Improving biodiversity data retrieval through semantic search and ontologies
Due to the increased amount of available biodiversity data, many biodiversity research institutions are now making their databases openly available on the web. Researchers in the field use this databases to extract new knowledge and also share their own discoveries. However, when these researchers n...
| Autor principal: | Amanqui, Flor K. |
|---|---|
| Outros Autores: | Serique, Kleberson J.A., Cardoso, Silvio Domingos, Santos, José L.dos, Albuquerque, Andréa Corrêa Flôres, Moreira, Dilvan de Abreu |
| Grau: | Trabalho Apresentado em Evento |
| Idioma: | English |
| Publicado em: |
Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/20018 |
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oai:repositorio:1-20018 |
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dspace |
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oai:repositorio:1-20018 Improving biodiversity data retrieval through semantic search and ontologies Amanqui, Flor K. Serique, Kleberson J.A. Cardoso, Silvio Domingos Santos, José L.dos Albuquerque, Andréa Corrêa Flôres Moreira, Dilvan de Abreu Biodiversity Deforestation Motion Picture Experts Group Standards Ontology Search Engines Societies And Institutions Space Research Biodiversity Datum Keyword-based Search National Research Institutes Ontology Terms Precision And Recall Research Institutions Search Accuracy Semantic Search Semantic Web Due to the increased amount of available biodiversity data, many biodiversity research institutions are now making their databases openly available on the web. Researchers in the field use this databases to extract new knowledge and also share their own discoveries. However, when these researchers need to find relevant information in the data, they still rely on the traditional search approach, based on text matching, that is not appropriate to be used in these large amounts of heterogeneous biodiversity's data, leading to search results with low precision and recall. We present a new architecture that tackle this problem using a semantic search system for biodiversity data. Semantic search aims to improve search accuracy by using ontologies to understand user objectives and the contextual meaning of terms used in the search to generate more relevant results. Biodiversity data is mapped to terms from relevant ontologies, such as Darwin Core, DBpedia, Ontobio and Catalogue of Life, stored using semantic web formats and queried using semantic web tools (such as triple stores). A prototype semantic search tool was successfully implemented and evaluated by users from the National Research Institute for the Amazon (INPA). Our results show that the semantic search approach has a better precision (28[%] improvement) and recall (25[%] improvement) when compared to keyword based search, when used in a big set of representative biodiversity data (206,000 records) from INPA and the Emilio Gueldi Museum in Pará (MPEG). We also show that, because the biodiversity data is now in semantic web format and mapped to ontology terms, it is easy to enhance it with information from other sources, an example using deforestation data (from the National Institute of Space Research - INPE) to enrich collection data is shown. © 2014 IEEE. 2020-06-16T17:31:43Z 2020-06-16T17:31:43Z 2014 Trabalho Apresentado em Evento https://repositorio.inpa.gov.br/handle/1/20018 10.1109/WI-IAT.2014.44 en Volume 1, Pags. 726-731 Restrito Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014 |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
Biodiversity Deforestation Motion Picture Experts Group Standards Ontology Search Engines Societies And Institutions Space Research Biodiversity Datum Keyword-based Search National Research Institutes Ontology Terms Precision And Recall Research Institutions Search Accuracy Semantic Search Semantic Web |
| spellingShingle |
Biodiversity Deforestation Motion Picture Experts Group Standards Ontology Search Engines Societies And Institutions Space Research Biodiversity Datum Keyword-based Search National Research Institutes Ontology Terms Precision And Recall Research Institutions Search Accuracy Semantic Search Semantic Web Amanqui, Flor K. Improving biodiversity data retrieval through semantic search and ontologies |
| topic_facet |
Biodiversity Deforestation Motion Picture Experts Group Standards Ontology Search Engines Societies And Institutions Space Research Biodiversity Datum Keyword-based Search National Research Institutes Ontology Terms Precision And Recall Research Institutions Search Accuracy Semantic Search Semantic Web |
| description |
Due to the increased amount of available biodiversity data, many biodiversity research institutions are now making their databases openly available on the web. Researchers in the field use this databases to extract new knowledge and also share their own discoveries. However, when these researchers need to find relevant information in the data, they still rely on the traditional search approach, based on text matching, that is not appropriate to be used in these large amounts of heterogeneous biodiversity's data, leading to search results with low precision and recall. We present a new architecture that tackle this problem using a semantic search system for biodiversity data. Semantic search aims to improve search accuracy by using ontologies to understand user objectives and the contextual meaning of terms used in the search to generate more relevant results. Biodiversity data is mapped to terms from relevant ontologies, such as Darwin Core, DBpedia, Ontobio and Catalogue of Life, stored using semantic web formats and queried using semantic web tools (such as triple stores). A prototype semantic search tool was successfully implemented and evaluated by users from the National Research Institute for the Amazon (INPA). Our results show that the semantic search approach has a better precision (28[%] improvement) and recall (25[%] improvement) when compared to keyword based search, when used in a big set of representative biodiversity data (206,000 records) from INPA and the Emilio Gueldi Museum in Pará (MPEG). We also show that, because the biodiversity data is now in semantic web format and mapped to ontology terms, it is easy to enhance it with information from other sources, an example using deforestation data (from the National Institute of Space Research - INPE) to enrich collection data is shown. © 2014 IEEE. |
| format |
Trabalho Apresentado em Evento |
| author |
Amanqui, Flor K. |
| author2 |
Serique, Kleberson J.A. Cardoso, Silvio Domingos Santos, José L.dos Albuquerque, Andréa Corrêa Flôres Moreira, Dilvan de Abreu |
| author2Str |
Serique, Kleberson J.A. Cardoso, Silvio Domingos Santos, José L.dos Albuquerque, Andréa Corrêa Flôres Moreira, Dilvan de Abreu |
| title |
Improving biodiversity data retrieval through semantic search and ontologies |
| title_short |
Improving biodiversity data retrieval through semantic search and ontologies |
| title_full |
Improving biodiversity data retrieval through semantic search and ontologies |
| title_fullStr |
Improving biodiversity data retrieval through semantic search and ontologies |
| title_full_unstemmed |
Improving biodiversity data retrieval through semantic search and ontologies |
| title_sort |
improving biodiversity data retrieval through semantic search and ontologies |
| publisher |
Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014 |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/20018 |
| _version_ |
1787142449164976128 |
| score |
11.755432 |