Data Sharing and Secondary Use of Scientific Data: Experiences of Ecologists

Abstract

In recent years, scientific disciplines related to global, environmental problem solving have been a special target of data sharing efforts. Yet, very little research exists to guide the organization of scientific data sources or to understand the technical and social infrastructures needed to support the secondary use of data. Ecology is one of the disciplines that contributes to our knowledge of the natural world, but several factors complicate the sharing and reuse of ecological data. I conducted in-depth interviews to investigate the experiences of ecologists who used data they did not collect themselves in order to understand how they overcome these challenges. My findings extend our knowledge of information reuse, and they have implications for the design of digital libraries, for the development of standards, and for the creation of data sharing policies and programs. Fieldwork performs an important function in shaping ecologists' formal and informal knowledge, which carries over to their reuse of data. The informal knowledge ecologists acquire as collectors of their own data in the field or laboratory plays the most important role in their reuse of data. The secondary use of data on a large scale requires a greater emphasis on standardization, peer review, and quality control, which alters the extent of reliance on informal knowledge. However, a formal system offers only some of the information that scientists require to reuse data, and there is a danger in thinking that informal knowledge is easily replaced and is no longer necessary or important. My study shows how social exchange is an integral part of all scientific understanding. Standard research methods, metadata standards, and common storage formats make it possible to integrate data on a large scale, but this power comes from leaving out information that is necessary to secondary data use. Ecology teaches us that there are multiple sides to issues of trust, standards, understanding, and judgments about data quality. To be effective vehicles of data sharing, digital libraries and data repositories must capture public and private knowledge and must find ways to document the implicit knowledge that ecologists recognize and can articulate.