the ability to work independently at the intersection of digital data, technology, and metadata. These core skills are the base on which training in digital preservation concepts, data modeling, data standards, policy, and data collection and management can be added to round out a data liaison’s preparation. In addition, because data services are in their infancy, it cannot hurt for a data liaison to be skilled in building library programs and services. There is a long-standing debate over whether it is more important for engineering and science data curation liaisons to have domain expertise or information science expertise. The answer is that data liaisons must have both. To create data liaisons with this combination of skills, libraries can develop existing liaisons with interest, passion, and strong analytical skills or they can recruit domain experts, and teach them about excellent information science practices. Consider the following four potential data liaison personas: • A subject liaison with a domain-specific education and work experience in a field such as civil engineering or chemistry. • A subject liaison with no domain-specific expertise, but with excellent analytical and technical skills who has a passion for understanding and manipulating data. • A researcher in the life sciences who fell into managing data for a lab because they were the only one available to do it and they find the work enjoyable. • A newly minted Masters of Science candidate from a library and information science program with a specialization in research data curation. One important feature of data curation in engineering and science fields is that curatorial needs vary widely across each discipline. In physics there are large, established data repositories and a hugely collaborative culture therefore the data curation services needed by individual physicists may be fewer and necessarily very different from services that might be useful in the neurosciences, where disciplinary repositories are not as common and the proliferation of data types and formats prevents easy standardization. For this RLI 265 19 The Last Mile: Liaison Roles in Curating Science and Engineering Research Data ( C O N T I N U E D ) AUGUST 2009 RESEARCH LIBRARY ISSUES: A BIMONTHLY REPORT FROM ARL, CNI, AND SPARC The highly self-motivated liaisons who want to work in this realm will need to have very strong analytical, project management, and problem solving skills, as well as the ability to work independently at the intersection of digital data, technology, and metadata.