WP3: Common policies and implementation strategies Parthenos Prato– 14/12/2016 Hella Hollander KNAW-DANS

WP3 1. Vision and Approach on Common Policies 2. Fair Principles 3. Parthenos Wizard 4. Questions

1. Commom Policies Parthenos WP3– Rome– 14/11/2016 Hella Hollander KNAW-DANS

The PARTHENOS VISION – Common Policies Challenge Goal is to agree on and define the concepts of Policy, Guidelines, Best practice, their objectives and target audience How are humanities repositories assessed? How to create assessment ‘profile’ for humanities? How to comply with it? How to coordinate reviews? What quality of (meta)data is desired? How can it be measured? Task objectives 4

Objectives Real objective Project objective Task objectives Enable research questions to be answered More & better! Make research data available More & better! Provide policy and guidelines for repository, data and metadata. Conduct foresight studies

PARTHENOS FLAGSHIP EXPECTED RESULTS Guidelines on data management Produce a coherent, authoritative, well accepted set of policies/guidelines/tools concerning the management of data lifecycle and related issues such as IPR, quality and so on Standardization and semantics Produce a wide set of standards and semantics, originated from community needs and tailored to the methodology and intended use by researchers Services and tools Produce a coherent set of tools for carrying out research using and re-using data

The PARTHENOS VISION – Common Policies Focus Approach WP3 The results of the effort of Work Package 3 should have a long-term impact on common policies and guidelines on research data management, IPR, Open Access and Open data and how to implement them within the Humanities. WP2 and WP3 work on an inventory of existing policies from the different infrastructures, and will define and test requirements for shared policies. D3.1 represents the result of desk research and theoretical background giving guidelines and case studies to the researchers. The outcomes of this deliverable could be made more useful and reusable by creating an interactive guide (web page) to present the results.

Common Vision WP3 Help researchers to make their data of better quality, interoperable, sharable, findable and reusable (FAIR principles) Agree on and define what policies, guidelines and best practice are. Overview of existing policies in the Parthenos disciplines, for different data lifecycle phases Find the commonalities between disciplines in the humanities in terms of policies, RDM and IPR, open access Find the gaps: what disciplines are advanced in terms of policies and what are not Give recommendation and guidance to researchers Give recommendation and guidance to data archives Give guidance and recommendations to cultural heritage institutions

Approach Deliverable as a shared product of WP3 Deliverable: Text and Wizard Matrixes and Chapters: New content on policies and best practices: Receive input via working groups Wizard: What does it bring for Parthenos? A clear picture FAIR principles into Deliverable: connecting backbone

2. FAIR principles

Open and FAIR Data in Trusted Data Repositories Data does not only need to be Open Data must also be FAIR Findable, Accessible, Interoperable, Reusable And must remains so, and therefore should be preserved in a DSA Certified Trusted Digital Repository

International standards and guidelines Certificats 3 standards 3 levels http://www.trusteddigitalrepository.eu

What is FAIR? FAIR principles for data quality, DSA criteria for quality of TDR minimal set of community agreed guiding principles to make data more easily discoverable, accessible, appropriately integrated and re-usable, and adequately citable. A perfect couple for quality assessment of research data and trustworthy data repositories Ideally: a DSA certified archive will contain FAIR data

FAIR Data Principles In the FAIR Data approach, data should be: Findable – Easy to find by both humans and computer systems and based on mandatory description of the metadata that allow the discovery of interesting datasets; Accessible – Stored for long term such that they can be easily accessed and/or downloaded with well-defined license and access conditions (Open Access when possible), whether at the level of metadata, or at the level of the actual data content; Interoperable – Ready to be combined with other datasets by humans as well as computer systems; Reusable – Ready to be used for future research and to be processed further using computational methods.

Implementing FAIR Principles 15 Criteria

Combine and operationalize Growing demand for quality criteria for research datasets Combine the ideas of DSA and FAIR Use the principles as quality criteria: DSA – digital repositories FAIR – research data (sets) Operationalize the principles to make them easily implementable in any trustworthy digital repository

Findable - defined by metadata, documentation (and identifier for citation): No URI or PID and no documentation PID without or with insufficient metadata Metadata without PID PID with limited metadata, just enough to understand the data Extensive metadata and rich additional documentation available Accessible - defined by presence of a user license; [metadata retrievable by identifier: already included under F] No user license / unclear conditions of reuse / metadata nor data are accessible Metadata are accessible (even when the data are not or no longer available) User restrictions apply (of any kind, including privacy, commercial interests, embargo period, etc.) Public access (after registration) Open Access (unrestricted)

Interoperable - defined by the data format; modified version of Tim Berners- Lee’s 5-star open data plan: Proprietary, non-open format data Proprietary format, accepted by Certified Trusted Data Repository Non-proprietary, open format (= “archival format”) Data is additionally harmonized/standardized, using standard vocabulary Data is additionally linked to other data to provide context Reusable - the most difficult dimension (partly subjective); aspects: 1. Clear provenance of data (to facilitate both replication and reuse) 2. Data is in a TDR – unsustained data will not remain usable 3. Explication on how data was or can be used is available 4. Data automatically usable by machines 5. Data is reliable (replicable)

Ranking Quality of Data

FAIR as the backbone principles PARTHENOS High level principle: FINDABLE - Defined by metadata, documentation (and identifier for citation) Connected part in the Use CASE: Indy is looking for best practices and common policies within the archaeological community. She finds policies about data creation from serveral countries that makes her data findable. Mappings to backbone FAIR principle like this: Fair principle: Findable DSA principle: the data can be found on the Internet Matrix WP3: Data Creation of the UKDA data lifecycle Policies: Best practices ADS, DANS preferred formats guide (examples) Standards SSK toolkit : WP4 Training HTML page: WP7

3. Parthenos Wizard

Parthenos Wizard: the design process

Parthenos Wizard

Parthenos Wizard Not just a deliverable, we want something that our stakeholders can use, an instrument that can guide them trough the jungle of research policies! Idea discussed and approved in Krakow, first results discussed in Rome. We could create an interactive guideline where our users can find information about the policies that best adapt to their use case We can include not only the research outputs of WP3 but also WP4 and WP7 and integrate this with the datamodel and infrastructure of Parthenos via WP5/6.

Parthenos Wizard: latest developments Technically, it is developing as a widget in the Parthenos website: something very simple and sustainable Intra-WPs task including WP2, WP3, WP4, WP5/6, WP7 (regular meetings) Connect these policies through the FAIR principles of data quality We want to start with a proof of concept that will serve the others to see how the wizard can be developed

Parthenos Wizard: the technical solution The wizard (widget) will be integrated in the Parthenos website Take the information of the T.3.2. Matrix via API Displays the information on the selected policies in the wizard

Hella Hollander DANS-KNAW 4. Questions Hella Hollander DANS-KNAW Hella.Hollander@dans.knaw.nl PARTHENOS is a Horizon 2020 project funded by the European Commission. The views and opinions expressed in this publication are the sole responsibility of the author and do not necessarily reflect the views of the European Commission.