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nano publication as a way to explain rich triples

Created: 2009-10-23 07:32:36 | Last updated: 2009-10-25 20:38:34

Credits: Barend Jan Velterop Concept Web Alliance (general)

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: application/x-download

Comments: 0 | Viewed: 81 times | Downloaded: 87 times

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Digital Multimedia Repositories Ontology (DMRO) and ...

Created: 2012-01-29 16:35:26 | Last updated: 2012-01-29 16:38:25

Credits: Lawrynka

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: ZIP archive

Comments: 0 | Viewed: 218 times | Downloaded: 41 times

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HCLS - Semantic Web for Health Care and Li...

Unique name: hcls
Created: Friday 01 May 2009 17:12:56 (UTC)

8 shared items   |   0 announcements

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Concept Web Alliance (general)

Unique name: CWA
Created: Monday 27 July 2009 12:48:15 (UTC)

4 shared items   |   2 announcements

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CWA Working Group 2.6: Storage and mainten...

Created: Friday 27 November 2009 19:39:12 (UTC)

0 shared items   |   0 announcements

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NBIC Life Science Information Management 2013

Created: Tuesday 18 June 2013 15:51:17 (UTC)

2 shared items   |   0 announcements

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myExperiment paper for Concurrency Practice and Expe...

Created: 2009-04-10 13:41:56 | Last updated: 2009-04-14 08:38:09

8 items in this pack

Comments: 1 | Viewed: 181 times | Downloaded: 38 times

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Presentation: SKOS, Past, Present and Future

Created: 2010-06-15 11:18:56 | Last updated: 2010-07-17 08:22:00

3 items in this pack

Comments: 0 | Viewed: 36 times | Downloaded: 12 times

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BioSemantics Concept Profile Generation Workflows

Created: 2014-06-04 12:31:09 | Last updated: 2014-06-04 13:01:44

9 items in this pack

Comments: 0 | Viewed: 224 times | Downloaded: 0 times

Mining Semantic Web data using FastMap - E... (1)

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This workflow describes how to learn from the Semantic Web's data. The input to the workflow is a feature vector developed from a RDF resource. The loaded example set is then divided into training and test parts. These sub-example sets are used by the FastMap operators (encapsulate the FastMap data transformation technique), which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve classfica...

Created: 2011-06-25 | Last updated: 2011-06-25

Mining Semantic Web data using Corresponde... (1)

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This workflow describes how to learn from the Semantic Web's data using a data transformation algorithm 'Correspondence Analysis'. The input to the workflow is a feature vector developed from a RDF resource. The loaded example set is divided into training and test parts. These sub-example sets are used by the Correspondence Analysis operators (encapsulate the Correspondence Analysis data transformation technique) which processes each feature at a time and transform the data into a different...

Created: 2011-06-25 | Last updated: 2011-06-25

Mining Semantic Web data using Corresponde... (1)

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This workflow will explain that how an example set can be extracted from an RDF resource using the provided SPARQL query. This example set is then divided into training and test parts. These sub-example sets are used by the Correspondencce Analysis operators (encapsulate the Correspondencce Analysis data transformation technique) which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve clas...

Created: 2011-06-25 | Last updated: 2011-06-25

Semantic clustering (with AHC) of SPARQL q... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Common classes" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". ...

Created: 2012-01-29 | Last updated: 2012-01-29

Semantic clustering (with k-medoids) of SP... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". The SPARQL query is entered in a parameter of "SPARQL selector" operator. The clustering operator (k-medoids) allows to specify which of the query variables are to be used as clustering criteria. If more ...

Created: 2012-01-29

Semantic clustering (with alpha-clustering... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Epistemic" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". This ...

Created: 2012-01-29 | Last updated: 2012-01-30

Loading OWL files (RDF version of videolec... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/). Operator "Build knowledge base" is responsible for collecting data either from OWL files or SPARQL endpoints or RDF repositories and provide it to the subsequent operators in a workflow. In this workflow it is parametrized in this way, that is builds a Sesame/OWLIM repository from the files specified in "Load file" operators. Paths to OWL files are specified as parameter va...

Created: 2012-01-29 | Last updated: 2012-01-29

Get HPO concept label and synonym (1)

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This workflow queries bioportal for label and synonyms of Human Phenotype Ontology concepts.Note: this workflow requires a BioPortal API key to work. It can be requested from bioportal.bioontology.org

Created: 2014-10-20 | Last updated: 2014-10-20

Credits: Rajireturn BioSemantics