Full text
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| Author(s): |
Daniel Cintra Cugler
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Instituto de Computação |
| Defense date: | 2014-01-09 |
| Examining board members: |
Claudia Maria Bauzer Medeiros;
Clodoveu Augusto Davis Junior;
Luciano Antonio Digiampietri;
André Santanchè;
Fábio Luiz Usberti
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| Advisor: | Claudia Maria Bauzer Medeiros |
| Abstract | |
Biological observation databases contain information about the occurrence of an organism or set of organisms detected at a given place and time according to some methodology. Such databases store a variety of data, at multiple spatial and temporal scales, including images, maps, sounds, texts and so on. This priceless information can be used in a wide range of research initiatives, e.g., global warming, species behavior or food production. All such studies are based on analyzing the records themselves, and their metadata. Most times, analyses start from metadata, often used to index the observation records. However, given the nature of observation activities, metadata may suffer from quality problems, hampering such analyses. For example, there may be metadata gaps (e.g., missing attributes, or insufficient records). This can have serious effects: in biodiversity studies, for instance, metadata problems regarding a single species can affect the understanding not just of the species, but of wider ecological interactions. This thesis proposes a set of processes to help solve problems in metadata quality. While previous approaches concern one given aspect of the problem, the thesis provides an architecture and algorithms that encompass the whole cycle of managing biological observation metadata, which goes from acquiring data to retrieving database records. Our contributions are divided into two categories: (a) data enrichment and (b) data cleaning. Contributions in category (a) provide additional information for both missing attributes in existent records, and missing records for specific requirements. Our strategies use authoritative remote data sources and VGI (Volunteered Geographic Information) to enrich such metadata, providing missing information. Contributions in category (b) detect anomalies in biological observation metadata by performing spatial analyses that contrast location of the observations with authoritative geographic distribution maps. Thus, the main contributions are: (i) an architecture to retrieve biological observation records, which derives missing attributes by using external data sources; (ii) a geographical approach for anomaly detection and (iii) an approach for adaptive acquisition of VGI to fill out metadata gaps, using mobile devices and sensors. These contributions were validated by actual implementations, using as case study the challenges presented by the management of biological observation metadata of the Fonoteca Neotropical Jacques Vielliard (FNJV), one of the top 10 animal sound collections in the world (AU) | |
| FAPESP's process: | 11/19284-3 - Supporting the Collection and Curation of Biological Observation Databases |
| Grantee: | Daniel Cintra Cugler |
| Support Opportunities: | Scholarships in Brazil - Doctorate |