mSpace2.0 Architecture Documentation

by Daniel Alexander Smith on October 3rd, 2009

Over the next couple of weeks we’ll be documenting how the components of mSpace work, in preparation for the open source release of mSpace2.0, a complete rewrite of mSpace that powers sites such as the iPlayer mSpace.

Firstly, a short overview of the architecture, as shown in the diagram below (click for full size):

mSpace Architecture, as of September 2009

mSpace Architecture, as of September 2009

mSpace is made up of the following components:

  1. Semantic Web Import Engine
  2. Basic mSpace subsystem
    1. mSpace server
    2. mSpace front-end
  3. Pivoting subsystem

In summary, there is an “mSpace Maker” service that uses the “Facet Ontology” (more information coming soon) to describe how to gather and query RDF in order to generate an faceted view onto the data. A file of RDF that conforms to the Facet Ontology is submitted to the mSpace Maker, which indexes the source data RDF, and creates an mSpace.

The mSpace Server is a PHP/MySQL server-side component that is queried by the mSpace front-end, a JavaScript/HTML/CSS component that faces the users. These two components are due to be open sourced as soon as possible.

In the coming weeks a number of blog posts are planned which we hope will explain the core concepts of the various mSpace subsystems to help anyone who is interested in utilising the mSpace software.

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  1. Hi Ricky,Support of nigotean:I agree it doesn’t have nigotean keyword but it has nigotean operator, using filter and optional we can implement nigoteanSupport of Path Expression:This is available now.Predicates cannot have Properties:True but it can be achieved using proper ontology. I echo danbri.RDF inference Rule:In my view, SPARQL/RDF are best suited, for creating and traversing the graph. Its not good if you are doing computation.Using inference it can generate the more triple that can be accessed using the defined ontology.For example in your example we can add one more predicate “family income” and can put the computed income there either using direct logic or inference.

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