RDF - Semantic Web Standards. Overview RDF is a standard model for data interchange on the Web.
RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a “triple”).
Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications. This linking structure forms a directed, labeled graph, where the edges represent the named link between two resources, represented by the graph nodes. Recommended Reading The RDF 1.1 specification consists of a suite of W3C Recommendations and Working Group Notes, published in 2014. A number of textbooks have been published on RDF and on Semantic Web in general. Discussions on a possible next version of RDF. Triplestore. Much like a relational database, one stores information in a triplestore and retrieves it via a query language.
Unlike a relational database, a triplestore is optimized for the storage and retrieval of triples. In addition to queries, triples can usually be imported/exported using Resource Description Framework (RDF) and other formats. Some triplestores can store billions of triples. Implementation Some triplestores have been built as database engines from scratch, while others have been built on top of existing commercial relational database engines (i.e. List of implementations Technical overview The following table is an overview of available triplestores, their technical implementation, support for the SPARQL World Wide Web Consortium (W3C) recommendations, and available application programming interfaces (API). See also Freebase uses a triplestore called graphdNamed graph a.k.a. References External links Large-scale RDF Graph Visualization Tools.
AI3 Assembles 26 Candidate Tools The pending UMBEL subject concept “backbone” ontology will involve literally thousands of concepts.
In order to manage and view such a large structure, a concerted effort to find suitable graph visualization software was mounted. This post presents the candidate listing, as well as some useful starting resources and background information. A subsequent post will present the surprise winner of our evaluation. Starting Resources Various Example Visualizations For grins, you may also like to see various example visualizations, most with a large-graph bent: Software Options Here is the listing of 26 candidate graph visualization programs assembled to date: Cytoscape – this tool, based on GINY and Piccolo (see below), is under active use by the bioinformatics community and highly recommended by Bio2RDF.org GINY implements a very innovative system for sub-graphing and allows for stunning visuals.
Headline: Large-scale RDF Graph Visualization Tools alternativeHeadline: Cytoscape: Hands-down Winner for Large-scale Graph Visualization. I still never cease to be amazed at how wonderful and powerful tools are so often and easily overlooked.
The most recent example is Cytoscape, a winner in our recent review of more than 25 tools for large-scale RDF graph visualization. We began this review because the UMBEL subject concept “backbone” ontology will involve literally thousands of concepts. Graph visualization software suitable to very large graphs would aid UMBEL’s construction and refinement. Cytoscape describes itself as a bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data. Cytoscape is partially based on GINY and Piccolo, among other open-source toolkits.
Cytoscape was first brought to our attention by François Belleau of Bio2RDF.org. Requirements We had a number of requirements and items on our wish list prior to beginning our review. Features and Attractions Other Cytoscape Resources Plugins Initial Use Tips. Cytoscape: An Open Source Platform for Complex Network Analysis and Visualization. Tutorial.