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Love Your Data Week, February 8-12, 2016

e-Science Portal blog - Thu, 02/04/2016 - 14:27

In case you didn’t know, next week is Love Your Data week. It is a good chance for you to learn more about data and data management, or to spread the word about your library services related to data. Follow #LYD16 on Facebook or Twitter to see what other libraries are doing. And there is a Love Your Data 2016 pinterest board.

From the website:  “Love Your Data (LYD) week is a social media event coordinated by research data specialists, mostly working in academic and research libraries. LYD is designed to raise awareness about research data management, sharing, and preservation along with the support and resources available at your college or university. We believe research data are the foundation of the scholarly record and crucial for advancing our knowledge of the world around us. If you care about research data, please join us! This campaign is open to any institution – small, large, research intensive or not, so please feel free to share, adapt, and improve upon it.
Each day will have a theme driving the event. We will share daily tips and tricks for managing research data, stories (both success and horror!), examples, resources, and point you to experts on your campus or in your discipline. All we ask in return is that you share your own experiences and results from the daily activities to keep the conversation lively.”




On Adding Data to Our Collections

e-Science Portal blog - Wed, 02/03/2016 - 00:26

Submitted by Amanda L. Whitmire, Head Librarian & Bibliographer, Miller Library, Hopkins Marine Station, Stanford University

I used to have the luxury of being “just” a data services specialist at Oregon State University Libraries. In one way or another, all of my job duties were related to data management and curation. I liked this situation because data is something that I’m very comfortable with. Before I joined the library, I had been collecting it, creating it and working with it for well over a decade. Since January 2016 however, I have been in the position of overseeing an entire library. It’s a small, marine science branch library, but still – the scope of my duties has drastically changed.

“Dr., do you have any data to add to the IR?” The Librarian and her faculty, in the manner of The Life Aquatic.

This shift has prompted me to contemplate the circumstances of the many other academic librarians for whom data services are only a part of their duties. It’s forced me to scrutinize just how many ways I can possibly justify bringing data into the scope of my new responsibilities. Within this new context, I’m proposing to take a broader perspective on collection development. We all say that, “data is a kind of information,” right? So why not develop our collections to include datasets, as well? In my world, datasets truly are first-class citizens that deserve respect, consideration,  and care in digitization, cataloging, and preservation. Right? RIGHT?

A different kind of collection development.

So, I wondered, “Is there data already in the library that we could add to our collections?” Here in the Miller Library, the answer to that question is a resounding, “YES!” This place is FULL of data-related treasure. Researchers at the Hopkins Marine Station have been collecting field data since the early 1900s, and some of the original log books are sitting 30 feet from my office in the special collections room. Are those datasets something that I could digitize, make actionable, and add to the collection? You bet!

Sifting through our collections looking for data is, for me, a way to stay in touch with data (my Precious!) and to familiarize myself with the research history of the marine station. It’s also an excuse to think creatively about how I approach collection development (since it’s all new to me anyway, why not?!).  Treating this historical data as an important and timely resource also gives me a way to demonstrate to the Hopkins faculty, research staff, post docs and graduate students that their data is likely to have value beyond their original intent in collecting it, and also well beyond the time frame during which they alone could benefit from using it.

So, if you’re a librarian who’s looking for more ways to bring data into your life, consider going on a hunt for legacy datasets. They’re out there. They’re out there everywhere. And they need a good librarian to bring them back out into the light. Get to it. Have courage, and report back.

Notebooks full of hand-written, coastal oceanographic observations, dating back to the early 1930s. Just hanging out in the Miller Library special collections room. In a cardboard box. On the bottom shelf. Whatevs.

Job opportunity: Tenure-Track STEM Librarian – Salem State University

e-Science Portal blog - Tue, 02/02/2016 - 12:14

Salem State University in Salem, MA has an opening for a Tenure-Track STEM Librarian. Please see the posting for a complete description of the position: https://careers-salemstate.icims.com/jobs/1637/tenure-track%2c-stem-librarian/job

Data Literacy for High School Students

e-Science Portal blog - Fri, 01/29/2016 - 09:11

I am very fortunate to be a part of the research team of an IMLS funded project examining data literacy in High Schools and possible roles for school librarians in developing educational programming on data literacy.  This two year program is being led by my colleagues Kristin Fontichiaro, Clinical Assistant Professor at the University of Michigan’s School of Information, and Jo Angela Oehrli, Learning Librarian at the UM Library. Some of the products of this project will be online conferences for school librarians and a handbook to help librarians and others consider and craft educational programing on data literacy.

As someone who generally works primarily with graduate students, I don’t get a lot of exposure to what the expectations are for high school students around data literacy. In the interviews we conducted with graduate students in the Data Information Literacy project they indicated that their data management skills were primarily self-taught. Although I don’t see High School students needing to learn how to manage and curate research data sets necessarily, I am interested in how students could be better prepared for assuming these types of responsibilities as they progress in the education.

Earlier this month I participated in a three day, all-hands meeting for the project where we discussed aspects of data literacy and contemplated possible directions to support High School education. The meetings were intense and wide ranging, but I want to share a few items of that I found particularly interesting.

How much do you need to know to teach data? Many librarians do not have a background in the sciences or math (myself included) which could make teaching data literacy topics intimidating. However statistics and data are not math, or at least there are aspects of data literacy that transcend math, that students need to know and librarians are potentially well suited to teach.  Applying data in arguments effectively and ethically and being an intelligent consumer of data are just two areas where the knowledge and skills of a librarian could easily be applied. The bottom line is that while we may not be able to teach students everything about data literacy, we can teach them some important things to further their education.

Many issues in information literacy are relevant for data literacy. Evaluating the quality and appropriateness of materials, for example, is a concern in both information and data literacy requiring the development of critical thinking skills in students. For example, the Reuters news agency produced an egregiously bad chart implying that gun deaths had decreased in Florida since the “Stand Your Ground” law was enacted (they’ve actually increased), citing Florida’s Department of Law Enforcement as the source. Even when the data are sound, the presentation of the data may be suspect. Evaluating data could present particular difficulties for high school students as understanding the context and methodologies behind the data may overwhelm them.

This segues into another issue that was frequently brought up, the difficulty of teaching data literacy in a way that high school students could understand and apply. There are a number of fairly easy to use online tools available to analyze or visualize data that could be used to introduce high school students to working with data by taking a lot of the guess work out of the process. However, focusing on a tool may hinder a student’s ability to understand the underlying concepts of data analysis or visualization and limit their cognizance of the data itself. Schools librarians noted that students will often write their assignments and then seek out the data they need to support their arguments instead of the other way around.

In closing, participating in this project has renewed my admiration for school librarians. Everyone I met was incredibly passionate about the work that they are doing as educators and fully committed to extending their work into data. I can’t wait to see how school librarians will make use of the products with the materials produced from this project.

Registration is Now Open for the 8th Annual NE eScience Symposium April 6, 2016

e-Science Portal blog - Mon, 01/11/2016 - 09:00

Posted on behalf of Elaine Martin, Director of Library Services, Lamar Soutter Library and Director of NN/LM NER, University of Massachusetts Medical School

To continue to enhance collaborative New England Region libraries’ support of e-science initiatives for their research institutions, the Lamar Soutter Library at the University of Massachusetts Medical School is hosting the 8th Annual University of Massachusetts and New England Area Librarian e-Science Symposium. This day-long event will serve as an educational and collaborative opportunity for science and health sciences librarians to discuss e-science resources, in addition to future roles that libraries and librarians might take on to support their institutions.

The theme of this year’s symposium is “Library Research Data Services: Putting Ideas into Action.” Focusing on librarians involved in RDS, the broad goal of this symposium is to build off what has been discussed at the pervious symposia in order to give librarians a chance to share their current efforts in supporting scientific research. Discussions will inform how librarians can take action at their own institutions to engage in e-science initiatives, and also look at the roles of librarians in the dynamic field of data science.

The 2016 Symposium is set to focus on data services and the many practicing roles of librarians. Attendees will hear a keynote overview of data services from Kendall Roark. Kendall is an Assistant Professor and Research Data Specialist at Purdue University Libraries, and also a member of the CLIR/DLF eResearch Faculty. She will provide a broad perspective on the research data management services that US and Canadian libraries are implementing.

A new session at the symposium this year will be breakout sessions: participants will be able to attend 2 of 4 planned sessions featuring services that libraries are currently implementing. Options include:

  • Compliance with Margaret Henderson, Director of Research Data Services; and Hillary Miller, Scholarly Communications Outreach Librarian, Virginia Commonwealth University Libraries
  • Data Information Literacy with Jake Carlson, Research Data Services Manager, University of Michigan
  • Data Repositories with Lisa Johnston, Research Data Management/Curation Lead, Co-Director of the University Digital Conservancy, University of Minnesota
  • Informationist with Leah Honor, Library Fellow, Informationist Liaison to the Child and Adolescent Neurodevelopment Initiative, University of Massachusetts Medical School

In the afternoon, there will be presentations from two panels discussing the future of data science with library school educators and practicing data librarians. Participants on the panels include:

  • Library Educators:
    • Suzie Allard, Associate Dean for Research, University of Tennesee at Knoxville, Co-investigator of DataONE
    • Matthew Burton, Visiting Assistant Professor and Post-Doctoral Researcher, School of Information Sciences, University of Pittsburgh
    • Jian Qin, Professor, School of Information Studies, Syracuse University
    • Rong Tang, Associate Professor, School of Library and Information Science, Simmons College
  • Librarians:
    • Christopher Erdmann, Head Librarian, Wolbach Library, Harvard Smithsonian Center for Astrophysics
    • Margaret Henderson, Director of Research Data Services, Virginia Commonwealth University Libraries
    • Andrea Thomer, Doctoral Student, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign

Additionally, as with previous symposia, a poster session will be held, to highlight work in e-science that has been accomplished at various libraries in the region while also encouraging discussion and networking among event participants. This year’s symposium will again feature a poster competition with three different competition categories. You are invited to submit a poster abstract; we are still accepting submissions!

The symposium will be held on Wednesday, April 6th, 2016 in the Faculty Conference Room at the University of Massachusetts Medical School in Worcester, Massachusetts. The event is free of charge, but advance registration is required; due to strict space limitations, attendance will be capped at 90 people.

For further details, please visit the symposium website: http://escholarship.umassmed.edu/escience_symposium/2016

Please RSVP by completing the registration form. 

Please direct any questions to:

Julie Goldman, MLIS
Library Fellow
Lamar Soutter Library
University of Massachusetts Medical School
55 Lake Avenue North
Worcester, MA  01655
(508) 856-2229

On Annoyance

e-Science Portal blog - Mon, 12/28/2015 - 10:00

Lately I’ve been thinking about annoyance, fueled in part by readings like these:

From Joe Palca’s interview above, things that annoy people often include these characteristics:

  • They’re unpleasant
  • They’re unpredictable
  • They last for an uncertain duration

So how might we annoy researchers when we talk with them about research data management? I can think of a few ways.

Unpleasant. Some RDM-related interactions could be viewed as an examination of shortcomings. Clean your closet. Eat more fiber. Use good file naming conventions. All serve as reminders of stuff we know we should be doing better. These are not exactly cheery topics of conversation that people enter into enthusiastically – who wants a reminder that what they’re doing might be wrong or inadequate?

Unpredictable. Researchers might be expecting to have conversations like these with IT staff, or folks from sponsored research, for example, but they might not expect to hear librarians talking about strategies to manage data – until they realize that we’re in the business of organizing materials and ensuring they can be found in the future. Part of this is an ongoing educational piece, to ensure that our colleagues across campus realize how our training and experience might be able to make their lives a bit easier.

Uncertain duration. There is not necessarily a clear endpoint for RDM conversations; even those punctuated by a grant proposal deadline will (hopefully!) not come to an end when the data management plan is written.

What can we do to make these interactions less annoying, and more productive?  Add your comments below, or Tweet your 140-character thoughts to @NERescience

Notes from the November New England RDM Roundtable Discussion

e-Science Portal blog - Tue, 12/22/2015 - 10:00

The second New England Research Data Management Roundtable was held last month on November 20th, at the Lamar Soutter Library at the University of Massachusetts Medical School campus. This roundtable was the second in a planned series of roundtable discussions targeted for New England librarians who are engaged in research data management services or who want to learn more about data librarianship. Sponsored by the National Network of Libraries of Medicine, New England Region, the NE RDM Roundtables will provide opportunities for New England librarians to compare notes, ask questions, share lessons learned, explore new working models, acquire fresh ideas for their workplaces and develop new partnerships.

This particular Roundtable event was specifically intended for librarians in the RDM Community of Practice, i.e. librarians who are currently actively engaged in planning and/or delivering RDM services (note:  future NE Roundtables will also be planned for an RDM Community of Interest). It was also preceded by a “Data Tools Forum” which featured a brief introduction on the integration of data science tools in the research landscape and overview presentations of three open-source tools commonly used in working with data extraction, wrangling, analysis, and presentation:  OpenRefine, RStudio, and Jupyter. Videos of these presentations can be viewed on the NER eScience Program YouTube site.

Twenty four librarians from multiple New England institutions discussed the topic “Engaging faculty and graduate student researchers at our institutions.” Attendees were divided into five tables with four to five other attendees per table. At each table a member of the NE Roundtable planning team served as moderator for the discussion. The program was divided into two 1 hour sessions. During the first session, the discussion topic focused on how librarians engage with their faculty. The second session focused on how librarians engage the graduate students at their institution. The discussions revolved around specific questions.  Time was given after each session for each table to report out to the entire group.

Feedback on the Roundtable events have been quite positive. Attendees have noted that they like the opportunity to hear what their colleagues are doing and to discuss RDM issues, challenges, strengths, and their libraries’ service models. The New England eScience Program plans to coordinate future Roundtables three times a year. Topics for these roundtables will be based on attendee recommendations.

The following is a summary of questions and bulleted attendee responses and comments from the Roundtable Discussion tables.


Topic 1: How do you engage with your faculty?

Specific Questions Addressed:

  • What are your typical interactions with faculty about data?
  • What are your methods of contact and how do you reach out to this group?
  • What are faculty’s greatest concerns about data?
  • How is the library positioned to provide support to faculty concerning their data?
  • What are your concerns about engaging with faculty on your campus?
  • What ideas do you have for increasing your outreach to this group?

1. Types of interactions with faculty:

One-on-one or small group discussions

  • On the train this morning I talked to faculty about data. The faculty was enthusiastic.
  • Identify champions at all levels and across departments to build momentum; even if it means starting your own project on your own.
  • “How can I help?” I didn’t know if I was ready but I did it.
  • Look at how you can get 5 minutes.
  • Open access, open data, open workflows – communicate these cultural changes. Most not (yet) talking with faculty.
  • Just do it and present what you want to do. What services? DMP, DM instruction (one shot.) Go alone or in a group (which may be too many cooks in the kitchen)
  • Go to people to see if you can help. Next steps – who is coming with me? Bring community resources to help and to teach yourself.


  • Workshops for liaisons, faculty and graduate students. Some faculty are receptive. They often get technical writers
  • Data management workshop series.
  • Data analysis tools and reformatting workshop with hands-on.
  • Offer to train grad students on data management topics
  • Offer some types of classes to support researchers. In some cases attendance has dropped off from initial offerings. Like many types of instruction finding the right time for reaching an audience is important.
  • Stipends for attending training?
  • Held a webinar on the DMPTool using WebEx, so faculty didn’t have to leave their office.

Other offices on campus

  • Hit faculty where they are already interacting with another office, e.g. OSP, IRB.
  • Sits on IRB, good to form relationships with faculty
  • Research data management is not the sole responsibility of the library. IT, Library, Research Office, researcher, policy makers, IRB, institutional animal care and use committee – all feed faculty to librarian for assistance with RDM.
  • Storage issues and charge backs for electronic records (incentive to manage data better.) Research data manager is in IT.
  • Clear message about ownership of data. Data management is part of IT, main focus is on storage. DM working group = relationship with IT. Build on the relationship.
  • Encourage offices currently embedded in the research workflow to refer research to the library – for example Research Office
  • Libraries are involved on University committee on PhD development and data issues are a theme. One institution did a faculty survey to ID campus needs (and found many.) Working to foster broader campus discussions on this topic. Another hosted (with IT) conversations with faculty about data issues and needs. Another is exploring data needs as the school gears up to offer doctoral programs
  • Office of sponsored research funders mandates – encouragement.

Other Library efforts to reach faculty

  • Drafting white paper for head of research data services = segregated different vocabularies/values understanding of data services; white paper addresses this; laterally interact with faculty rather than trying to get buy-in from top
  • What are others doing about website/web presence? Resources are on campus everywhere – maybe a website could accumulate those
  • Did a faculty survey on data needs, with a 33% response rate
  • Data summit with stakeholders. Approach small groups of faculty stakeholders
  • Best practices: use existing pathways that already have relationships with faculty: for example, the scholarly communication group refers research to Data Management team. The Office of Research does also.
  • For publicly available data we assign a DOI
  • Creating an individual Dataverse is possible for data repository
  • Leverage existing relevant services currently in use (scholarly communication team, OER)
  • Craft meaningful emails that liaisons can send to faculty & researchers
  • Created libguide on data management (in process)
  • Records management – need buy-in from “the top,” the stick. Top down? Bottom up?
  • Try to woo liaisons
  • Tasked with beginning data management conversation with faculty – created libguide

2. Topics addressed when engaging with faculty:


  • Who owns data needs to be clear
  • Education, collaboration, time, compliance, sharing – who is using, already sharing data
  • How to choose storage options: IT storage, Dropbox, University options; Dataverse, Figshare
  • Security, backup, intellectual property – data ownership, international issues
  • Research wants lab archives and statistical analysis


  • The new DM person is creating chargeback service for storage as a push to better manage data
  • Working group began around tools – IT, research computing, research compliance, labs. Talking about broader topics
  • Data management services – building program capacity and outreach, doing consultations, providing education, making liaisons aware, working with campus stakeholders
  • Learning tools of data management is an avenue to connect with faculty
  • Data that is manipulated, analyzed, GIS servers, working with data, social sciences data

Data Management Plans

  • Are campuses requiring DMP’s even if funder does not require it? Yes, looking at examples
  • Stipends for faculty who get DMP training
  • Faculty DMPs all have the same process
  • If we get asked to talk about research grants, bring up DMP’s
  • DMP Support is an area where most of the group was involved. At [school] all of the DMPS are reviewed by the Libraries via their sponsored programs group. Setting reasonable boundaries (don’t write DMP’s for researcher) is important. While DMP support is an active area of engagement in the present, most anticipate that the need for support will diminish or change in nature as researchers become accustomed to developing them
  • Disclaimer: what we say on your plan does not mean plan will pass. Get them thinking about issues surrounding DMP. Entrée to it, repository, follow up, post-award review
  • DMP too seen by many as bureaucratic burden

3. Concerns about engaging with faculty on campus:

For the library

  • Concern about IP with data and faculty in bio-chem/pharm areas
  • International students don’t understand, institutional policy about data ownership
  • Ethical /policy issues about data
  • [School] has isolated pockets
  • Data services scattered, no common definition/understanding; working to create bigger group to take care of these services for the whole campus
  • “Another Library” initiative asking for a group (negative)
  • What do we do next? Feedback from campus/faculty? Create a service and then publicize? Is it easier to go it alone? Key players: IT, grants office, but resistance to interdepartmental collaboration
  • Best examples: some workshops, some emails, some adjuncts interested. Faculty don’t see us as data management specialists
  • Hosting versus ensuring access to data – does it matter?
  • So many entities on campus with interest in data, sometimes no clear ownership. Whose domain is this?
  • Debates about storage within library staff
  • Patient care, security issues. Very technical
  • Our concerns about faculty: do they know to look to the library?
  • Managing expectations in what we as librarians can do – develop skills
  • Reaching out is an issue, might be ready when faculty come to the library, not perceived now
  • Primary and secondary data support can have different service providers and support. Discussion on primary researcher generated data
  • Communities need a lot of support navigating the world of repositories, for putting their data and data discovery. Institutional repositories may lack desired functionality
  • Communities both express a need for greater knowledge as well as exhibit a lack of awareness about data management issues among many
  • Libraries are not in many people’s minds when they need help with data
  • Insularity with data practices can make support and sharing difficult
  • Libraries have a challenge in creating broader campus partnerships to support RDM. Groups need to learn to work together in new ways
  • Libraries have a challenge in building their capacity in step with and in anticipation of campus needs. Shaping data positions in a sensible way, and how to mix that role with other responsibilities is a puzzle in smaller institutions
  • Offices on campus often competing, spread out
  • No grant office – not a research institution – not a culture of grantsmanship. RDM turn into grant office? Mission creep
  • How do you support liaison so they are not scared?
  • Some departments just don’t want to interact with library

For faculty

  • Wide issues with storage
  • Research faculty feels neglected because it is a teaching school
  • Meeting research data mandates
  • Getting past funding
  • Internal systems at institutions are different
  • Campus structure – partners IT, VP of research, grants & sponsored programs. No one can do it all. Faculty were bouncing from place to place


Topic 2: How do you engage with graduate students?

Specific Questions Addressed:

  • What are your typical interactions with graduate students concerning data?
  • What are the differences and similarities in engaging with this group as opposed to engaging with faculty?
  • Do you tend to work with specific groups of graduate students in depth, globally with all graduate students, or a combination of the two?
  • If you teach graduate students about data, what are the topics you teach?
  • What are graduate students’ greatest concerns about data?
  • What are your concerns about engaging with graduate students on your campus?
  • What ideas do you have for increasing your outreach to this group?

1. Types of interactions with graduate students: 

Within the library

  • 4 part class in data management for everyone to attend
  • Primary attendees to seminars
  • Avoid “you have to talk to a librarian”
  • Brief 20 minute sessions on data management
  • Workshops by topic not department
  • Consultations
  • Library events
  • Workshops taught in Python and R
  • Through teaching research methods and lifelong learning
  • Through established programs and instructional sessions
  • Instruction like research methods and data sharing
  • Small group
  • Individual

Outside the library

  • Invited to labs / lab tours
  • Through other campus offices (IRB)
  • Panel discussions with IS&T, administration, staff, engineering, and digital humanities
  • Through electronic lab notebook
  • Outreach through department level workshops works best
  • Present to lab groups but not as much
  • Python groups
  • With office of research
  • With office of professional development
  • With the graduate council
  • Responsible research committee
  • Grant writing
  • TA and RA orientations
  • With liaisons

2. Topics addressed when working with graduate students:

Data Management

  • DMP intro
  • DMPTool
  • Metadata
  • File naming
  • Organization
  • Repositories
  • Best practices
  • Data security
  • Readme files
  • Preservation
  • Formats
  • Storage options
  • Responsible data storage

Working with Data

  • Using statistical software
  • Electronic notebook best practices
  • Python
  • R
  • GitHub
  • Jupyter
  • Data visualization
  • Data for information
  • Data for statistics
  • Research methods

Finding/Sharing Data

  • Data sharing
  • Open access
  • Finding data
  • Scholarly publishing
  • University policies
  • Copyright
  • Patient data
  • Personally identifiable data

3. Concerns about engaging with graduate students on campus:

  • How to make services scalable
  • Too many graduate students to reach everyone
  • What to actually know how to do it, not just the tools
  • How do we reach them at the point of need?
  • Some students don’t know the questions to ask?
  • Graduate students going back to PI and saying “you’re doing this wrong”
  • Limited interactions
  • University policies and compliance
  • MA doesn’t have public documents requirement
  • They do a lot of work and then leave
  • When to reach? (time in the term? Before bad habits begin?)
  • What is the right mode? (class, workshop, lab?)


Data Tools Forum Videos Now Available

e-Science Portal blog - Wed, 12/16/2015 - 15:26

If you didn’t get to attend the Data Tools Forum that was held November 20th at UMass Medical School, no worries! And if you did attend the forum, but would like the opportunity to review the interesting presentations, you can do that too!

All the presentations from the Data Tools Forum are now available on the New England Region eScience Program YouTube site on this playlist.

Check them out!  And if you’d like to view more information about the speakers at the Data Tools Forum, check out the event LibGuide.

Meta-Service: How Illinois’ Research Data Service Benefits the Library

e-Science Portal blog - Mon, 12/14/2015 - 13:17

Contributed by Heidi Imker, Director of Research Data Service and Associate Professor, on behalf of the Illinois Library

At the University of Illinois at Urbana-Champaign, our Scholarly Commons’ Data Services has served our campus community in acquisition, preparation, and secondary analysis of data for both research and teaching purposes since 2009. Following participation by the Library and the Office of the Vice Chancellor of Research in the ARL eScience Institute in 2011 and a subsequent year-long Illinois Research Data Initiative (1), our campus recognized the need to include explicit efforts to increase stewardship, curation, and preservation of research data created at the University of Illinois. With campus support and funding, we formally launched a Research Data Service (RDS) in 2014 with the expectation that the RDS would actively engage in collaborations and interface both internally with our Library colleagues and externally with partners across campus. Although the model is not without challenges, we all have steadily worked together to expand our support of data-related needs at Illinois.

As the Director of the Research Data Service (RDS) at Illinois, in the fall of 2015 I was asked to give a seminar at another university about Illinois’ RDS program. From publications, blogs, conferences, and conversations, it’s clear there’s an undercurrent of uncertainly around research data at academic libraries as a whole. In preparation for the seminar, I wanted to be able to talk about what having an RDS program brings to the Library. I e-mailed a swath of colleagues and asked them “How do you think having an RDS has been beneficial to the Library (or for your positions as Librarians)?” It was a casual e-mail question, but I’ve found the organic and honest nature of their responses especially illuminative. The small quotes I could use for the talk didn’t do their vision, thoughtfulness, and variety justice, so I wanted to share them more broadly. Here they are:


University Librarian John Wilkin:

“I find it both a funny question (RDS is fundamental to who we are, from my perspective, so I might ask “what value do we get from reference service?” “what value do we get from collection development?”) but also say that the RDS gives us [the value] of engagement in new and more powerful ways with emerging areas of work, which is invigorating.”

Subject Specialist Peg Burnette:

“It has been nothing but beneficial as far as I can tell. Data literacy is something that has been added to subject specialist positions for several years, but research data management is still an emerging and multi-faceted field that most librarians have only cursory knowledge of at best.

Being involved in the “birthing” of the RDS has been invaluable for me as a subject specialist. Obviously biomedical science is all about research data, and the ability to understand the nuances of the entire data spectrum allows me to talk to researchers intelligently about their research challenges and needs. It has been interesting to discuss these issues with researchers as well. While most researchers think they do an adequate job with research data, it has been eye opening for them as well and very much a case of not knowing what they don’t know.

Being part of the research data workshops and seminars has such an immersive experience and has resulted in a strong foundation in issues related to research data while also illuminating unique case-based understanding. My involvement with both the RDS Implementation Committee, and now the RDS Committee, has been a rich learning experience that has been both personally and professionally rewarding.”

Preservation Librarian Kyle Rimkus:

“From where I sit the benefits of the RDS to the library haven’t been too obvious yet, but I think they will become more so with time. For starters, the RDS is bringing the library into closer collaborative contact with our supercomputing center and the sciences. Academic libraries have traditionally had a strong humanities focus, and while UIUC and its domain-specific libraries already have a strong service connection to the sciences, hosting the RDS in the Main Library is strengthening our connection to the broader campus, rather than asking the departmental libraries to shoulder all of this responsibility on their own. I think that as the service gains momentum, it will also foster new technical knowledge in our organization of how research on campus is conducted, and that this will benefit us as librarians. After all, the book is no longer the only game in town when it comes to transmitting knowledge, and libraries are evolving to address current and future modes of networked scholarly communication — data management will have a huge role to play in this evolution. Taken in all, I see the seeds of many benefits in place, but expect that these will be slow to accrue and reveal themselves.”

Archivist for Electronic Records Joanne Kaczmarek:

“I think the value of having RDS program in the Library gives librarians an opportunity to get more directly engaged in the research work being done across the campus. More engagement means more understanding which in turn means more likelihood to provide meaningful assistance to the teaching and scholarship endeavors of the institution. It helps us better understand how subject matter experts are actually conducting their research and therefore it can have a positive influence on our collection development activities – both traditional resources as well as the procurement of data resources.”

Subject Specialist Christie Wiley:

“The benefits of having a RDS are that as an engineering librarian – I am not a one person solo band trying to identify data needs and create services for researchers alone.  There is a tangible value in having people within the research data services from various backgrounds to learn from, share ideas, obtain input and collaborate. As a librarian, it sharpens and enhances my perspective, inspires me to keep learning, ask more questions and learn new ones as well.”


Although I was reasonably optimistic that the RDS was of benefit to our Library, hearing of ways that hadn’t even occurred to me and across a breadth of positions enforced both how well research data “fits” into the Library and the value of our collaborative model. Not only do our colleagues’ strong support and genuine interest in research data reflect how the RDS came to have its home at the Illinois Library to begin with, they reflect how we’re positively positioning ourselves – collectively – for successful support of research needs on our campus. As other universities consider the future of research data stewardship on their campus and in their Libraries, we hope that our experiences at Illinois can serve as evidence of the genuinely synergistic relationship between data and the Library.


1. “About the Illinois Research Data Initiative.” Illinois Research Data Initiative. University of Illinois at Urbana-Champaign, Last Accessed 3 Dec. 2015. https://web.archive.org/web/20151203202311/https://blogs.cites.illinois.edu/datasteward/about/

Job opportunity: Librarian for Research Data – Tisch Library at Tufts University

e-Science Portal blog - Fri, 12/04/2015 - 11:00

The Tisch Library at Tufts University in Medford/Somerville, Massachusetts is seeking a Librarian for Research Data.  Please see the posting for a complete description of the position: http://tufts.taleo.net/careersection/ext/jobdetail.ftl?job=15001602&lang=en.

Link Roundup – Recent Items of Interest on Data, Open Access, and Scholarly Communication

e-Science Portal blog - Wed, 12/02/2015 - 15:29

I’m sure many of you are like me and find it hard to follow-up on all the interesting links you find through blogs, twitter, and other social media channels. So I thought it might be helpful if I looked at some of the things that have come up recently, and let you know which ones are helpful and why.

Dean Giustini has a top 10 trends list for medical libraries that includes things that everyone should be aware of. It includes all the usual suspects, including altmetrics, data, and open access.

If you’ve been thinking of reading Christine Borgman’s latest book, “Big Data, Little Data, No Data”, you can get an overview in 47 minutes by linking to a lecture she gave earlier this year at the University of Gottingen, Big Data, LIttle Data, Open Data.

A social networking site is not an open access repository. Even if you don’t have an institutional repository to offer as an alternative, know why researchers need to be wary of putting their papers on ResearchGate or Academia.edu. This feature from the Office of Scholarly Communication at the University of California covers what open access means, interoperability, long-term preservation and access, business models, use of contacts and personal data, and of course, the fine print, which includes an indemnification clause. Bottom line, the sites might be useful for social networking, but they are not going to help with open or public access requirements.

Why Open Research? is a new project by  Erin C. McKiernan (@emckiernan13 on Twitter) that aims to help research learn about the benefits of sharing their work. McKiernan has been an advocate for open research for quite a while and developed this website with a Shuttleworth Foundation flash grant. The site has appealing graphics and short, too-the-point reasons for sharing and open access. For those of you wanting to promote open research, there are images, card sheets, and slides you can reuse for your teaching or promotion.

An Open Science Peer Review Oath. Developed by a group of researchers as part of the AllBio: Open Science & Reproducibility Best Practice Workshop, This article gives 4 principles as an open peer review oath, and then gives some guidelines for open science reviewers. It will be interesting to see if open science and open peer review are able to gain a toehold in the scholarly communication community. The article itself if publishing in F1000Research with open peer review, so it gives you an idea of how the process might look, a good reason to check it out.

Department of Transportation Public Access Plan is finally out. Luckily for us, SPARC has already done a nice overview of the policy on their blog, so we don’t have to try and wade through all the government-speak. Lots of interest, including use of DOIs and ORCIDs for articles. As for data, DMPs are required and they specifically address licensing “strong preference for the use of CC-BY or equivalent license”. There is also mention of a minimum of common core metadata!

If you’ve been reading the news about Elsevier and the researcher, Chris Hartgerink, who wants to text mine some articles, you might be wondering how to text mine. ASIS&T had a webinar in early November that is now online so you can learn all about it. Clifford Anderson and Hilary Craiglow of Vanderbilt University are the presenters of Text Mining in Libraries: How Librarians Develop Skills Required to Support This Evolving Form of Research.

And for those of us encouraging researchers to deposit well-documented data, an article that surveyed 100 ecology and evolution datasets and found over half could not be reused. Public Data Archiving in Ecology and Evolution: How Well Are We Doing? As well as the assessment of datasets, the article includes a nice summary of reasons for data sharing, and some recommendations to improve public data archiving (PDA). One useful part of the article is the fact that the images are all open access so you can download them as powerpoint slides for any talks you are giving – and figure 1 is a cute cartoon if you want to break up the wordy slides in a presentation.

Notes from the first Midwest Data Librarian Symposium

e-Science Portal blog - Mon, 11/02/2015 - 16:44

On October 15 and 16, I was lucky enough to be a part of the Midwest Data Librarian Symposium as a participant and facilitator. The Symposium was organized by Kristin Briney and Brianna Marshall and held in Milwaukee, WI, at the University of Wisconsin-Milwaukee Golda Meir Library. The Symposium was developed with the idea of giving participants lots of discussion time, but also, some concrete ideas to take home.

The good news is, the slides, handouts, working documents, etc. are available online for everyone to use. Just look for the links in the Symposium schedule to view the materials. A more formal collection of these materials will be deposited in the University of Wisconsin-Milwaukee repository, so keep an eye out for that link.

The Symposium started with a full morning workshop on Data Management Teaching Materials led by Lisa Johnston. Participants were asked to submit their favorite teaching slide, idea, trick, etc. ahead of time, so each person had a chance to present during the workshop. We started out with introductions and then Lisa had us all arrange ourselves around the room by different criteria – distance travelled, experience level, data specialty, etc. Each change of position allowed  us to meet new people before settling down to learn. Lisa started out by introducing the concept of backwards design, defining the goals, i.e. what do you want students to learn, then defining acceptable evidence that the goals have been met, then finally, creating an instruction session to accomplish the goal. With that in mind, the group presented their favorite ideas.The exchange of ideas was wonderful, from tools for risk analysis, checklists, thinking exercises, memes, and more.

The afternoon discussion topic was Consulting on Data, led by Cynthia Hudson-Vitale. Cynthia based her discussion format on the World Cafe model. There were 5 topics that data librarians might be consulted about:

  • Finding data
  • Data management plans/funding requirements
  • Data visualization
  • Data archiving, preservation, sharing
  • Other/Undefined

We thought about these topics with regard to marketing/initiating contacts, workflows, and follow up/assessment – and within these subtopics, tried to think about methods, outcomes, and strategies for addressing challenges. People were able to choose their topics(s) of interest, and move around as sub-topics changed. As we moved around, a table leader helped us bring together ideas for getting the most out of consultations in those areas. Once again,lots of great ideas – but sure to check out the link to the group notes at the end of the Session Plan.

The next day, we started with my session on Data Curation. I put out some mini-scenarios to get people thinking, and had people put stickers on the scenarios they thought warranted saving. (listed in the Session Plan). People moved into discussion groups that didn’t involve colleagues, so there was more chance to learn about what others were doing. We also had some enthusiastic LIS students, and I asked them to split up as well. After giving broad definitions of curation and some basic appraisal criteria, I had the groups discuss curation and report back on legal or funder issues, curation policies, and proper documentation. We returned to the scenarios after discussing data curation and generally there were fewer datasets that people felt needed to be saved. I think we ended up with more questions than answers, but that is the way it goes with data.

Our third session was led by Brianna Marshall and focused on creating elevator speeches to use when trying to bring in new partners to help with data. First we did a quick brainstorming session to think of partners (lots – see the list on the Session Plan) and then we chose 7 to work with. We all got a chance to create personas for the partner, which was enlightening. Then the group developed an elevator speech, and one group member delivered it after all the table discussions were finished. Links to the partner personas and elevator speeches are in the Session Plan as well, and I know they will be helpful to many people, because it is often hard to condense our ideas into a precise speech, plus, have a request for how that partner might help us.  This exercise really pulled it all together.

Our final discussion session on Teaching Data Management was led by Heather Coates, and build upon the ideas we had gathered in Lisa Johnson’s session the day before. Heather had us think about the 12 data information literacy concepts (DIL – found in table 1 of this article http://www.ijdc.net/index.php/ijdc/article/view/8.1.204/306)  and then create a sample lesson plan for teaching one or two of these concepts, based on one of the scenarios describing a class, course, or workshop. Heather separated us based on familiarity with data or teaching, or both or neither, so each group had a mix of skills to work with. The lesson plan outline provided guidance for how to structure our work. Of course, none of the groups have a totally completed lesson plan, but the great thing was, each group had different ideas how to teach, even when the group or topic was similar, so we all now have lots of good ideas to start with.

The format of the meeting encouraged lots of discussion, and each facilitator chose a different way to organize their discussions, and different types of outcomes. So not only did we all learn lots of new things about data librarianship, we also tested different ways to facilitate discussions for future teaching and events.

The symposium wrap-up was led by Jamene Brooks-Kieffer. It was an excellent way to pull together an amazing series of discussions. Jamene did the usual review of ideas, with a lovely garden metaphor to describe data services, and then she had us think about our local ‘growing conditions’ and think about the ideas we could transplant. And we had a writing exercise! For 7 minutes the whole group wrote about what we wanted to do and how we might do it when we got back to work. Then, just to make us accountable, we discussed it with one of the other participants, and hopefully, in 6 months, we’ll see if we managed to do something. Jamene also storified the tweets so you can read some of the fun https://storify.com/jbkieffer/mdls15-all-the-tweets-both-days

The great news is, there are people in many other Midwest libraries who want to make this an annual event, so be sure to keep your ears open.  I crashed the symposium from Virginia (I went to school in London, Ontario so I am a displaced midwesterner) and you might want to as well. And as I mentioned, keep your eyes open for the link to all the materials in the University of Wisconsin-Milwaukee repository – you won’t be sorry.

New Issue of Journal of eScience Librarianship

e-Science Portal blog - Fri, 10/23/2015 - 15:08

The latest issue of the Journal of eScience Librarianship has been published! The issue’s focus is on “Targeting and Customizing Research Data Management Services (RDM).” The full issue is available at http://escholarship.umassmed.edu/jeslib/vol4/iss1/. Check it out!

Table of Contents Volume 4, Issue 1 (2015)


Targeting and Customizing Research Data Management Services (RDM)
Elaine R. Martin

Full-Length Papers

Differences in the Data Practices, Challenges, and Future Needs of Graduate Students and Faculty Members
Travis Weller and Amalia Monroe-Gulick

Required Data Management Training for Graduate Students in an Earth and Environmental Sciences Department
Bonnie L. Fong and Minglu Wang

Assessment of Data Management Services at New England Region Resource Libraries
Julie Goldman, Donna Kafel, and Elaine R. Martin

Research Data Practices in Veterinary Medicine: A Case Study
Erin E. Kerby

EScience in Action

Examination of Federal Data Management Plan Guidelines
Jennifer L. Thoegersen

Diving into Data: Planning a Research Data Management Event
Robyn B. Reed

En Français S’il Vous Plaît: Translation and Adaptation of the New England Collaborative Data Management Curriculum’s Introductory Module
Natalie Clairoux

Data Management Outreach to Junior Faculty Members: A Case Study
Megan Sapp Nelson

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