[Esip-preserve] Fwd: [External] Re: [rda-datacitation-wg] RDA WGDC Paper summarizing adoption stories and lessons...

[Mark Parsons]

The “magnum opus” of dynamic data citation. 

-m.
Sent from my iPhone

Begin forwarded message:

> From: Umunshi via Data Citation WG <rda-datacitation-wg at rda-groups.org>
> Date: November 19, 2021 at 18:44:17 GMT+1
> To: rauber at ifs.tuwien.ac.at, Data Citation WG <rda-datacitation-wg at rda-groups.org>
> Subject: [External] Re: [rda-datacitation-wg] RDA WGDC Paper summarizing adoption stories and lessons...
> Reply-To: umunshi at gmail.com
> 
> 
> congratulations!
> 
> On Fri, 19 Nov 2021, 20:32 rauber via Data Citation WG, <rda-datacitation-wg at rda-groups.org> wrote:
>> Dear all,
>> 
>> I am very happy to inform you that the paper jointly written by many of 
>> the adopters of the recommendations on dynamic data citation has been 
>> published in the Hardvard Data Science Reviews:
>> 
>> 
>> Rauber, A., Gößwein, B., Zwölf, C. M., Schubert, C., Wörister, F., 
>> Duncan, J., … Parsons, M. A. (2021). Precisely and Persistently 
>> Identifying and Citing Arbitrary Subsets of Dynamic Data. Harvard Data 
>> Science Review, 3(4).
>> https://doi.org/10.1162/99608f92.be565013
>> 
>> https://hdsr.mitpress.mit.edu/pub/si7wzxxa/release/2?readingCollection=1ccd159a
>> 
>> (Abstract attached below)
>> 
>> It provides a summary of the recommendations, describes the reference 
>> implementations for different types of data and, most important of all, 
>> presents a number of implementations that have been deployed in various 
>> infrastructures. It is a kind of "opus magnum" for this WG, collecting a 
>> lot of the work done in one single report and shows how far we have come 
>> from the time when we have published the recommendations with some 
>> initial demonstrators, via proper reference implementations to 
>> infrastructures that have actually deployed them in practice and put 
>> them into full operation.
>> 
>> My thanks go, specifically, to all the WG members who have put trust 
>> into the recommendations and put up the effort to actually implement and 
>> deploy them - and contributed to this paper summarizing all the lessons 
>> learned so far - thank you so much!
>> 
>> I hope this paper is useful for other institutions who want to embark on 
>> implementing the recommendations, providing templates and points of 
>> reference. We will, of course, continue to support such adoptions - and 
>> we would be happy to learn more about other adoptions taking place 
>> collecting them, and sharing information about them - initially e.g. via 
>> our webinar series, and then maybe by a sequel to this paper. We have 
>> been a bit quite during the last plenaries as thse on-line meetings are 
>> not th emost efficient mechanisms for discussion, especially when a lot 
>> of these sessions are squeezed into a tight week. But we would be very 
>> happy to pick up the webinar series again if you have any adoption 
>> stories to share.
>> 
>> Best regards,
>> Andreas Rauber
>> 
>> ----------------------
>> Abstract:
>> Precisely identifying arbitrary subsets of data so that these can be 
>> reproduced is a daunting challenge in data-driven science, the more so 
>> if the underlying data source is dynamically evolving. Yet an increasing
>> number of settings exhibit exactly those characteristics. Larger amounts 
>> of data are being continuously ingested from a range of sources (be it
>> sensor values, online questionnaires, documents, etc.), with error 
>> correction and quality improvement processes adding to the dynamics. 
>> Yet, for studies to be reproducible, for decision-making to be 
>> transparent, and for meta studies to be performed conveniently, having a 
>> precise identification mechanism to reference, retrieve, and work with 
>> such data is essential. The Research Data Alliance (RDA) Working Group 
>> on Dynamic Data Citation has published 14 recommendations that are 
>> centered around time-stamping and versioning evolving data sources and 
>> identifying subsets dynamically via persistent identifiers that are 
>> assigned to the queries selecting the respective subsets. These 
>> principles are generic and work for virtually any kind of data. In the 
>> past few years numerous repositories around the globe have implemented 
>> these recommendations and deployed solutions. We provide an overview of 
>> the recommendations, reference implementations, and pilot systems 
>> deployed and then analyze lessons learned from these implementations. 
>> This article provides a basis for institutions and data stewards 
>> considering adding this functionality to their data systems.
>> 
>> --
>> Full post: 
>> https://www.rd-alliance.org/group/data-citation-wg/post/rda-wgdc-paper-summarizing-adoption-stories-and-lessons-learned
>> Manage my subscriptions: https://www.rd-alliance.org/mailinglist
>> Stop emails for this post: 
>> https://www.rd-alliance.org/mailinglist/unsubscribe/74761
> --
> Full post: https://www.rd-alliance.org/group/data-citation-wg/post/rda-wgdc-paper-summarizing-adoption-stories-and-lessons-learned
> Manage my subscriptions: https://www.rd-alliance.org/mailinglist
> Stop emails for this post: https://www.rd-alliance.org/mailinglist/unsubscribe/74761
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.esipfed.org/pipermail/esip-preserve/attachments/20211119/71e4c1df/attachment.htm>