Title
Challenges of developing a global wildlife health information management system part 2: Lessons learned from a wildlife epidemiologist's perspective
Author(s)
Joly, Damien O.; O'Rourke, Tammie; Palmer, Jonathan; Olson, Sarah; O'Rourke, Daniel; Mollard, Debbie; Dohm, Michelle; Rabinowitz, Peter; Vesgo, Sally; Goldstein, Tracey; Kreuder Johnson, Christine; Greig, Denise; Kelly, Terra; Karesh, William; Mazet, Jonna
Published
2013
Abstract
There is a positive trend in the wildlife health discipline towards large, interdisciplinary and interinstitution collaborative endeavours, such as the multi-agency West Nile and avian influenza surveillance projects over the last decade. Management of the data derived from these projects presents multiple challenges, from effectively communicating user needs to IT specialists to implementing a data terminology and taxonomy that is sufficiently flexible and comprehensive to capture the data necessary to achieve the project’s objectives. PREDICT is a five-year project funded by the United States Agency for International Development and led by the University of California at Davis, with a goal of improving the global capacity to detect emerging viral zoonotic pathogens of wildlife. PREDICT operates in almost 20 countries in Latin America, Central and East Africa, and Asia. In this talk, we discuss the unique data and information management challenges such a large and geographically dispersed project has presented from the non-IT specialist perspective, complementing the IT specialists’ perspective. Specifically, we explore the process of bridging the gap between an epidemiologists’ in-depth understanding of data content (with a naïve understanding of data management) and a database analysts’ broad understanding of data management (but limited knowledge of data content). We feel this oft overlooked exploration is important as we move towards “big data” underpinning increasing portions of our discipline.

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PUB27093