PADI-web corpus: Labeled textual data in animal health domain
Monitoring animal health worldwide, especially the early detection of outbreaks of emerging pathogens, is one of the means of preventing the introduction of infectious diseases in countries (Collier et al., 2008) [3]. In this context, we developed PADI-web, a Platform for Automated extraction of ani...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-02-01
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| Series: | Data in Brief |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340918316032 |
| _version_ | 1811310111239438336 |
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| author | Julien Rabatel Elena Arsevska Mathieu Roche |
| author_facet | Julien Rabatel Elena Arsevska Mathieu Roche |
| author_sort | Julien Rabatel |
| collection | DOAJ |
| description | Monitoring animal health worldwide, especially the early detection of outbreaks of emerging pathogens, is one of the means of preventing the introduction of infectious diseases in countries (Collier et al., 2008) [3]. In this context, we developed PADI-web, a Platform for Automated extraction of animal Disease Information from the Web (Arsevska et al., 2016, 2018). PADI-web is a text-mining tool that automatically detects, categorizes and extracts disease outbreak information from Web news articles. PADI-web currently monitors the Web for five emerging animal infectious diseases, i.e., African swine fever, avian influenza including highly pathogenic and low pathogenic avian influenza, foot-and-mouth disease, bluetongue, and Schmallenberg virus infection. PADI-web collects Web news articles in near-real time through RSS feeds. Currently, PADI-web collects disease information from Google News because of its international and multiple language coverage. We implemented machine learning techniques to identify the relevant disease information in texts (i.e., location and date of an outbreak, affected hosts, their numbers and clinical signs). In order to train the model for Information Extraction (IE) from news articles, a corpus in English has been manually labeled by domain experts. This labeled corpus (Rabatel et al., 2017) is presented in this data paper. |
| first_indexed | 2024-04-13T09:53:46Z |
| format | Article |
| id | doaj.art-60c3e36215074d44a9cd4ac870cd56a6 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-13T09:53:46Z |
| publishDate | 2019-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-60c3e36215074d44a9cd4ac870cd56a62022-12-22T02:51:31ZengElsevierData in Brief2352-34092019-02-0122643646PADI-web corpus: Labeled textual data in animal health domainJulien Rabatel0Elena Arsevska1Mathieu Roche2Cirad, Montpellier, FranceASTRE, Cirad, INRA, Montpellier, France; Cirad, Montpellier, FranceTETIS, Univ. of Montpellier, AgroParisTech, Cirad, CNRS, Irstea, Montpellier, France; Cirad, Montpellier, France; Corresponding author.Monitoring animal health worldwide, especially the early detection of outbreaks of emerging pathogens, is one of the means of preventing the introduction of infectious diseases in countries (Collier et al., 2008) [3]. In this context, we developed PADI-web, a Platform for Automated extraction of animal Disease Information from the Web (Arsevska et al., 2016, 2018). PADI-web is a text-mining tool that automatically detects, categorizes and extracts disease outbreak information from Web news articles. PADI-web currently monitors the Web for five emerging animal infectious diseases, i.e., African swine fever, avian influenza including highly pathogenic and low pathogenic avian influenza, foot-and-mouth disease, bluetongue, and Schmallenberg virus infection. PADI-web collects Web news articles in near-real time through RSS feeds. Currently, PADI-web collects disease information from Google News because of its international and multiple language coverage. We implemented machine learning techniques to identify the relevant disease information in texts (i.e., location and date of an outbreak, affected hosts, their numbers and clinical signs). In order to train the model for Information Extraction (IE) from news articles, a corpus in English has been manually labeled by domain experts. This labeled corpus (Rabatel et al., 2017) is presented in this data paper.http://www.sciencedirect.com/science/article/pii/S2352340918316032 |
| spellingShingle | Julien Rabatel Elena Arsevska Mathieu Roche PADI-web corpus: Labeled textual data in animal health domain Data in Brief |
| title | PADI-web corpus: Labeled textual data in animal health domain |
| title_full | PADI-web corpus: Labeled textual data in animal health domain |
| title_fullStr | PADI-web corpus: Labeled textual data in animal health domain |
| title_full_unstemmed | PADI-web corpus: Labeled textual data in animal health domain |
| title_short | PADI-web corpus: Labeled textual data in animal health domain |
| title_sort | padi web corpus labeled textual data in animal health domain |
| url | http://www.sciencedirect.com/science/article/pii/S2352340918316032 |
| work_keys_str_mv | AT julienrabatel padiwebcorpuslabeledtextualdatainanimalhealthdomain AT elenaarsevska padiwebcorpuslabeledtextualdatainanimalhealthdomain AT mathieuroche padiwebcorpuslabeledtextualdatainanimalhealthdomain |