A Digital Library Framework for Biodiversity Information Systems
| dc.contributor.author | Torres, Ricardo da Silva | en |
| dc.contributor.author | Medeiros, Claudia | en |
| dc.contributor.author | Goncalves, Marcos A. | en |
| dc.contributor.author | Fox, Edward A. | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2013-06-19T14:35:58Z | en |
| dc.date.available | 2013-06-19T14:35:58Z | en |
| dc.date.issued | 2004 | en |
| dc.description.abstract | Biodiversity information systems (BISs) involve all kinds of heterogeneous data, which include ecological and geographical features. However, available information systems offer very limited support for managing such data in an integrated fashion. Furthermore, such systems do not fully support image content management (e.g., photos of landscapes or living organisms), a requirement of many BIS end-users. In order to meet their needs, these users - e.g., biologists, environmental experts - often have to alternate between distinct biodiversity and image information systems to combine information extracted from them. This cumbersome operational procedure is forced on users by lack of interoperability among these systems. This hampers the addition of new data sources, as well as cooperation among scientists. The approach provided in this paper to meet these issues is based on taking advantage of advances in Digital Library (DL) innovations to integrate networked collections of heterogeneous data. It focuses on creating the basis for a biodiversity information system under the digital library perspective, combining new techniques of content-based image retrieval and database query processing mechanisms. This approach solves the problem of system switching, and provides users with a flexible architecture from which to tailor a BIS to their needs. To illustrate the use of this architecture, it has been instantiated to support the creation of a BIS for fish species in a real application. The goal is to help researchers on ichthyology to identify fish specimen by using search retrieval techniques. Experimental results suggest that this new approach improves the effectiveness of the fish identification process, if compared to the tradition key-based method. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier | http://eprints.cs.vt.edu/archive/00000681/ | en |
| dc.identifier.sourceurl | http://eprints.cs.vt.edu/archive/00000681/01/techreport.pdf | en |
| dc.identifier.trnumber | TR-04-01b | en |
| dc.identifier.uri | http://hdl.handle.net/10919/20161 | en |
| dc.language.iso | en | en |
| dc.publisher | Department of Computer Science, Virginia Polytechnic Institute & State University | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Digital libraries | en |
| dc.title | A Digital Library Framework for Biodiversity Information Systems | en |
| dc.type | Technical report | en |
| dc.type.dcmitype | Text | en |
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