management (i.e., file formats, local storage and back up procedures and security) 3. Legal and ethical issues (i.e., intellectual property, confidentiality of study participants) 4. Access policies and provisions (i.e., how the data will be made available to others, any restrictions needed) 5. Provisions for long-term archiving and preservation (i.e., establishment of a new data archive or utilization of an existing archive) 6. Assigned data management responsibilities (i.e., persons responsible for ensuring data Management, monitoring compliance with the Data Management Plan)

    This resource is a subset of the LNWB Ch03 Data Processes Collection Resource.

  10. e

    DICE: data management plan - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Apr 5, 2023
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    (2023). DICE: data management plan - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/7166de57-608d-50ea-b632-d651a867cc19
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    Dataset updated
    Apr 5, 2023
    Description

    This document is the first version of the DICE data management plan. It provides information on the type of data being produced by the project, their sources and how the consortium will act to support the FAIR principles during and after the lifetime of the project. The current data management plan is to be considered a living document that will be enriched during the project with a final version to be released at M18.

  11. Z

    Analyzed dataset: DMPs chosen for the study titled 'Researchers' Perception...

    • data.niaid.nih.gov
    Updated Jul 11, 2024
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    Veiga, Viviane (2024). Analyzed dataset: DMPs chosen for the study titled 'Researchers' Perception and Practice with with Management Plans in the Health: An Exploratory Study' [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8335518
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    Dataset updated
    Jul 11, 2024
    Dataset provided by
    Pereira, Isabella H. Lima
    Pires, Luís Ferreira
    Moreira, João
    Veiga, Viviane
    Henning, Patrícia
    Description

    This data corresponds to the compilation and study carried out in the DMPs of researchers who responded to a questionnaire about completing Data Management Plans. The table shows information regarding the DMPs link, country of research development, affiliation, research title, template used and the funding agencies.

  12. U

    Data Management Plan

    • research-data.urosario.edu.co
    pdf
    Updated Aug 16, 2024
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    Universidad del Rosario (2024). Data Management Plan [Dataset]. http://doi.org/10.34848/LXPHTB
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    pdf(449570)Available download formats
    Dataset updated
    Aug 16, 2024
    Dataset provided by
    Universidad del Rosario
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This document outlines the systematic approach for collecting, handling, and safeguarding data throughout the research study. It details procedures for data collection. The plan outlines data storage methods complying with regulations and security guidelines for safeguarding patient confidentiality. It includes guidelines for data validation and quality control to maintain data integrity and accuracy. Additionally, the plan addresses data sharing and archiving practices, outlining how data will be disseminated and preserved for future reference while ensuring adherence to ethical and legal requirements.

  13. Data management plan (DMP): Towards a more efficient scientific management...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Dec 24, 2024
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    Kevin Amilcar Hernández Gutierrez; César Hernández; Doria América Díaz (2024). Data management plan (DMP): Towards a more efficient scientific management at the Universidad Centroamericana José Simeón Cañas [Dataset]. http://doi.org/10.5061/dryad.1zcrjdg25
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    zipAvailable download formats
    Dataset updated
    Dec 24, 2024
    Dataset provided by
    Universidad Centroamericana José Simeón Cañas
    Biblioteca Judicial "Dr Ricardo Gallardo"
    Authors
    Kevin Amilcar Hernández Gutierrez; César Hernández; Doria América Díaz
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    This dataset presents the assessment tool used to analyze 20 Data Management Plan (DMP) templates on the Argos platform, along with the pre-print of the manuscript for an article that is about to be published in the Journal Biblios of the University of Pittsburgh. The main objective of this study was to investigate the need to implement a DMP at Universidad Centroamericana José Simeón Cañas (UCA) to improve accessibility, discovery, and reuse of research. Using a qualitative case study methodology, we worked with 10 selected research groups to evaluate and adapt a base model for the DMP. The results indicated a significant improvement in research data management and a positive perception from users regarding the processing and organization of their data. This set includes the DMP format generated for UCA, as well as recommendations for other institutions interested in adopting similar data management practices, contributing to the continued growth of scholarly output and the ethical and responsible management of data. This summary encapsulates the objectives, methods, results, and relevance of the dataset, providing a clear and concise overview of the work conducted. Methods Method: A qualitative case study methodology was employed, which included participant observation of researchers and administrative staff from various 2024 research groups, along with an analysis of documentation and LibGuides. A benchmarking process was also conducted, comparing 20 PGDI templates to extract the best structure and practices from various research institutions. Content analysis: This method was used to examine a set of 20 PGDI templates from the ARGOS initiative, a platform developed by OpenAIRE and EUDAT for planning and managing research data. A systematic review of the structure and content of each of these templates was conducted, assessing the clarity, consistency, and adequacy of the information presented. Through this content analysis, key elements were identified that needed to be incorporated or improved in the base template provided to UCA research groups. This process allowed us to highlight best practices and identify areas that required additional attention, thereby contributing to the continuous improvement of the resource used in implementing the model. Benchmarking of processes: A comparative analysis was conducted on the content and structure of 20 PGDI templates from research institutions that apply data management processes based on the proposed instrument. The objective of this analysis was to identify and evaluate the best sections of each selected template, using the instrument proposed in this study as a reference.

  14. e

    SFB/Transregio 161 Data Management Plan 2019-2023 - Dataset - B2FIND

    • b2find.eudat.eu
    Updated May 4, 2023
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    (2023). SFB/Transregio 161 Data Management Plan 2019-2023 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/d62795a5-7452-50d5-ac03-b34d6ce56acc
    Explore at:
    Dataset updated
    May 4, 2023
    Description

    The participating universities in SFB/Transregio 161 acknowledge the general importance of research data management as a vital issue for all of their work and provide increasing central support for long-term accessibility and reusability of data, documentation of methods and tools and privacy protection. However, technical and organisational offerings for data management can only be effective as far as researchers are aware of them and can make informed decisions on which solution is the right one for which data, which in turn requires an overall knowledge of the types and amounts of data collected or produced in the project. Furthermore, ensuring long-term availability of data for reproducibility of research results, which is one of the key ideas behind the research efforts of SFB/Transregio 161, requires planful actions as serving data beyond the lifetime of a project involves allocation of technical and organisation resources. This data management plan (DMP) identifies the research data collected or produced in SFB/Transregio 161, assesses their value for the goals of reusability and reproducibility and states the timeframes in which SFB/Transregio 161 and/or the participating universities guarantee their future availability. It furthermore describes the technical and organisational means for storing and publishing research data which the researchers of SFB/Transregio 161 can make use of. Such means might be provided by the project and funded by DFG or by the universities. The DMP states minimum requirements for metadata that must be provided for research data, briefly addresses privacy and ethics issues and provides the researchers with guidelines for GPDR-compliant handling of personal data which might be collected in the projects. The DMP is a living document and therefore will be updated as necessary.

  15. e

    Data Management Plan (DMP) for large CRC projects.

    • data.europa.eu
    zip
    Updated Nov 7, 2023
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    Universitätsbibliothek der Technischen Universität München (2023). Data Management Plan (DMP) for large CRC projects. [Dataset]. https://data.europa.eu/data/datasets/https-open-bydata-de-api-hub-repo-datasets-https-mediatum-ub-tum-de-1709465-dataset?locale=bg
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    zipAvailable download formats
    Dataset updated
    Nov 7, 2023
    Dataset authored and provided by
    Universitätsbibliothek der Technischen Universität München
    License

    http://dcat-ap.de/def/licenses/cc-byhttp://dcat-ap.de/def/licenses/cc-by

    Description

    This data management plan was created for large Collaborative Research Centers (CRC). The data generated in such centers is considered big, broad and heterogeneous. It may range from surveys, lab experiments, simulations, data models to software code and hardware design as well as real world objects etc. This plan has been implemented for the work of TRR277 AMC (a CRC funded by German Research Council (DFG)) since mid-2020. Since then, it has been offered as template of online fillable forms in TUM Workbench. TUM Workbench features some of the basic properties e.g. title, unique ID and project/ work package associations. And the functions of versioning and logs. The Guidelines and hints section of this DMP has been through several updates to help users. The latest draft version 3.2.1 dated September 02, 2022 is being published in its actual document form.

  16. Data Set from the DMP survey and interviews - intermediate results

    • zenodo.org
    bin
    Updated Dec 20, 2022
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    Daniela A. Hausen; Daniela A. Hausen; Ann-Christin Andres; Ann-Christin Andres; Jochen Dr. Ortmeyer; Jochen Dr. Ortmeyer; Herres-Pawlis, Sonja, Prof. Dr.; Herres-Pawlis, Sonja, Prof. Dr. (2022). Data Set from the DMP survey and interviews - intermediate results [Dataset]. http://doi.org/10.5281/zenodo.7443839
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    binAvailable download formats
    Dataset updated
    Dec 20, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Daniela A. Hausen; Daniela A. Hausen; Ann-Christin Andres; Ann-Christin Andres; Jochen Dr. Ortmeyer; Jochen Dr. Ortmeyer; Herres-Pawlis, Sonja, Prof. Dr.; Herres-Pawlis, Sonja, Prof. Dr.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is the data set for a series of interviews in chemistry on data management (plans) and presents interim results. A more detailed analysis and description can be found in the paper "Road to a Chemistry-specific Data Management Plan" submitted to Data Science Journal (2022-12-15).
    The interview series will continue in 2023 and final results will be published later in 2023.

    The aim of the conducted interview series is the enrichment of the online survey data from the RDA WG Discipline-specific Guidance for DMP and in a second step the development of a chemistry-specific data management plan template. For this purpose, the current status of data management as well as information about the workflows in the various chemical disciplines were requested in a personal interview with 22 participants so far.

    All the gathered information and examples will be used to develop a DMP template or guide in line with chemistry-specific requirements. The results provide a comprehensive outlook on the future developments of RDM in chemistry. Possible strategies for implementation are also discussed.

  17. H

    SU-EOSC Nordic 5.3.2 maDMP project

    • dataverse.harvard.edu
    Updated Nov 21, 2022
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    Joakim Philipson (2022). SU-EOSC Nordic 5.3.2 maDMP project [Dataset]. http://doi.org/10.7910/DVN/MGZBAL
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 21, 2022
    Dataset provided by
    Harvard Dataverse
    Authors
    Joakim Philipson
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Sep 1, 2020 - Nov 14, 2022
    Dataset funded by
    EOSC Nordic wp. 5
    Description

    Stockholm University SU-VR template (pdf) in DMP Online, based on Swedish Research Council (VR) and Science Europe model (sections I-VI and original questions), but with more specified question and answer options by means of multiple choice checkboxes , dropdown menus, radio buttons for increased machine actionability of output. The template has possible answers formatted with respect to Stockholm University Research Data Policy, local research data management rules and the RDA DMP Common Standard. The objectives are to make it easier to fill out for the individual researcher and the output (from DMP Online API v0) more machine-actionable, thus facilitating review, validation against RDA DMP Common Standard maDMP-schema and evaluation of potential FAIRness of data management measures described in the DMP. Version (v33) of the template also involves a change to a one phase model - Initial and Full DMP phase in one, motivated in part by an effort to avoid repeated entries of the same information. Instead, a final section IX: Full DMP - additional Datasets and identifiers, Reference list and Project end has been introduced to mark the completion of the research project described in the DMP. New from version 34 of the template (published in DMP Online 2021-10-05) are questions in section VIII DMP administrative information:Q5-Q7 about Funder, Grant ID and Funding status. From version 0-93 of the XSLT transformation file SUDMP2maDMP1-1.xsl there is a funderName2fundRefIDmap, which leverages the answers to VIII:Q5-7 for enhanced compliance with the RDA DMP Common Standard. Also included in this dataset is a Schematron schema (working on the transform.xml files) for assessment of prospective FAIRness of the RDM measures described by the DMP ("Research Outputs" in DMP Tool). Further included are DMP Online instances of DMPs that used the SU-VR maDMP template, with raw API (v0) JSON output, converted to XML, then transformed using XSLT-file and converted back to JSON to check compliance with maDMP-schema-1.1.json (also included in this dataset). File descriptions in this dataset begin with a number (0), representing the workflow in the processing or production of the files, while files are presented in alphanumeric order based on file names, not entirely corresponding to the workflow order, but in the tree-view distributed in different folders for different versions of the template (v33, v34 etc.). From SU-VR template v.35, substantial changes have also been made to the transformation file (SUDMP2maDMP1-1.xsl.xsl), version 0.95 and the FAIRness evaluation schema (Schematron SUDMP-FAIReval.sch, v0.2), following also a change in conversion algorithm JSON to XML to JSON in Oxygen XML Editor 24.0. The transformation file SUDMP2maDMP1-1.xsl v0.95 further uses a direct download of the DMP export.json, converted to xml, as a parameter document for the provision of some information elements lacking in the APIv0 output, notably start and end-date of project. Updated again (2022-03-08) with SU-VR template v36, transformation file SUDMP2maDMP1-1.xsl v0.96 and Schematron schema SUDMP-FAIReval.sch v0.3, including refined validation of consistency between dataset identifier and identifier type. Last update before publication (and activation of DOI) with SU-VR template v40, SUDMP-FAIReval.sch v0.4, instance DMP111193 files (.json, .xml, .html, .pdf) and SUDMP2maDMP1-1.xsl: 2022-11-14 *New version 0.98: Added transform_dateTime/current-dateTime() to get a time stamp of last transformation performed. Cleaned up" text in Section I: ReusedDatasetURL-licenseQ9/Text with local:removeHtml-function. Added FAIR Enabling Resources - nanopublication identifiers / links to FAIR-score for doi, handle, and orcid. For best overview of files included please use Tree tab! (description/metadata updated):

  18. Crosswalks from the NFDI4DS hackathon "machine-actionable Data Management...

    • zenodo.org
    bin, pdf, tsv
    Updated May 26, 2025
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    Dhwani Solanki; Dhwani Solanki; Suhasini Venkatesh; Suhasini Venkatesh; Safial Islam Ayon; Safial Islam Ayon; Martin Armbruster; Martin Armbruster; Katja Diederichs; Katja Diederichs; Sara El-Gebali; Sara El-Gebali; Giacomo Lanza; Giacomo Lanza; Antonia Leidel; Antonia Leidel; Jimena Linares Gómez; Jimena Linares Gómez; Olaf Michaelis; Olaf Michaelis; Rajendran Rajapreethi; Rajendran Rajapreethi; Marco Reidelbach; Marco Reidelbach; Gabriel Schneider; Gabriel Schneider; Sabine Schönau; Sabine Schönau; Christoph Steinbeck; Christoph Steinbeck; David Wallace; David Wallace; Jürgen Windeck; Jürgen Windeck; Xiao-Ran Zhou; Xiao-Ran Zhou; Leyla Jael Castro; Leyla Jael Castro (2025). Crosswalks from the NFDI4DS hackathon "machine-actionable Data Management Plan for NFDI" [Dataset]. http://doi.org/10.5281/zenodo.15129830
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    tsv, bin, pdfAvailable download formats
    Dataset updated
    May 26, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Dhwani Solanki; Dhwani Solanki; Suhasini Venkatesh; Suhasini Venkatesh; Safial Islam Ayon; Safial Islam Ayon; Martin Armbruster; Martin Armbruster; Katja Diederichs; Katja Diederichs; Sara El-Gebali; Sara El-Gebali; Giacomo Lanza; Giacomo Lanza; Antonia Leidel; Antonia Leidel; Jimena Linares Gómez; Jimena Linares Gómez; Olaf Michaelis; Olaf Michaelis; Rajendran Rajapreethi; Rajendran Rajapreethi; Marco Reidelbach; Marco Reidelbach; Gabriel Schneider; Gabriel Schneider; Sabine Schönau; Sabine Schönau; Christoph Steinbeck; Christoph Steinbeck; David Wallace; David Wallace; Jürgen Windeck; Jürgen Windeck; Xiao-Ran Zhou; Xiao-Ran Zhou; Leyla Jael Castro; Leyla Jael Castro
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary

    From 28 to 30 October 2024, ZB MED Information Centre for Life Sciences organized a hackathon in Cologne within the scope of NFDI4DataScience with the purpose of identifying core elements for a machine-actionable Data Managemnt Plan (maDMP) across the German National Research Data Infrastructure (NFDI). We used as a starting/reference point the maDMP application profile from the Research Data Alliance DMP Commons Working Group. An additional element, ManagementPlan, was also included. Management Plan comes originally from DataCite v4.4, its representation as an extension proposed by the ZB MED/NFDI4DataScience machine-actionable Software Management Plan metadata schema was used.

    This dataset comprises crosswalks corresponding to the following elements from the RDA maDMP: DMP, Project, Dataset, Distribution. The crosswalks were created following a template prepared by the organizers. Participants freely select a metadata schema or platform to be mapped with regards to the attributes in the RDA maDMP application profile. Crosswalks were created for DMP, Project, Dataset, and Distribution, while comments were provided by DMP and Dataset.

    The list of files in this dataset is as follows:

    • Crosswalk template: two spreadsheets (AllTemplates.ods and AllTemplates.xlsx) containing 13 tabs corresponding to the instructions (InstructionsAllTemplates.pdf and InstructionsAllTemplates.tsv), crosswalks templates for Management Plan (CrosswalkTemplate-MngPlan.tsv), DMP (CrosswalkTemplate-DMP.tsv), Project (CrosswalkTemplate-Project.tsv), Dataset (CrosswalkTemplate-Dataset.tsv), Distribution (CrosswalkTemplate-Distribution.tsv) and Host (CrosswalkTemplate-Host.tsv), and comment templates for all the same elements Management Plan (CommentsTemplate-MngPlan.tsv), DMP (CommentsTemplate-DMP.tsv), Project (CommentsTemplate-Project.tsv), Dataset (CommentsTemplate-Dataset.tsv), Distribution (CommentsTemplate-Distribution.tsv) and Host (CommentsTemplate-Host.tsv). The crosswalk templates are meant to be used to compare a source against the reference point while the comment templates are meant to be used to provide comments to the reference point. Eash tab/crosswalk is also provided as individual TSV files. The crosswalk and comment templates contain the following columns:
      • Crosswalk for the reference source: Property, Range, Description, Cardinality (One, Many), Requirement (minimum, recommended, optional), Example
      • Crosswalk for the mapped source: Property, Range, Description, Cardinality (One, Many), Requirement (minimum, recommended, optional), Recommended Vocabulary, Comment, Review
      • Comments for the reference source: Property, Range, Description, Cardinality (One, Many), Requirement (minimum, recommended, optional), Example
      • Comments for the mapped source: Comments to Property, Comments to Range, Comments to Description, Comments to Cardinality (One, Many), Comments to Requirement (minimum, recommended, optional), Recommended Vocabulary
    • Crosswalk summary: two spreadsheets (Summary.ods and Summary.xlsx) containing six tabs corresponding to crosswalks summary for DMP (Summary-DMP.tsv), Project (Summary-Project.tsv), Dataset (Summary-Dataset.tsv), and Distribution (Summary-Distribution.tsv), and comments summary forDMP (Summary-Comments-DMP.tsv), and Dataset (Summary-Comments-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files. The crosswalks and comments always contain the reference point (i.e, as defined by the RDA maDMP application profile) and the following mapped resources, separated by an empty (blue) column:
      • Crosswalks for DMP: RDMO, DataPLAN, NFDIxCS, Horizon Europe, DFG Checklist, DataCite, and GFBio_DMPT
      • Comments to DMP: NFDIxCS
      • Crosswalks for Project: RDMO, Metadata4Ing, NFDIxCS, Schema.org, and DFG Checklist
      • Crosswalks for Dataset: RDMO, DataPLAN, Metadata4Ing, NFDIxCS, Horizon Europe, DFG Checklist, and DataCite
      • Comments to Dataset: NFDIxCS
      • Crosswalks for Distribution: RDMO and Metadata4Ing
    • Crosswalks to RDMO: two spreadsheets (RDMO.ods and RDMO.xlsx) containing four tabs corresponding to the crosswalks for DMP (RDMO-DMP.tsv), Project (RDMO-Project.tsv), Dataset (RDMO-Dataset.tsv) and Distribution (RDMO-Distribution.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to DataPLAN: two spreadsheets (DataPLAN.ods and DataPLAN.xlsx) containing two tabs corresponding to the crosswalks for DMP (DataPLAN-DMP.tsv) and Dataset (DataPLAN-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to Metadata4Ing: two spreadsheets (Metadata4Ing.ods and Metadata4Ing.xlsx) containing three tabs corresponding to the crosswalks for Project (Metadata4Ing-Project.tsv), Dataset (Metadata4Ing-Dataset.tsv) and Distribution (Metadata4Ing-Distribution.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to NFDIxCS: two spreadsheets (NFDIxCS.ods and NFDIxCS.xlsx) containing five tabs corresponding to the crosswalks for DMP (NFDIxCS-DMP.tsv), Project (NFDIxCS-Project.tsv), and Dataset (NFDIxCS-Dataset.tsv), and additional comments for DMP (NFDIxCS-Comments-to-DMP.tsv) and Dataset (NFDIxCS-Comments-to-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to Schema.org: two spreadsheets (SchemaOrg.ods and SchemaOrg.xlsx) containing one tab corresponding to the crosswalk for Project (SchemaOrg-Project.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to Horizon Europe as recorded in its RDMO template: two spreadsheets (HorizonEurope.ods and HorizonEurope.xlsx) containing two tabs corresponding to the crosswalks for DMP (HorizonEurope-DMP.tsv) and Dataset (HorizonEurope-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to DFG Checklist as recorded in its template in RDMO: two spreadsheets (DFGChecklist.ods and RDFGChecklistMO.xlsx) containing three tabs corresponding to the crosswalks for DMP (DFGChecklist-DMP.tsv), Project (DFGChecklist-Project.tsv), and Dataset (DFGChecklist-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to DataCite v4.5: two spreadsheets (DataCite.ods and DataCite.xlsx) containing two tabs corresponding to the crosswalks for DMP (DataCite-DMP.tsv) and Dataset (DataCite-Dataset.tsv). Eash tab/crosswalk is also provided as individual TSV files.
    • Crosswalks to GFBio_DMPT: two spreadsheets (GFBio_DMPT.ods and GFBio_DMPT.xlsx) containing one tabs corresponding to the crosswalk for DMP (GFBio_DMPT-DMP.tsv). Eash tab/crosswalk is also provided as individual TSV files.

    More information about the activities carried out during the hackathon and the analysis of the crosswalks available at 10.5281/zenodo.15130045.

    Acknowledgements

    The activities and discussion reported here were carried out during a hackathon organized by the Semantic Technologies team at ZB MED Information Centre from 28 to 30 October 2024 in Cologne, Germany, and sponsored by the NFDI4DataScience consortium. NFI4DataScience is funded by the German Research Foundation (Deutsche Forschungsgemeinschaft – DFG) under the grant No. 460234259

    The DMP4NFDI team acknowledges the support of DFG - German Research Foundation - through the coordination fund (project number 521466146).

    David Wallace and Jürgen Windeck would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4ING consortium. Funded by the German Research Foundation (DFG) - project number 442146713.

    Marco Reidelbach is supported by MaRDI, funded by the Deutsche Forschungsgemeinschaft (DFG), project number 460135501, NFDI 29/1 “MaRDI – Mathematische Forschungsdateninitiative”.

  19. Z

    Data from: OpenAIRE and FAIR Data Expert Group survey about Horizon 2020...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Aug 2, 2024
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    Sarah Jones (2024). OpenAIRE and FAIR Data Expert Group survey about Horizon 2020 template for Data Management Plans [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_1120244
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    Dataset updated
    Aug 2, 2024
    Dataset provided by
    Sarah Jones
    Marjan Grootveld
    Eliane Fankhauser
    Emilie Hermans
    Ellen Leenarts
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.

    It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.

    The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.

    Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.

    At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.

  20. d

    Data Management Plan

    • dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Calleja, Sabine (2023). Data Management Plan [Dataset]. http://doi.org/10.5683/SP3/A9DKJW
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Calleja, Sabine
    Description

    This data management plan (DMP) contains guidance and documentation on how HSIC librarians can upload their knowledge synthesis search strategy data. The DMP includes information on the types of data that should be uploaded, file format(s), file naming convention(s), license/reuse terms, and deposit guidance for librarians.

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Evering, Danica; Acharya, Shrey; Pratt, Isaac; Behal, Sarthak (2024). Data Management Plan Examples Database [Dataset]. http://doi.org/10.5683/SP3/SDITUG

Data Management Plan Examples Database

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Dataset updated
Sep 4, 2024
Dataset provided by
Borealis
Authors
Evering, Danica; Acharya, Shrey; Pratt, Isaac; Behal, Sarthak
Time period covered
Jan 1, 2011 - Jan 1, 2023
Description

This dataset is comprised of a collection of example DMPs from a wide array of fields; obtained from a number of different sources outlined below. Data included/extracted from the examples include the discipline and field of study, author, institutional affiliation and funding information, location, date created, title, research and data-type, description of project, link to the DMP, and where possible external links to related publications or grant pages. This CSV document serves as the content for a McMaster Data Management Plan (DMP) Database as part of the Research Data Management (RDM) Services website, located at https://u.mcmaster.ca/dmps. Other universities and organizations are encouraged to link to the DMP Database or use this dataset as the content for their own DMP Database. This dataset will be updated regularly to include new additions and will be versioned as such. We are gathering submissions at https://u.mcmaster.ca/submit-a-dmp to continue to expand the collection.

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