[Kathleen Gregory]

Collaborative session notes: https://docs.google.com/document/d/1IalqtclDzVRkYB63HQkTAofxymT_3S_2TSZi7y7E1gg/edit?usp=sharing
 

Introduction of the group (10 minutes)

Discussion on short-term activities on the open topics (60 minutes)

Metadata enrichment for discovery, for example, using upper-level ontologies

Possible introductory talk: Mingfang Wu

Suggested scope:

Identify existing resources, their purposes, problems that they are designed to address, domains where used, examples of successful application. 

Challenges or difficulties, e.g. in applying specific controlled vocabularies or upper-level ontologies

Potential tasks:

Identify existing surveys that could be used as input

Might require the design of a new survey, tailored to the particular questions

Expected outcomes of the session discussion:

Agreement on Scope

Discuss possible tasks

Potential leads

Machine learning for data discovery, for example, topic modelling

Possible introductory talk: 

Suggested scope:

Doing a landscape of ML solutions, either a survey of repositories or document/literature review, from perspectives (taking into consideration all stakeholders, i.e. researchers, librarians, citizen scientists, etc) / activities / efforts that are assisting / facilitating Data Discovery. Based on the landscape, identify best practices across multiple domains

Examination of how ML models trained for data discovery can be described and shared.

How to ensure that repositories can facilitate ML-based workflows while avoiding potential biases (resulting from only certain subsets of relevant data being discovered).

Facilitate (semi-)automated processes (e.g. recommendation) in repositories for identifying items of interest from user perspective.  

Potential tasks:

Landscape performed as a literature review, and/or a survey of repositories

A best-practices document, that can be consequently transformed into a recommendations document.

Expected outcomes of the session discussion:

Agreement on Scope

Discuss possible tasks

Potential leads

User study / meta-research/analysis of data discovery interviews 

Possible introductory talk: Kathleen 

Suggested scope:

Revisit the prior efforts on user study interviews/surveys 

Meta analysis / research of the efforts.

Potential tasks:

Organize a series of presentations of existing efforts.

Create a list capturing all the existing/past/ongoing efforts

Expected outcomes of the session discussion:

Agreement on Scope

Discuss possible tasks

Potential leads

Next steps and wrap up (20 minutes)

Additional links to informative material
The group has delivered the following three supporting outputs: 

Eleven quick tips for finding research data
 

Data discovery paradigms: user requirements and recommendations for data repositories
 

A survey of current practices in data search services
 

Slides from previous plenary sessions: 

January 2021 – RDA Virtual Plenary 17:

Investigating data discovery across domains (Group session, slides)

November 2020 – RDA Virtual Plenary 16:

What information about data do users desire for discovery? (Group session, slides)

 

April 2020 – RDA Virtual Plenary 15:

Inferring data searchers’ intent and their interaction with data discovery systems (group session)
 

Data Granularity BoF; user perspectives, data citation and data versioning (BoF session)

Oct. 2019 (P14) – Data Discovery Paradigms IG: Reports from Task Forces and Way Ahead (slides)

April 2019 (P13): Data Discovery Paradigms IG: Reports from Task Forces and Way Ahead (slides)

Oct. 2018 – RDA Plenary 12; IG meets, Task Forces report back

March 2018 — RDA Plenary 11; IG meets, Task Forces report back

Slides from earlier plenaries are available from the group page.

Applicable Pathways
The FAIR Agenda, Data Infrastructures – Organisational to Environments

Avoid conflict with the following group (1)
Data Versioning IG

Brief introduction describing the activities and scope of the group
The objective of this IG is to provide a forum where representatives from across the spectrum of stakeholders and roles pertaining to data discovery can work together to identify, study and make recommendations concerning issues related to improving data discovery. The goal is to produce concrete deliverables that will be recognised and valued by the research and data communities.
This group was officially endorsed at RDA P9. The group has worked on the following task forces, namely:

User study in data discovery (ongoing)

Data/Metadata granularity (ongoing, a BoF has been submitted)

Using schema.org for research dataset discovery (This task force has spun off to the Research Metadata Schemas Working Group, which was endorsed in Sept. 2019).
 

Initial four task forces from the group:

Relevancy ranking (completed)
 

Use cases, prototyping tools and test collections (completed)
 

Best practice for making data findable (completed)
 

Metadata enrichment (closed)

Group chair serving as contact person
Kathleen Gregory

Meeting objectives

To update the group progress

To discuss new task forces

Please indicate the breakout slot (s) that would suit your meeting
Breakout 16, Breakout 19, Breakout 22

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