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How to start and scale research data services: outreach, models and hiring advice
Summary
Presenters advised libraries first pursue outreach and awareness, then scale services as expertise and buy-in grow; practical tips included avoiding 'kitchen sink' job descriptions, considering distributed models, and budgeting for professional development.
April Wright recommended outreach as the first practical step for libraries beginning RDS: meet researchers, promote open science and data-sharing practices, and use that engagement to identify service needs. "The first step this 1st step might be to reach out to your research community to raise awareness of issues around open science and open data," she said.
Wright outlined two operational models: a distributed model where liaisons and informationists extend data services across disciplines, and a centralized team model where dedicated staff provide deeper technical services. She cautioned against "kitchen sink" job descriptions that list every possible duty without clear scope or posted salary, and recommended instead clearly scoped roles (for example, a data archivist or geospatial librarian) with reporting lines and appropriate compensation.
To build capacity, presenters urged libraries to invest in professional development, give emerging data librarians time to grow into roles, and remove conflicting duties so staff can focus on data work. Wright also suggested bundling adjacent services—such as pairing open access and open data messaging—to increase visibility and uptake.
