DATA MANAGEMENT PLANS Requirements and Recommendations for H2020 Projects. Matthias Razum April 20, 2018

Similar documents
EC Horizon 2020 Pilot on Open Research Data applicants

Towards FAIRness: some reflections from an Earth Science perspective

Science Europe Consultation on Research Data Management

Deliverable 6.4. Initial Data Management Plan. RINGO (GA no ) PUBLIC; R. Readiness of ICOS for Necessities of integrated Global Observations

Data Management Plans. Sarah Jones Digital Curation Centre, Glasgow

Checklist and guidance for a Data Management Plan, v1.0

Data Management Checklist

Open Access & Open Data in H2020

Make your own data management plan

Horizon 2020 Open Research Data Pilot: What is required? Sarah Jones Digital Curation Centre

How to share research data

Assessing the FAIRness of Datasets in Trustworthy Digital Repositories: a 5 star scale

Research Data Management

Horizon2020/EURO Coordination and Support Actions. SOcietal Needs analysis and Emerging Technologies in the public Sector

Swedish National Data Service, SND Checklist Data Management Plan Checklist for Data Management Plan

DuraSpace FAIRness and GDPR

NSF Data Management Plan Template Duke University Libraries Data and GIS Services

Legal Issues in Data Management: A Practical Approach

Horizon 2020 and the Open Research Data pilot. Sarah Jones Digital Curation Centre, Glasgow

Open Access to Publications in H2020

How FAIR am I? FAIR Principles and Interoperability of Data and Tools

Focus: Themes within Introduction and Context

Basic Requirements for Research Infrastructures in Europe

The KM3NeT Data Management Plan

GEOSS Data Management Principles: Importance and Implementation

RPg procedures for Research Data Management (RDM)

Developing a Research Data Policy

FAIR-aligned Scientific Repositories: Essential Infrastructure for Open and FAIR Data

Introduction to Data Management

Data management Backgrounds and steps to implementation; A pragmatic approach.

WP4: Data Forum. Øystein Godøy, Boris Radosavljević, Boris Biskaborn, Anna Irrgang

Mercè Crosas, Ph.D. Chief Data Science and Technology Officer Institute for Quantitative Social Science (IQSS) Harvard

CEH Environmental Information Data Centre support to NERCfunded. Jonathan Newman EIDC

Scientific Data Policy of European X-Ray Free-Electron Laser Facility GmbH

EUDAT B2FIND A Cross-Discipline Metadata Service and Discovery Portal

How to make your data open

Facilitate Open Science Training for European Research What to know about interdisciplinary research data management in order to assess DMPs

Data Curation Handbook Steps

Data Management Plan Generic Template Zach S. Henderson Library

Reproducibility and FAIR Data in the Earth and Space Sciences

Technical documentation. SIOS Data Management Plan

ASPECT Adopting Standards and Specifications for. Final Project Presentation By David Massart, EUN April 2011

Welcome to the Pure International Conference. Jill Lindmeier HR, Brand and Event Manager Oct 31, 2018

Checklist for a Data Management Plan (v3.0, 17 March 2011)

Metadata Overview: digital repositories

Adding Research Datasets to the UWA Research Repository

ZB MED Information Center Life Sciences

Scientific Research Data Management Policy

DATA PROTECTION POLICY THE HOLST GROUP

Archivierung und Publikation von Forschungsdaten mit RADAR

Management: A Guide For Harvard Administrators

Sharing Qualitative Data: Challenges and Opportunities

European Open Science Cloud Implementation roadmap: translating the vision into practice. September 2018

Data Management and Data Management Plans. Dr. Tomasz Miksa. TU Wien & SBA Research

DIGITAL STEWARDSHIP SUPPLEMENTARY INFORMATION FORM

Digital repositories as research infrastructure: a UK perspective

Wat is ORCID? Open Researcher en Contributor Identifier

META-SHARE : the open exchange platform Overview-Current State-Towards v3.0

Striving for efficiency

RADAR Introduction and Basic Concepts. Matthias Razum

Guidelines for Depositors

Data Curation Profile Food Technology and Processing / Food Preservation

DATA SELECTION AND APPRAISAL CHECKLIST University of Reading Research Data Archive

Guide to e-infrastructure Requirements for European Research Infrastructures

Comparing Curricula for Digital Library. Digital Curation Education

28 September PI: John Chip Breier, Ph.D. Applied Ocean Physics & Engineering Woods Hole Oceanographic Institution

Deliverable Initial Data Management Plan

Data is the new Oil (Ann Winblad)

Towards FAIRness in research data. Per Öster, 3 October 2018

Summary of Bird and Simons Best Practices

Feed the Future Innovation Lab for Peanut (Peanut Innovation Lab) Data Management Plan Version:

re3data.org - Making research data repositories visible and discoverable

I data set della ricerca ed il progetto EUDAT

Data subject ( Customer or Data subject ): individual to whom personal data relates.

EVALUATION AND APPROVAL OF AUDITORS. Deliverable 4.4.3: Design of a governmental Social Responsibility and Quality Certification System

Best Practice Guidelines for the Development and Evaluation of Digital Humanities Projects

META-SHARE: An Open Resource Exchange Infrastructure for Stimulating Research and Innovation

EUDAT-B2FIND A FAIR and Interdisciplinary Discovery Portal for Research Data

Inge Van Nieuwerburgh OpenAIRE NOAD Belgium. Tools&Services. OpenAIRE EUDAT. can be reused under the CC BY license

St Bernard s Primary School Data Protection Policy

Regulation for the accreditation of product Certification Bodies

Data Curation Profile Human Genomics

THEMATIC ANALYSIS OF DATA MANAGEMENT PLAN TOOLS AND EXEMPLARS

DSA WDS Partnership Working Group Catalogue of Common Requirements

Making research data repositories visible and discoverable. Robert Ulrich Karlsruhe Institute of Technology

Privacy Policy. staff members of our Clients who have been granted access to our Platform by the Client to use the Platform on the Client s behalf.

TARGET2-SECURITIES INFORMATION SECURITY REQUIREMENTS

National Materials Data Initiatives

Open Data is a new paradigm in which research data are freely and openly shared, with full re-use rights. Open data ensures that research integrity

Indexing Field Descriptions Recommended Practice

Data Curation Profile Movement of Proteins

Global Reference Architecture: Overview of National Standards. Michael Jacobson, SEARCH Diane Graski, NCSC Oct. 3, 2013 Arizona ewarrants

Indiana University Research Technology and the Research Data Alliance

The Road to Discovery is Paved with Standards

Approved 10/15/2015. IDEF Baseline Functional Requirements v1.0

Fair data and open data: differences and consequences

DATA PROTECTION POLICY

Data Management Planning

Research Data Edinburgh: MANTRA & Edinburgh DataShare. Stuart Macdonald EDINA & Data Library University of Edinburgh

DATA PROTECTION AND PRIVACY POLICY

Transcription:

DATA MANAGEMENT PLANS Requirements and Recommendations for H2020 Projects Matthias Razum April 20, 2018

DATA MANAGEMENT PLANS (DMP) typically state what data will be created and how, outline the plans for sharing and preservation noting what is appropriate given the nature of the data and any restrictions that may need to be applied. Source: Digital Curation Centre 2

HORZION 2020 REQUIREMENTS Guidelines on FAIR Data Management in Horizon 2020 Publications: open access is an obligation in Horizon 2020 Data: open access by default with opt-out ( flexible pilot ), applicable during the application phase during the grant agreement preparation (GAP) phase and after the signature of the grant agreement 3

DMP FOR HORIZON 2020 PROJECTS A DMP should include information on: the handling of research data during and after the end of the project what data will be collected, processed and/or generated which methodology and standards will be applied whether data will be shared/made open access and how data will be curated and preserved (including after the end of the project) Source: Guidelines on FAIR Data Management in Horizon 2020 4

FURTHER RECOMMENDATIONS For a H2020 proposal: ensure resource and budgetary planning for data management include a deliverable for an initial DMP at month 6 at the latest costs related to open access to research data are eligible for reimbursement during the duration of the project Your policy should also: reflect the current state of consortium agreements on data management be consistent with exploitation and Intellectual Property Rights (IPR) requirements 5

TYPICAL STRUCTURE FOR DMP 1. Data Summary 2. FAIR data 3. Allocation of resources 4. Data security 5. Ethical aspects 6. Other issues 6

TYPICAL STRUCTURE OF A DMP: DATA SUMMARY What is the purpose of the data collection/generation and its relation to the objectives of the project? What types and formats of data will the project generate/collect? Will you re-use any existing data and how? What is the origin of the data? What is the expected size of the data? To whom might it be useful ('data utility')? 7

THE FAIR DATA PRINCIPLES: A SET OF GUIDING PRINCIPLES TO MAKE DATA FINDABLE, ACCESSIBLE, INTEROPERABLE, AND RE-USABLE 8 Source: Force11

TYPICAL STRUCTURE OF A DMP: FAIR DATA - FINDABLE Are the data produced and/or used in the project discoverable with metadata, identifiable and locatable by means of a standard identification mechanism? What naming conventions do you follow? Will search keywords be provided that optimize possibilities for re-use? Do you provide clear version numbers? What metadata will be created? In case metadata standards do not exist in your discipline, please outline what type of metadata will be created and how F1. (meta)data are assigned a globally unique and eternally persistent identifier. F2. data are described with rich metadata. F3. (meta)data are registered or indexed in a searchable resource. F4. metadata specify the data identifier. 9

TYPICAL STRUCTURE OF A DMP: FAIR DATA - ACCESSIBLE /1 Which data produced and/or used in the project will be made openly available as the default? If certain datasets cannot be shared (or need to be shared under restrictions), explain why, clearly separating legal and contractual reasons from voluntary restrictions. How will the data be made accessible (e.g. by deposition in a repository)? What methods or software tools are needed to access the data? Is documentation about the software needed to access the data included?is it possible to include the relevant software (e.g. in open source code)? A1 (meta)data are retrievable by their identifier using a standardized communications protocol. A1.1 the protocol is open, free, and universally implementable. A1.2 the protocol allows for an authentication and authorization procedure, where necessary. A2 metadata are accessible, even when the data are no longer available. 10

TYPICAL STRUCTURE OF A DMP: FAIR DATA - ACCESSIBLE /2 Where will the data and associated metadata, documentation and code be deposited? Preference should be given to certified repositories which support open access where possible. Have you explored appropriate arrangements with the identified repository? If there are restrictions on use, how will access be provided? Is there a need for a data access committee? Are there well described conditions for access (i.e. a machine readable license)? How will the identity of the person accessing the data be ascertained? A1 (meta)data are retrievable by their identifier using a standardized communications protocol. A1.1 the protocol is open, free, and universally implementable. A1.2 the protocol allows for an authentication and authorization procedure, where necessary. A2 metadata are accessible, even when the data are no longer available. 11

TYPICAL STRUCTURE OF A DMP: FAIR DATA - INTEROPERABLE Are the data produced in the project interoperable, that is allowing data exchange and re-use between researchers, institutions, organizations, countries, etc.? What data and metadata vocabularies, standards or methodologies will you follow to make your data interoperable? Will you be using standard vocabularies for all data types present in your data set, to allow inter-disciplinary interoperability? I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles. I3. (meta)data include qualified references to other (meta)data. In case itis unavoidable that you use uncommon or generate project specific ontologies or vocabularies, will you provide mappings to more commonly used ontologies? 12

TYPICAL STRUCTURE OF A DMP: FAIR DATA - RE-USABLE How will the data be licensed to permit the widest re-use possible? When will the data be made available for re-use? If an embargo is sought to give time to publish or seek patents, specify why and how long this will apply, bearing in mind that research data should be made available as soon as possible. Are the data produced and/or used in the project useable by third parties, in particular after the end of the project? R1. meta(data) have a plurality of accurate and relevant attributes. R1.1. (meta)data are released with a clear and accessible data usage license. R1.2. (meta)data are associated with their provenance. R1.3. (meta)data meet domainrelevant community standards. If the re-use of some data is restricted, explain why. How long is it intended that the data remains re-usable? Are data quality assurance processes described? 13

TYPICAL STRUCTURE OF A DMP: ALLOCATION OF RESOURCES What are the costs for making data FAIR in your project? How will these be covered? Who will be responsible for data management in your project? Are the resources for long term preservation discussed? costs potential value who decides and how what data will be kept and for how long? 14

TYPICAL STRUCTURE OF A DMP: DATA SECURITY What provisions are in place for data security (including data recovery as well as secure storage and transfer of sensitive data)? Is the data safely stored in certified repositories for long term preservation and curation? 15

TYPICAL STRUCTURE OF A DMP: ETHICAL ASPECTS Are there any ethical or legal issues that can have an impact on data sharing? Is informed consent for data sharing and long term preservation included in questionnaires dealing with personal data? 16

TYPICAL STRUCTURE OF A DMP: OTHER ISSUES Do you make use of other national/funder/sectorial/departmental procedures for data management? If yes, which ones? 17

Except where otherwise noted, content on this site is licensed under a Creative Commons Attribution 4.0 International License. matthias.razum@fiz-karlsruhe.de Twitter: @RADAR_Service