Data Competencies
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Data Competencies

This section of the Data Driven Discovery Initiative provides resources to explore recommended competencies, knowledge, skills, and dispositions for data librarians.

Data Competencies
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Data librarian and open science competencies have been developed, through an evidence-based approach in collaboration with MLA. Links to other library organization resources about competencies in health science librarianship will also be presented.

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Recent & Relevant Scholarship

Search for Data competencies and librarians (Google Scholar)

Highlighted NLM Resources

Blog: Living on the Data Fringes: Making Sense of Competencies - NNLM Region 4

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Seminal Works

Federer L, Foster ED, Glusker A, Henderson M, Read K, Zhao S. (2020). The Medical Library Association Data Services Competency: a framework for data science and open science skills development. Here is the MLA website version of the data competencies

Ohaji IK, Chawner B, Yoong P. (2019). The role of a data librarian in academic and research libraries

Prado JC, Marzal MÁ. (2013). Incorporating data literacy into information literacy programs: Core competencies and contents.

Health science librarian professional competencies (2007)

ALA/PLA data competencies at the Data 101, Data Geek and Data Expert Level

Curator’s Choice

For librarians that are interested in an actual list of skills and competencies, this supplemental list of competencies extracted from the literature that accompanies the Federer et al. (2020) article is a place to start thinking about your data librarian persona.

To think broader than the library, here is a list of post-doctoral set of research competencies that overlap data competencies

The Association of Research Libraries (ARL) has provided  definitions and guidance on competencies for data management, as well as, scholarly communication and open science.

Data Skills & Tools
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One of the most important aspects of learning about data is learning how to use tools to help you collect data, wrangle and clean data and analyze data. In addition to data management tools, there are also toolkits and management tools that will help you become a more effective data librarian. Find resources here to build awareness of the tools available and to help you develop the skills you need to use those tools.

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Recent & Relevant Scholarship

Google Scholar search for scholarly articles at the intersection of data tools and data librarianship

Google Scholar search for open data science tools and libraries

Google Scholar Search for data tools and the health sciences

SEA Library Carpentry Workshop: that links to information on using Git, Open Refine and the Unix Shell

Blog: RDM Snippets: Working with Data

Webinar: Tools for Data-Powered Discovery NLM’s Data Discovery and Pillbox

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Seminal Works

Robinson DC, Hand JA, Madsen MB, McKelvey KR. (2018). The Dat Project, an open and decentralized research data tool.

Pawlik A, van Gelder CWG, Nenadic A, Palagi PM, Korpelainen E, Lijnzaad P, … Goble C. (2017). Developing a strategy for computational lab skills training through software and Data Carpentry: experiences from the ELIXIR pilot


General sites to learn data tools and data management best practices:

Learn about specific tools:

Curator’s Choice

If you are interested in learning R for data analysis, I would recommend you check out these open resources to R programming. I am a qualitative researcher and I have been reading about how R can be used to analyze qualitative data as well as quantitative data. I found a few great resources R for Data Science and the R graphics cookbook (2nd ed) that I am working through.

Staying Current
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Stay current in data topics by using social media and blogs to find out about new webinars, courses, conferences, and emerging data topics in the field. If you are working with researchers on your campus, you need to know about how data integrates into the research life cycle and develop skills so the library can be a valuable research partner. Considering the rapidly evolving data topic situation in libraries today, it is important to stay current on data-related topics. Blogs and social media ways of staying on top of emerging topics, events and conferences. MLA has a variety of strategies for continuing education.

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Recent & Relevant Scholarship


Google Scholar search for data professional development and librarianship

Blog search: Research data management and libraries

Listserve search: for data science/ management and librarian


Highlighted NLM Resources


Webinar: “Exploring Data Literacy Needs at Your institution” NNLM. YouTube

Blog: NLM Musings from the Mezzanine – NLM Director’s

Blog: NNLM regional blogs about data topics

Webinar: How to speak data: librarians as public data ambassadors.  

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Seminal Works
Brown RA, Wolski M, Richardson J. (2015). Developing new skills for research support librarians. The Australian library journal, 64(3), 224-234.

Henderson M. (2020). Why You Need Soft and Non-Technical Skills for Successful Data Librarianship.

Mizzy D, Hayslett M. (2016). Data librarianship: A day in the life-science edition. In Kellam, L. & Thompson, K. (Eds.), Databrarianship: the academic librarian in theory and practice (pp.335-351). ACRL.

Applications in the Field



  • DataLibs- news on data science events, job opportunities, and new articles/ issues of the Journal of eScience Librarianship.

Social media



Curator’s Choice

I have been very interested in the intersection of formal and informal learning because I think librarians work in the liminal space between formal classroom learning and informal learning venues - so I would recommend thinking about formal AND informal avenues: Bruguera C, Guitert M, Romeu T. (2019). Social media and professional development: a systematic review. Research in Learning Technology, 27


Professional Organizations & Networks
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Interested in learning more about data topics? Find a variety of options for data professional development through professional organizations, websites, and data networks. Professional organizations & networks can define, support, and educate. While the organizations chosen here have a clear role in the world of libraries there are many more data organizations outside this facet that can be explored.

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Recent & Relevant Scholarship

Google Scholar search for data librarian professional development

Google Scholar search for professional development on the topic of research data management

Google Scholar search for professional development and data science


Highlighted NLM Resources

Course: Data Literacy for the Busy Librarian

Webinar: Needs Assessments in Research Data Management: What Do We Know and Where are the Gaps? ( )

Course: The RDM Open Science and Data Science On-Demand Courses (series of 4 courses)

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Seminal Works
Federer L. (2018, July). Defining data librarianship: a survey of competencies, skills, and training. Journal of the Medical Library Association, 106(3), 294-303. 10.5195/jmla.2018.306

Khan HR, Rand Du Y. (2018) What is a Data Librarian?: A Content Analysis of Job Advertisements for Data Librarians in the United States Academic Libraries [Paper presentation]. IFLA WLIC 2018, Kuala Lumpur, Malaysia.



Medical Library Association: MLA is a global non-profit organization that educates health information professionals, supports health information research.

RDAP (Research Data Access and Preservation)

Public Library Association (PLA), a division of ALA provides guidance on the PLA data-driven librarian

Coalition for Networked Information (CNI) -


Curator’s Choice

“Data Science in Libraries: Findings and a Roadmap Forward” Coalition for Networked Information.

“Data Librarians in Public Libraries” Celia Emmelhain, Public Libraries Online: Publication of the Public Library Association