An observational biodiversity database for the University of Colorado Museum of Natural History [electronic resource]
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Online Access |
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| Format: | Thesis Electronic eBook |
| Language: | English |
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2011.
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| Abstract: | Natural history collections play an important role in the accumulation of biodiversity knowledge through the collection and conservation of specimens. But other sources of biodiversity data are also important to preserve, curate and make widely available to data consumers. Observational databases are one such source that has great potential value. The amount of information generated from these observational biodiversity data can be many times greater than what is represented by specimens in natural history collections. Thus organizing and digitizing observational data into formats interoperable with other species occurrence datasets will enhance accessibility and provide users of this data with a cost effective method of querying and analyzing the largest amount of biodiversity information. Because data management and curation are an essential part of collections management practices, museum scientists are well poised to tackle the challenge of managing observational databases in addition to the specimen databases already being curated. My thesis work involves the development of a database for the University of Colorado Museum of Natural History comprised of occurrence records related to observational biodiversity data, based on Darwin Core standards. In addition, this database will be robust enough to include the kinds of detailed ecological data often collected by field biologists as well as digital information such as photographs, video, audio or document files. The flexibility of the database to incorporate multiple data types was tested using six case study datasets provided by four collaborators. Additionally, the amount of effort needed to prepare and import each dataset into the database was evaluated, in order to determine the feasibility of having museum staff curate the database. Due to the heterogeneity in data among the six datasets, eighteen hours were spent in data manipulation for all of the datasets in preparation for import into the database, which is more efficient than manually entering the data. The database efficiently captured the majority of data from five out of the six datasets. Ultimately, sharing the database through the Global Biodiversity Information Facility (GBIF) or similar database federations is the future objective of this database. |
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| Item Description: | Source: Masters Abstracts International, Volume: 49-06, page: 3428. Adviser: Robert P. Guralmick. |
| Physical Description: | 43 pages. |
| ISBN: | 9781124672854 |
| Host Item Entry: | Masters Abstracts International 49-06. |