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Our next Research IT Reading Group topic will be: Research Data Management - Service Launch, Th 8 October / noon / 200C Warren Hall.

When: Thursday, October 8th from noon - 1pm
Where: 200C Warren Hall, 2195 Hearst St (see building access instructions on parent page).
Event format: The reading group is a brown bag lunch (bring your own) with a short <20 min talk followed by ~40 min group discussion.

Presenters: Chris Hoffman, Jamie Wittenberg, Rick Jaffe, Research IT

The Research IT team will describe the recent launch of Research Data Management consulting ( and the RDM Guide (, an information resource pulling together existing services and best practices.  

Please review the following prior to our 10/8 meeting:

Chris Hoffman, Research IT
Jamie Wittenberg, Research IT & Library
Rick Jaffe, Research IT


Aaron Culich, Research IT
Aron Roberts, Research IT
Jason Christopher, Research IT
Jean Ferguson, Library
John Krantz, CDL
John Lowe, Research IT & Linguistics
Norm Cheng, TPO
Quinn Dombrowski, Research IT
Patrick Schmitz, Research IT
Perry Willett, CDL
Raymond Yee
Ronald Sprouse, Linguistics
Scott Peterson, Doe Library
Steve Masover, Research IT
Steven Carrier, School of Education



==> No 'regular' reading group 10/22, but all are invited to a debrief lunch in the BIDS space, discussing progress made by IT support organizations across the campus who will hold a CONSULTING PLANNING MEETING that morning on the topic of supporting researchers' information technology needs. We'll hear a bit about what discussion has occurred to-date and discuss topics related to improving research IT consultations across the campus, across domains of research and IT expertise, and across organizations with different missions and client-bases.

==> On 11/05 we'll have a topic whose formal title is still TBA, but the general subject area will have to do with computational research on data sets that require secure environments for data storage, data transfer, and or computation.


Presentation (Chris, Jamie, Rick)

cf. slide deck (PDF)

o Intro to RDM program; reference to Town Hall (cf. Research IT news article for video and slide deck: Town Hall spotlights new services for researchers, Savio expansion)
o -- RDM Service Guide -- site still in development
o -- RDM consulting service -- a campus-wide expert network -- office hours (Library Data Lab, D-Lab, BIDS)
o RDM view from Berkeley: training, support, resources, & consultation at the core of the program
o RDM service guide: a brokerage service to providers on and off campus
o Seeking feedback on the service guide -- what's missing? more case studies to illustrate campus researcher needs? A 'living' set of documents, will change as researcher needs change
o about 12 inquiries since 9/21 launch of consulting service; consultant network includes Librarians, CSS-IT, et al. Mostly about storage and backup to-date.
o Several examples already of collaborative referrals across RDM, BRC, SCF -- data storage, data transfer, backup of research and bibliographical data, computation "bigger than laptop"
o in general: researchers are happy and relieved to have some help, someone with whom to consult -- and we expect and hope that will lead to further word-of-mouth referrals as word spreads among the research community that the RDM resources are available
o RDM Program is very interested in working directly with partners and researchers!
o Early December workshop is likely -- more detailed / hands on demos than the March workshop.

Aaron C: Are incoming inquiries more mechanistic or do researchers come in with a bigger-picture perspective.
Chris H: They tend to start out mechanistically, but lead in fairly short order to deeper engagement.
Patrick S: As we talk about scaling out consulting, we are interested in producing written materials that help researchers DIY. Is this something you see working in RDM space?
Jamie W: We have had requests of this sort already, e.g., a HowTo about making data public, archiving it, associating it with their dissertation, etc.
Rick: That sort of thing answers mechanistic questions, but a little initial intake, reflection on questions

Perry W: Where should I put my data, what are characteristics of an appropriate repository?
Jamie W: Library expertise, reference interviews, are likely the key to eliciting specifics that lead to a workable answer to that sort of very general question.
Raymond Y: Conversations with Sponsored Project Office? DMPs, how well researchers are executing on the plans written into their funding proposals?
Chris H: We're having those conversations, they continue. Audit on data management ongoing on the campus now, first ever. In conversation with VCRO to get access to some of the DMPs being written on campus so we can assess what's being promised, how we can help to support execution.
Patrick S: Some other campuses have gotten their SPO offices (or similar) to include checkboxes in process of filing grants that indicate whether reearch computation or research data management issues are a part of the proposed research.
Quinn D: In DH, we end up with some very complexly heterogeneous data sets -- e.g., music associated to documentation of dance performances to that music ... would going down routes this fuzzy be something that RDM is able/willing to grapple with
Chris H: Deliberately keeping definition quite open. We're very interested in diverse use cases to see what commonalities (sometimes quite unexpected) we might find and profit from.
Patrick S: Is some of this around the data management, or around metadata management?
Quinn D: Researchers are thinking about both. Complex taxonomies that have proven brittle in actual use; but also how to store/maintain for future access.
Patrick S: These may well prove to be similar to concerns in other domains. Everybody has format problems, software version problems, preservation of software problems (which is a very old and familiar problem -- not solved, but well-trodden ground)

Topics/Tools/Demos for (tentatively scheduled) December RDM Workshop?
o DMP tool?
o How to choose a repository: case study, break down that question
o Identify communities that have more-or-less decided how/where to store domain-specific data sets -- recommendations reflective of a specific discipline's tools and workflow/practices
o Practices regarding how archived data is/can/can't be shared for further examination/research
o Risk of losing control -- accidental sharing of data
o Upfront curation -- people think it's not worth the work -- but then you get an accumulated debt re: deciding much later what do with accumulated data
... when data that is archived becomes valuable (or loses value)



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