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Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
Biodiversity Informatics on the Semantic Web
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Biodiversity Informatics on the Semantic Web

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  • Today I am going to give you a brief overview of the semantic web and how it can be useful to biodiversity informatics.\n
  • Here is a traditional table in a spreadsheet. It is a list of the various species and includes ID field that is used to connect it to another table for locations.\nIn this we have a representation for taxa and a representation for location that are often specific to this and only this database.\nOther similar databases that might be useful will have different names for the fields, and different names within the fields for what is often the same entity. \nWhat you have is a data island that knows nothing else about potentially related data and shares nothing about itself to other data sets.\n
  • The result of this structure are large islands of data which are difficult to integrate. \nEach of these gains little value from other data sets and are of little value to other datasets.\n
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  • 1.Use URIs as names for things\nUse HTTP URIs so that people can look up those names.\nWhen someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)\nInclude links to other URIs. so that they can discover more things.\n\n
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  • Linked Data is data that is linked together following the principles laid out by Tim Berners-Lee.\nLinked Open Data is Linked Data that is open and accessible.\nThere are ways to query this knowledge base, but you can also create your own subset for your own knowledge base.\n
  • Since all these data sets are connected you can do some interesting things.\nHere is something I just tried this Wednesday.\nMy data set is linked to Wikipedia through Dbpedia I can easily pull in all the images for my species that are in Wikipedia.\nThe RDF icons are for images that are too large to be displayed.\n
  • Your data set can continue to exist in its current relational database form, but you need to expose it to the semantic web in a different form\n
  • The semantic web represents statements as triples.\nTriples consist of a subject predicate and object.\nAn english language version of a triple might look something like this. \n“Ochlerotatus triseriatus occurrence in La Crosse County, WI\n
  • I can now use these unique identifiers to make machine processable statements about these entities.\nThe statement “Ochlerotatus triseriatus is expected in La Crosse County, WI”\nCan now be represented as the following triple\n <http://lod.taxonconcept.org/ses/iuCXz#Species>\n <http://lod.taxonconcept.org/ontology/txn.owl#isExpectedIn>\n <http://sws.geonames.org/5258961/> .\n It is important to recognize that these statements are part of the database, but they are not there for humans to process, they are there so that it is clear to this system and others what we actually mean.\n
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  • Here are the different ways of representing that original triple.\n
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  • Triple or Quadstores have their own SQL-like query language called SPARQL\n
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  • Improvements in the quantity and quality of LOD data sets.\nImproved Alignment of Vocabularies\nImprovements in SPARQL and Quadstores\nHuman and Machine Interpretable Views Merged in RDFa\nBetter Visualization and Analysis Tools\n
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