Stanford Libraries has created a new division called Research Data Services (RDS) that will work with other units on campus, such as the Stanford Research Computing Center, to provide services to Stanford scholars working with data.
RDS was created to support the lifecycle of data and digital scholarship by convening research support in digital humanities, geospatial analysis, computational social sciences and statistical support, and data management in all disciplines, including STEM.
Peter Leonard is the first Assistant University Librarian for Research Data Services. Prior to joining Stanford, he served as Director of the Digital Humanities Lab at Yale University’s Yale Library. Previously, he supervised Humanities Research Computing at the University of Chicago.
Here, Leonard explains why Stanford Libraries created RDS, how data is changing, and how this new division will serve researchers in all fields and disciplines at Stanford.
Why did Stanford Libraries create the Research Data Services division?
Researchers in all disciplines are confronted with enormous amounts of research data from a variety of sources: their own experiences or observations, commercial vendors, government agencies, and cultural heritage institutions. This research data could be mortgage records, satellite images of the Amazon rainforest, or thousands of digitized books. Entire research imperatives, such as the drive to ensure a sustainable planet, hinge on access and ease with complex, large-scale datasets.
Stanford Libraries is committed to supporting researchers throughout the research data lifecycle. From discovery or acquisition, to curation and cleaning, to algorithmic and quantitative analysis, to storage in a repository. We want to build on our tradition of service and learn from researchers on campus what to do next.
What departments within Stanford Libraries contributed to the formation of RDS?
The Stanford Geospatial Center, which supports spatial data science data, methods, and technology; the Interdisciplinary Research Center (CIDR), which designs and develops data tools and methods; scientific data librarians at Stanford Libraries; and the Stanford Libraries Digital Research Architect. We hope to build on the great work these teams are already doing – including data acquisition, licensing, curation, preservation and sharing – and make the services we offer even more clear and accessible. , both physically and virtually.
Can you cite some examples of how these RDS units support academics?
The Stanford Geospatial Center is the university’s primary support center for GIS (geographic information system) and spatial data science. Spatial techniques and approaches are shared by many disciplines. For example, they can help a marine biologist map current patterns of marine life on the California coast and let a historian studying the Salem witch trials explore the geography of accusers and defendants in the 17th century.
We need to be aware of how data can be used for harmful purposes…
CIDR is made up of academic technology specialists who support digital scholarship in a specific program or department. CIDR also has developers who create software for faculty digital research projects. And CIDR’s Data Science Software and Services (SDSS) group helps researchers learn languages such as Python and R, which are important in text and data analysis.
RDS also has staff who convert and enhance datasets with millions of records into formats usable for researchers, then place them on Stanford Libraries’ servers. We also have science librarians who catalog the results of research projects so that the information can be shared with others.
Who can use RDS and are there any fees?
RDS serves all Stanford scholars free of charge. Whether you’re a student with questions about multilingual text analysis, a postdoc interested in geospatial tools and data, or a faculty member looking for data for your next project, RDS can help.
Are there any challenges or concerns with using the data?
It is useful to consider the entire lifecycle of research data – whether from its acquisition or discovery, to its cleaning or transformation into forms better suited for computation, or to the actual work of research. analysis (in traditional or deep learning contexts), and finally to the ways in which the research products derived from it can be safely stored long-term for discovery and re-use. All of these steps will differ across disciplinary, departmental, and individual contexts – and it is especially incumbent upon Stanford Libraries to understand as much of them as possible. For this reason, our specialist subject colleagues are a vital resource.
Additionally, many discussions of “big data” today are increasingly informed by issues related to bias, algorithmic damage, and unrepresentative or incomplete training data. We need to be aware of how data can be used for harmful purposes, and we hope Stanford Libraries will continue to be a place where these questions and concerns are discussed and solutions offered.
Is RDS the only place at Stanford that provides help with data and digital scholarship?
RDS exists in an ecosystem of departmental and school libraries on campus, some of which report directly to these academic units and provide valuable resources to researchers through their disciplinary expertise. For example, colleagues at the Lane Medical Library are very knowledgeable about research data issues in health research, such as new NIH data management and sharing requirements. The Graduate School of Business’s Research Center and Library also has a knowledgeable team that provides many data and research services to the GSB community. We greatly benefit from their close relationship with their customers and their knowledge of their respective fields. And finally, the Stanford Research Computing Center (SRCC) is a hub for high-performance computing, as well as expertise, advice and experience for large-scale computing and storage. They play a key role in advancing research at Stanford.
For more information, visit the Research Data Services website.
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