Data Granularity WG Case Statement
The latest version of the Case Statement from July 2021 has been endorsed by the RDA Council. This latest version, version 2, was submitted in July 2021. Version 1 underwent community review in February / March 2021 and was reviewed by TAB.
The Data Granularity Task Force of the Data Discovery Paradigms Interest Group (DDPIG) of the Research Data Alliance (RDA) proposes to form an RDA Data Granularity Working Group (WG). This WG would address issues of data granularity in data discovery, access, interoperability, analysis, citation, and more. More efficient and effective reuse of data requires that users can find and access data at various levels of granularity. The WG will explore key questions and collect and share valuable information for how to best support data granularity, providing guidance to help data professionals to determine the best level of granularity for user discovery, access, interoperability and citability.
The activities and final recommendations of the Data Granularity WG will build upon and complement existing and ongoing work of several RDA Working and Interest Groups that touch upon the subject of data granularity. The final deliverable for the WG is a set of collected use cases and a guidance document of data granularity approaches for prioritized use cases, including terminology, methods to evaluate approaches, and a summary of community feedback.
| Attachment | Size |
|---|---|
 Case Statement_ RDA Data Granularity Working Group Version 1.pdf | 145.59 KB |
| Case Statement_ RDA Data Granularity Working Group Version 2.pdf | 178.02 KB |
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Author: Karen Payne
Date: 09 Feb, 2021
Looking forward to the WG synthesizing the relevant WG and IG listed in the appendix.
Author: Chris Little
Date: 10 Feb, 2021
In the case statement " When granularity is too low, users have to download a great number of datasets and try to fit them together ..." has the opposite definition of what I expected. this is not just me. See https://en.wikipedia.org/wiki/Granularity#Precision_and_ambiguity .
Rather than 'high' and 'low', I suggest using 'fine-grained' and 'coarse-grained'.
Author: Alessandro Sarretta
Date: 04 Mar, 2021
I do support this comment: I was a bit confused reading in the document how high/low granularity are used as opposite meaning compared to what I was expecting. Fine/coarse granularity would serve better the purpose.
Author: Tanja Friedrich
Date: 11 Feb, 2021
Hello all, this case statement looks very good! I have a minor comment regarding the wording; have you considered speaking of "data reuse" and "data reusers" instead of "secondary data use" and "secondary data users"? There may be pros and cons for both alternatives. Best wishes,
Tanja
Author: Amy Nurnberger
Date: 18 Feb, 2021
It would be wonderful to see some stronger links between this proposed work and organisations who might put it to use. I think there is a lot of potential for organisational use cases to inform the devleopment of this. It would be great to understand early on how these "guidelines and best practices for capturing data granularity," might be best used by the organisations that will implement them.