Tracing Networks Collaborative Working Environment Architecture

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TN CWE Architecture

TN Architecture

The following paragraph describes a draft version of 4-layer architecture of the system.

  • User in various research teams can use any available databases (e.g. Microsoft Access, Microsoft Excel etc) on the laptop or desktop with their own database structures. A cross-subproject unified DB schema is not required.

Web UI Layer

From a user’s point of view, user will only directly interact with Web UI, which provides these interfaces:

Database backup/restore interface: user will be able to synchronise local database with a centralised repository through Generic DB importer as soon as Internet connection is available.

  • Cross-project mashup interface: cross-project mashup interface component will combine, aggregate data from different sub-projects and show on a web interface to allow users to explore implicit relations or interactions in the social network \cite{socialnetwork}.
  • Cross-project advanced search interface: this interface provides a sophisticated but user friendly, easy-to-use search engine to query and access complex data across different sub projects.

DB Adaptor Layer

  • DB Adaptor Layer consists of a Relational Database (RDB) and SQL Exporter.
  • user's’ local databases are synchronised and stored separately within RDB.
  • SQL exporter should be able to export data as SQL thus user should be able to restore from backups.
  • changes on local database schema should be notified in advanced

Ontological Mapping and Data Mashup Layer

  • in this layer, as an extension of CIDO Conceptional Reference Model,a generic Tracing Networks OWL/RDF ontology is defined to provide a logical infrastructure to support classification and analysis/interpretation of data.
  • schemata/class level: RDB schemata will then be mapped to OWL/RDFS ontology via D2RQ Mapping Language.
  • instance Level: Records stored in the RDB can be classified using a DL-reasoner (Description Logic reasoner), which is designed to support tasks of classification and consistency checking.
  • all information in the RDB including schema and instances will then be converted to an ontology-based triple store (as in-memory model or persistent storage subject to our requirement). In addition, a RDF exporter is also avaliable here to enhance compatibility with other semantic web analysis tools.

Data Access and Visualization Layer

  • application can access triple store using raw SPARQL query, or through Advanced Search Interface on Web UI layer, a powerful query builder should be able to help user to create queries dynamically.
  • a deductive rule-based reasoner is also used in conjunction with SPARQL query engine to discover implicit information.
  • Flex diagrammer will be used to visualize the data and display interactive diagram for the search results
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