Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health
Aim: AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analys...
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description | Aim: AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to AquaticHealth.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so AquaticHealth.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, AquaticHealth.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location: Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods: Automated: AquaticHealth.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results: AquaticHealth.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite AquaticHealth.net. The Australian Sub-Committee for Aquatic Animal Health (SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses AquaticHealth.net to make forecasts—for example, used aquaculture equipment is a high-risk pathway for OsHV. AquaticHealth.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions: AquaticHealth.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method. |
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The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to AquaticHealth.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so AquaticHealth.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, AquaticHealth.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location: Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods: Automated: AquaticHealth.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results: AquaticHealth.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite AquaticHealth.net. The Australian Sub-Committee for Aquatic Animal Health (SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses AquaticHealth.net to make forecasts—for example, used aquaculture equipment is a high-risk pathway for OsHV. AquaticHealth.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions: AquaticHealth.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method.</description><identifier>ISSN: 1366-9516</identifier><identifier>EISSN: 1472-4642</identifier><identifier>DOI: 10.1111/ddi.12057</identifier><language>eng</language><publisher>Oxford: Blackwell Publishing Ltd</publisher><subject>Aggregation ; aquatic animal health ; Aquatic ecosystems ; Automation ; BIODIVERSITY RESEARCH ; biosecurity ; Blogs ; crowdsourcing ; Data analysis ; Disease outbreaks ; Diseases ; Emerging diseases ; Environmental monitoring ; Humans ; intelligence ; Marine ; Marine zoology ; risk analysis ; Search engines ; Search terms ; Social media ; Viral diseases</subject><ispartof>Diversity & distributions, 2013-05, Vol.19 (5-6), p.640-650</ispartof><rights>Copyright © 2013 John Wiley & Sons Ltd.</rights><rights>2013 John Wiley & Sons Ltd</rights><rights>Copyright © 2013 John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4257-49566d579fc9698ede4583a1aa8bb3aadc4cad6dd648295ce0e2963d6b59540d3</citedby><cites>FETCH-LOGICAL-c4257-49566d579fc9698ede4583a1aa8bb3aadc4cad6dd648295ce0e2963d6b59540d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/23479785$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/23479785$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,1417,11562,27924,27925,45574,45575,46052,46476,58017,58250</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1111%2Fddi.12057$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc></links><search><contributor>Yemshanov, Denys</contributor><contributor>Yemshanov, Denys</contributor><creatorcontrib>Lyon, Aidan</creatorcontrib><creatorcontrib>Grossel, Geoff</creatorcontrib><creatorcontrib>Burgman, Mark</creatorcontrib><creatorcontrib>Nunn, Mike</creatorcontrib><title>Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health</title><title>Diversity & distributions</title><addtitle>Diversity Distrib</addtitle><description>Aim: AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to AquaticHealth.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so AquaticHealth.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, AquaticHealth.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location: Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods: Automated: AquaticHealth.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results: AquaticHealth.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite AquaticHealth.net. The Australian Sub-Committee for Aquatic Animal Health (SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses AquaticHealth.net to make forecasts—for example, used aquaculture equipment is a high-risk pathway for OsHV. AquaticHealth.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions: AquaticHealth.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method.</description><subject>Aggregation</subject><subject>aquatic animal health</subject><subject>Aquatic ecosystems</subject><subject>Automation</subject><subject>BIODIVERSITY RESEARCH</subject><subject>biosecurity</subject><subject>Blogs</subject><subject>crowdsourcing</subject><subject>Data analysis</subject><subject>Disease outbreaks</subject><subject>Diseases</subject><subject>Emerging diseases</subject><subject>Environmental monitoring</subject><subject>Humans</subject><subject>intelligence</subject><subject>Marine</subject><subject>Marine zoology</subject><subject>risk analysis</subject><subject>Search engines</subject><subject>Search terms</subject><subject>Social media</subject><subject>Viral diseases</subject><issn>1366-9516</issn><issn>1472-4642</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp1kE1P3DAQhqOKSqWUQ39AJUu9lEPAib_i3srXFglagfg4WrP27OIlm7C2I9h_jyEtByTmMiO9zzuaeYvia0V3q1x7zvndqqZCfSg2K67qkkteb-SZSVlqUclPxecYF5RSxkS9WZir6Ls58V3C0GF6GdrWz7GzSFJPltDBHMnU9xHtEHxak-DjXfxJgFiISGIa3JrM-kBgNUDylkDnl9CSW4Q23X4pPs6gjbj9r28VV8dHlwe_y9O_k5ODX6el5bVQJddCSieUnlktdYMOuWgYVADNdMoAnOUWnHRO8qbWwiLFWkvm5FRowaljW8WPce996FcDxmSWPtr8CnTYD9FUTEjNKOM0o9_foIt-CF2-7pmigmslZKZ2RsqGPsaAM3Mf8l9hbSpqnqM2OWrzEnVm90b2wbe4fh80h4cn_x3fRscipj68OmrGlVaNyHo56j4mfHzVIdwZqZgS5ubPxND9m7Pr88m1uWBPEOyY5A</recordid><startdate>201305</startdate><enddate>201305</enddate><creator>Lyon, Aidan</creator><creator>Grossel, Geoff</creator><creator>Burgman, Mark</creator><creator>Nunn, Mike</creator><general>Blackwell Publishing Ltd</general><general>Blackwell Publishing</general><general>John Wiley & Sons, Inc</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>C1K</scope><scope>M7N</scope><scope>7QH</scope><scope>7U1</scope><scope>7U2</scope><scope>7UA</scope><scope>F1W</scope><scope>H95</scope><scope>H98</scope><scope>L.G</scope></search><sort><creationdate>201305</creationdate><title>Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health</title><author>Lyon, Aidan ; Grossel, Geoff ; Burgman, Mark ; Nunn, Mike</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4257-49566d579fc9698ede4583a1aa8bb3aadc4cad6dd648295ce0e2963d6b59540d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aggregation</topic><topic>aquatic animal health</topic><topic>Aquatic ecosystems</topic><topic>Automation</topic><topic>BIODIVERSITY RESEARCH</topic><topic>biosecurity</topic><topic>Blogs</topic><topic>crowdsourcing</topic><topic>Data analysis</topic><topic>Disease outbreaks</topic><topic>Diseases</topic><topic>Emerging diseases</topic><topic>Environmental monitoring</topic><topic>Humans</topic><topic>intelligence</topic><topic>Marine</topic><topic>Marine zoology</topic><topic>risk analysis</topic><topic>Search engines</topic><topic>Search terms</topic><topic>Social media</topic><topic>Viral diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lyon, Aidan</creatorcontrib><creatorcontrib>Grossel, Geoff</creatorcontrib><creatorcontrib>Burgman, Mark</creatorcontrib><creatorcontrib>Nunn, Mike</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Aqualine</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Water Resources Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Aquaculture Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Diversity & distributions</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lyon, Aidan</au><au>Grossel, Geoff</au><au>Burgman, Mark</au><au>Nunn, Mike</au><au>Yemshanov, Denys</au><au>Yemshanov, Denys</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health</atitle><jtitle>Diversity & distributions</jtitle><addtitle>Diversity Distrib</addtitle><date>2013-05</date><risdate>2013</risdate><volume>19</volume><issue>5-6</issue><spage>640</spage><epage>650</epage><pages>640-650</pages><issn>1366-9516</issn><eissn>1472-4642</eissn><abstract>Aim: AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to AquaticHealth.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so AquaticHealth.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, AquaticHealth.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location: Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods: Automated: AquaticHealth.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results: AquaticHealth.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite AquaticHealth.net. The Australian Sub-Committee for Aquatic Animal Health (SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses AquaticHealth.net to make forecasts—for example, used aquaculture equipment is a high-risk pathway for OsHV. AquaticHealth.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions: AquaticHealth.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method.</abstract><cop>Oxford</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/ddi.12057</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aggregation aquatic animal health Aquatic ecosystems Automation BIODIVERSITY RESEARCH biosecurity Blogs crowdsourcing Data analysis Disease outbreaks Diseases Emerging diseases Environmental monitoring Humans intelligence Marine Marine zoology risk analysis Search engines Search terms Social media Viral diseases |
title | Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health |
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