Status: Recognised & Endorsed
The Metadata IG will concern itself with all aspects of metadata for research data. In particular it will attempt to coordinate the efforts of the WGs concerned with metadata to produce a coherent approach to metadata covering metadata modalities of description, restriction, navigation, provenance, preservation and the use of metadata for the purposes discovery, contextualisation, validation, analytical processing, simulation, visualisation and interoperation. It will also liaise with the other WGs especially Data Foundation and Terminology, PIDs, Standardisation of data categories and codes and Data Citation. This IG activity relates to data management policies and plans of research organisations and researchers, and to policies and standards of research funders and of research communities which may or may not be official standards.
The metadata IG will organise itself through online meetings and face-to-face meetings of members of the IG present at RDA Plenary events. It is proposed that – while membership is open to any RDA registered member – key members will be the leaders of the WGs concerned with metadata. In order to get the renovated IG working I volunteer to initiate this activity but would expect elections and handover to someone else after an initial period.
Metadata Principles - Created and endorsed by all the RDA metadata groups
- The only difference between metadata and data is mode of use
- Metadata is not just for data, it is also for users, software services, computing resources
- Metadata is not just for description and discovery; it is also for contextualisation (relevance, quality, restrictions (rights, costs)) and for coupling users, software and computing resources to data (to provide a VRE)
- Metadata must be machine-understandable as well as human understandable for autonomicity (formalism)
- Management (meta)data is also relevant (research proposal, funding, project information, research outputs, outcomes, impact…)
RDA Plenary 9 Barcelona Breakout 3 - 16:00 Joint session of IG Metadata, WG Metadata Standards Catalog, IG Data in Context
The focus of the joint meeting of the Metadata Groups was the Metadata Standards Catalog and the activity to develop a standard canonical set of metadata elements.
The Metadata Standards Catalog Working Group (MSCWG) is working on the next generation of the RDA Metadata Standards Directory,[ and is scheduled to deliver the new Catalog in mid-2017. Alex Ball explained how the group is evolving and migrating the data from one to the other, and gave a demonstration of the current version of the Catalog. Among the improvements are a dynamic search interface, a richer subject classification, and an API for automated access. A transcript of the demonstration is available on the MSCWG wiki.
The Metadata Interest Group has been developing a set of metadata elements over the past few plenaries. The set of metadata elements is intended to specify the information that systems need in order to satisfy the use cases collected by the Data in Context Interest Group. This set could be used to characterize existing metadata schemes and facilitate mappings among them. By Plenary 8, the group had identified 17 high-level elements. Keith Jeffery explained that the next step was to 'unpack' these general elements, and produce lists of sub-elements that more closely resemble how the elements might be represented in a real metadata scheme. He demonstrated by providing a decomposition of spatial coordinates. Rebecca Koskela then led the group in tackling the rest of the list; the results of the activity can be viewed on Google Docs. These initial lists will be refined over the course of the next six months in a series of teleconferences. If you would like to be involved, please check the Metadata Interest Group mailing list for details of when and how to join the calls.
Metadata Standards Directory:
The RDA Metadata Standards Directory Working Group supports a collaborative, open directory of metadata standards applicable to scientific data. Additions or updates to the directory can be made here.
Metadata Element Set:
The metadata groups intend to recommend the following metadata element set. Please note that each element needs 'unpacking' to get to something recognizable and actionable by a computer.
- Unique Identifier (for later use including citation)
- Location (URL)
- Keywords (terms)
- Temporal coordinates
- Spatial coordinates
- Originator (organisation(s) / person(s))
- Facility / equipment
- Availability (licence, persistence)
- Related publications (white or grey)
- Related software
- Medium / format
As noted above, these are elements, not single-valued attributes. Most will have internal syntax (structure) and use of terms that require declared semantics. Also it is not exhaustive; it is expected that particular subject domains will have much greater lists of elements. This list is intended to be the recommend list of elements that should be provided by all within RDA to
- permit discovery,
- support contextualisation (assessment of relevance and value) and
- facilitate action (interoperation including query and integration).
Use Case Analysis:
The initial use case Analysis was presented in Session 9 joint meeting of all the metadata groups at Plenary 6 in Paris. Below are some revised slides based on the feedback from that meeting and the master use case spreadsheet showing the process.
The FAIR Guiding Principles for scientific data management and stewardship have been published
Press release: FAIR guiding principles published in Nature journal
Today, March 15 2016, the FAIR Guiding Principles for scientific data management and stewardship were formally published in the Nature Publishing Group journal Scientific Data. The problem the FAIR Principles address is the lack of widely shared, clearly articulated, and broadly applicable best practices around the publication of scientific data. While the history of scholarly publication in journals is long and well established, the same cannot be said of formal data publication. Yet, data could be considered the primary output of scientific research, and its publication and reuse is necessary to ensure validity, reproducibility, and to drive further discoveries. The FAIR Principles address these needs by providing a precise and measurable set of qualities a good data publication should exhibit - qualities that ensure that the data is Findable, Accessible, Interoperable, and Reusable (FAIR).
- 2016-09-15 - 2016-09-17 RDA Plenary 8 Denver
- 2016-03--01 - 2016-03-03 RDA Plenary 7 Tokyo
- 2015-09-23 - 2015-09-25 RDA Plenary 6 Paris
- 2015-03-08 - 2015-03-11 RDA Plenary 5 San Diego
- 2014-09-22 - 2014-09-24 RDA Plenary 4 Amsterdam
- 2014-03-26 - 2014-03-28 RDA Plenary 3 Dublin
- 2014-02-24 - 2014-02-25 RDA Europe Munich Meeting