fairfying data guidelines to digital humanities easy guide
TRANSCRIPT
Colour vision, Paul Grigg, Wellcome Collection, United Kingdom, CC BY
GUIDELINES to FAIRfying dataEasy guide for GLAMs and researchers in the Digital Humanities
Franco Niccolucci, PINSara Di Giorgio, ICCU
HOUSEKEEPINGPlease make sure your microphone is muted when you don’t speak - Thank you!
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SPEAKERSSara Di Giorgio, Project Manager ICCU, Cultura Italia
Franco Niccolucci, director of the VAST-LAB laboratory at PIN, Prato, Italy
Rob Davies - Europeana Common Culture, Cyprus Institute of Technology
Henning Scholz - Data Publishing Services, Europeana
FAIR DATA PRINCIPLES
The FAIR data principles concern data organization. They aim at improving data discovery, access and re-use by humans and directly by computational systems with little or no human intervention - the so-called machine-actionability.The principles focus on four aspects: Findability, Accessibility, Interoperability and Re-usability.
ORIGINS OF FAIR● The FAIR principles originate from a workshop held in Leiden
in 2014 and from previous discussions on open science● A 2016 paper published by a large grouping of scientists
formulated them in a precise and formal way● Supported by the EU Commission● Implemented through the recommendations of international
projects and organizations like RDA
https://www.force11.org/ G8 Science Ministers Statement (2013) Guidelines on FAIR data management
WHY FAIR DATA? The FAIR data principles are about data stewardship and re-use● Open Science: foster collaboration
& cross-fertilization● Saving money: 10 000 M€/year● Saving time: no double work, 80%
time spent in searching data● Machine-actionability● Widely adopted: UNESCO, G7, EU,
national governments (DE, NL, FR), LIBER, ...
Image by OpenAire
WHY GOING FAIR? Adopting the FAIR principles has many benefits for researchers:● Encouraging scientific enquiry and debate● Promoting innovation and potential new data uses● Fostering new collaborations between data users and data creators● Maximising transparency and accountability● Enabling scrutiny of research methods and findings● Reducing the cost of duplicating data collection● Increasing the impact and visibility of research● Getting credit for research outputs● Increase citation rates ● Last but not least, it is mandatory for many funders
https://zenodo.org/record/2668479#.XsfJiWgzZPY
PARTHENOS GUIDELINES 20 GUIDELINES TO FAIRify DATA MANAGEMENT AND MAKE DATA REUSABLE
PREREQUISITEINVEST IN PEOPLE AND INFRASTRUCTURE
● Best practices● Training● Implementation of technical infrastructures
How to make data FINDABLE?
● Use persistent identifiers (IDs)● Cite research data● Use persistent author identifiers (IDs) ● Use a standardized metadata schema
Guidelines - FINDABLE Focus: Metadata Schema and Identifiers. Humanists work with a variety of sources (from archives, museums, or surveys) and each of them requires a specific metadata standard;
Main message: make use of the right fields to describe the right research object;
Identifiers also play an essential role for the humanities: they need to be as unique and persistent as possible.
How to make data ACCESSIBLE?● Choose a trustworthy repository● Clearly state accessibility● Use a data embargo when needed● Use standardised exchange protocols
Guidelines - ACCESSIBLEFocus: where the researcher’s data are stored (trustworthy), how they can be retrieved (protocols), and stating if and how much they are accessible;
Main message: your research (meta)data can be as standardized as possible, but if they can’t be accessed, they cannot be consulted and cited, reused, etc.
Access does not mean Open Access: the rule is “As open as possible, as closed as necessary”
How to make data INTEROPERABLE?● Establish well documented APIs● Use open, well-defined vocabularies● Document metadata models● Use community data standards● Enhance data quality● Use future-proof file formats
Guidelines - INTEROPERABLE
Focus: making the researcher’s data able to dialogue with other (researchers’) data;
Main message: use of standards, vocabularies/ ontologies, APIs, support the researchers who want to connect their data with other data and enable machine-actionable interoperability
How to make data REUSABLE?
● Document data● Follow naming conventions● Use common file formats● Maintain data integrity● Use licence that allow reuse
Guidelines - REUSABLE
Focus:being able to integrate other researchers’ data into your own research and vice versa;
Main message: not only data, but also their documentation and reuse licences are important. Humanities data are all about interpretation, but aim to the higher data integration.
PARTHENOS GUIDELINESThe PARTHENOS high-level guides offer common guidelines to build bridges between different - although tightly interrelated - fields and stakeholders within the Cultural heritage and the Humanities sectors by the harmonization of policy definition and their implementation.
PARTHENOS is an FP7 project funded by the European Commission. It provided integrated facilities and resources concerning all aspects of data management for the Humanities and Cultural Heritage
https://zenodo.org/record/2668479#.XsfJiWgzZPY
PARTHENOS GUIDELINES
The PARTHENOS Guidelines are also available in French, German, Greek, Hungarian and Italian.
If you want to learn more visit PARTHENOS Training modules at http://training.parthenos-project.eu/sample-page/manage-improve-and-open-up-your-research-and
-data/
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Thank you!
Franco Niccolucci, PIN [email protected]
Sara Di Giorgio, ICCU [email protected]