Potentials and Pitfalls of Integrating Data From Diverse Sources: Lessons from a Historical Database for Great Lakes Stream Fishes
2001; Wiley; Volume: 26; Issue: 7 Linguagem: Inglês
10.1577/1548-8446(2001)026 2.0.co;2
ISSN1548-8446
AutoresRobert L. McLaughlin, Leon M. Carl, Trevor A. Middel, Marlene Ross, David L. G. Noakes, Daniel B. Hayes, Jeffrey R. Baylis,
Tópico(s)Water Quality and Resources Studies
Resumoopment of databases bringing together scientific information from diverse sources. The enthusiasm has arisen for at least three reasons. First, scientists and resource managers recognize that databases are valuable for making scientifically-defensible decisions regarding fish stocks and their environment. Second, database approaches can increase the integrity and consistency of the data, encourage data sharing among researchers with different areas of expertise, and facilitate the transfer of data among different application programs used for analysis (Harvey and Press 1996). Third, developments in statistics, such as meta-analysis, are improving greatly our ability to summarize what has been done, to examine questions at broader spatial, temporal, and taxonomic scales, and to plan future research (e.g., Osenberg et al. 1999). These developments mean that scientists and resource managers whose primary training may emphasize skills in fisheries management, fish ecology, environmental issues, and policy making, will be asked more frequently to be involved in the construction or management of large databases, or to contribute data or funds to them. On one hand, this is desirable because fisheries scientists are likely to be “closer” to the data and methods of collection, and therefore can improve the quality of the design and analysis of the database (Van Alstyne et al. 1995). On the other hand, this can be problematic if the scientists are unfamiliar with database design and management. Indeed, in some
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