Geosemantically-enhanced PubMed queries using the GeoNames ontology and Web Services

Maged N. Kamel Boulos

doi:10.1109/IGARSS.2012.6350722

Geosemantically-enhanced PubMed queries using the GeoNames ontology and Web Services

Maged N. Kamel Boulos

UHI Moray

Research output: Contribution to conference › Other › peer-review

1 Citation (Scopus)

Abstract

PubMed is a popular biomedical bibliographic database curated by the US National Library of Medicine. Limitations may be encountered when querying PubMed for studies from or about a particular geographic location. For example, if a citation record does not include the word `Canada' but instead includes `Ontario' as the named place in its text, a PubMed query to find all studies conducted in Canada using only the keyword `Canada' will not be able to retrieve that particular record. We propose that a GeoNames-powered PubMed search has the potential of solving such issues. By bringing in the “intelligence” of a geographic ontology and the ability to reason with place names (e.g., recognise `Ontario' as a province of `Canada'), a search engine can infer implicit meanings in the queried records that are not directly mentioned as free text or as keyword terms in either the citation records or their metadata.

Original language	English
Pages	2891-2893
Number of pages	3
DOIs	https://doi.org/10.1109/IGARSS.2012.6350722
Publication status	Published - Jul 2012
Event	IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium - Munich, Germany, United Kingdom Duration: 22 Jul 2012 → 27 Jul 2012

Conference

Conference	IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium
Country/Territory	United Kingdom
City	Munich, Germany
Period	22/07/12 → 27/07/12

Access to Document

10.1109/IGARSS.2012.6350722

http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6350722

Cite this

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title = "Geosemantically-enhanced PubMed queries using the GeoNames ontology and Web Services",

abstract = "PubMed is a popular biomedical bibliographic database curated by the US National Library of Medicine. Limitations may be encountered when querying PubMed for studies from or about a particular geographic location. For example, if a citation record does not include the word `Canada' but instead includes `Ontario' as the named place in its text, a PubMed query to find all studies conducted in Canada using only the keyword `Canada' will not be able to retrieve that particular record. We propose that a GeoNames-powered PubMed search has the potential of solving such issues. By bringing in the “intelligence” of a geographic ontology and the ability to reason with place names (e.g., recognise `Ontario' as a province of `Canada'), a search engine can infer implicit meanings in the queried records that are not directly mentioned as free text or as keyword terms in either the citation records or their metadata.",

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doi = "10.1109/IGARSS.2012.6350722",

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AU - Kamel Boulos, Maged N.

PY - 2012/7

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N2 - PubMed is a popular biomedical bibliographic database curated by the US National Library of Medicine. Limitations may be encountered when querying PubMed for studies from or about a particular geographic location. For example, if a citation record does not include the word `Canada' but instead includes `Ontario' as the named place in its text, a PubMed query to find all studies conducted in Canada using only the keyword `Canada' will not be able to retrieve that particular record. We propose that a GeoNames-powered PubMed search has the potential of solving such issues. By bringing in the “intelligence” of a geographic ontology and the ability to reason with place names (e.g., recognise `Ontario' as a province of `Canada'), a search engine can infer implicit meanings in the queried records that are not directly mentioned as free text or as keyword terms in either the citation records or their metadata.

AB - PubMed is a popular biomedical bibliographic database curated by the US National Library of Medicine. Limitations may be encountered when querying PubMed for studies from or about a particular geographic location. For example, if a citation record does not include the word `Canada' but instead includes `Ontario' as the named place in its text, a PubMed query to find all studies conducted in Canada using only the keyword `Canada' will not be able to retrieve that particular record. We propose that a GeoNames-powered PubMed search has the potential of solving such issues. By bringing in the “intelligence” of a geographic ontology and the ability to reason with place names (e.g., recognise `Ontario' as a province of `Canada'), a search engine can infer implicit meanings in the queried records that are not directly mentioned as free text or as keyword terms in either the citation records or their metadata.

U2 - 10.1109/IGARSS.2012.6350722

DO - 10.1109/IGARSS.2012.6350722

M3 - Other

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EP - 2893

T2 - IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium

Y2 - 22 July 2012 through 27 July 2012

ER -

Geosemantically-enhanced PubMed queries using the GeoNames ontology and Web Services

Abstract

Conference

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