Making sense of Interest Group/Working Group Activity by
RDA Technical Advisory Board
Beth PlaleProfessor of Data Science
Indiana University USA
With special thanks to RDA/US Fellow Nic Weber
• Beth Plale, co-chair (US)
• Andrew Treloar, co-chair (Australia)
• Bridget Almas (US)
• Carole Palmer (US)
• Chuang Liu (China)
• Francoise Genova (France)
Technical Advisory Board MembersTAB is an elected body
• Jamie Shiers (Switzerland)
• Peter Fox (US)
• Peter Wittenburg (Germany)
• Rainer Stotzka (Germany)
• Simon Cox (Australia)
• Susanna-Assunta Sansone (UK)
TAB: what it does
• Case statement review: Reviews and guides case statement creation
• Liaison: Engages and supports IG/WG activity. Host plenary IG/WG Chairs meetings. Each IG/WG has liaison. Cross group coordination.
• Plenary planning : with eye towards minimizing overlap and quality proposals
• Socio-technical vision and strategy: technical scope of RDA, issues of productivity: – e.g., 30% are Working Groups and 70% are Interest Groups. Is
that right/good balance?
RDA P6: 60 working groups and interest groups
60 WGs and IGs is a lot of activity.
How can newcomer possibly make sense of RDA?
Conceptualizing RDA Activity through Clustering: A Brief History
• RDA TAB undertook effort begun in 2014 under lead of TAB co-Chair Dr. B. Plale to better illuminate collective activity of RDA
• Sources of information influencing– Analysis of WG/IG stated objectives and other
information – Numerous discussions with WG/IG chairs and
community– Multiple earlier versions of clustering, none of which
quite worked (comprehensive, illuminating)
Clustering Purpose• Guide newcomers find products in progress of
interest, and groups to which they can contribute
• Help externals see scope of solution space of RDA
• Guide RDA members in gaps and overlaps• Help TAB in guidance and evaluation of
existing and new groups
Clustering along two dimensions
• Beneficiary dimension: spectrum from data provider to data consumer – Primary beneficiary is data provider (or act of data
provisioning) at one end of spectrum or data consumer at other end of spectrum
• Solution dimension: spectrum from technical to social/organizational– Solution manifests itself most strongly as software or
infrastructure (technical) on one hand; or as policy, organizational, governance, educational, or community building (social) on other
Technical solution aimed at data provider
Technical solution aimed at data consumer
Social/organizational solution aimed at data
consumer
Social/organizational solution aimed at data
provider
Placing activity on grid
• Self identification/positioning by WG/IG chairs• Activity is represented as single point in grid
space labeled by (0, 100) in each dimension• Following graphs are for those WG/IGs that
have responded to inquiries so far (about 50% have responded)
Social/organizational + data consumer
Technical + Data Consumer
Technical + Data Provider
Social/organizational + Data Provider
Terms to further describe• Use of terms to further describe activity of
WG/IG • Terms drawn from Data Practices and Curation
Vocabulary (DPCVocab) but not limited to
For 34 groups who have replied with their info. Location: Q1: UR, Q2: LR, Q3: LL, Q4: UR. Color coded by quadrant and WGs in dark
Term Assignment. Orange: social/consumer; Blue: technical/consumer. Terms chosen by group to describe activity more precisely than name alone.
Larger version of full list of term assignment to date.
Summary• Clustering has exposed relatively equal
representation of WG/IG activity in each category • WG activity more heavily concentrated in technical
dimension. TAB discussing solutions to stimulate WG activity on social/organizational dimension
• RDA/US Fellow: Building clustering into new web-enabled tool to explore RDA activity for RDA site
• RDA/US Fellow: gather additional information to study RDA (WG/IG engagement: e.g., profiles of those engaged based on organizational affiliation)
• Whitepaper in preparation on clustering