Archive for the ‘Linked Data’ Category

Using Linked Data to provide a different perspective on Software Architecture

Saturday, December 17th, 2011

As outlined in my previous post Linked Data and the SOA Software Development Process I am interested in using Linked Data to provided a more detailed view of  SOA services.

A coupled of scenarios during the past week highlighted the value of the approach and also that it would benefit with extending the scope to include more information about the consumers of the SOA services and also the external data sources (in particular databases) used by the SOA services.

Both scenarios involved setting up environments for the development and testing of new functionality involving a number of different systems, with each system needing to be deployed at a specific version level.

The first scenario related to the software versions. The UML diagrams presented to describe the architecture were at too high a level to show the actual dependencies, but to add the level of detail needed would have made the diagrams too busy.

Although not yet complete the work already done to provide a Linked Data perspective of the SOA services enabled a more fined grained view of the actual dependencies.  Knowing what the specific lower level dependencies were resulted in more flexibility with the actual deployment. In particular work could start on developing the new functionality for one component since it was not going to be affected by proposed changes in another component. On the original UML diagram both components were shown as requiring changes. The Linked Data perspective provided enough additional detail to see that the changes could happen in parallel.

The second scenario related to finding the owners of external data sources so that we could determine if they were available for use in a given test environment. Adding this ownership information to our  Linked Data repository would speed up this part of the process in the future.

Linked Data and the SOA Software Development Process

Thursday, November 17th, 2011

We have quite a rigorous SOA software development process however the full value of the collected information is not being realized because the artifacts are stored in disconnected information silos. So far attempts to introduce tools which could improve the situation (e.g. zAgile Teamwork and Semantic Media Wiki) have been unsuccessful, possibly because the value of a Linked Data approach is not yet fully appreciated.

To provide an example Linked Data view of the SOA services and their associated artifacts I created a prototype consisting of  Sesame running on a Tomcat server with Pubby providing the Linked Data view via the Sesame SPARQL end point. TopBraid was connected directly to the Sesame native store (configured via the Sesame Workbench) to create a subset of services sufficient to demonstrate the value of publishing information as Linked Data. In particular the prototype showed how easy it became to navigate from the requirements for a SOA service through to details of its implementation.

The  prototype also highlighted that auto generation of the RDF graph (the data providing the Linked Data view) from the actual source artifacts would be preferable to manual entry, especially if this could be transparently integrated with the current software development process. This is has become the focus of the next step, automated knowledge extraction from the source artifacts.


Key artifact types of our process include:

A Graph of Concepts and Instances

There is a rich graph of relationships linking the things described in the artifacts listed above. For example the business entities defined in the UML analysis model are the subject of the service and service operations defined in the Service Contracts. The service and service operations are mapped to the WSDLs which utilize the Xml Schema’s that provide an XML view of business entities. The JAX-WS implementations are linked to the WSDLs and Xml Schema’s and deployed to the Oracle Weblogic Application Server where the configuration files list the external dependencies. The log files and defects link back to specific parts of the code base (Subversion revisions) within the context of specific service operations. The people associated with the different artifacts can often be determined from artifact meta-data.

RDF, OWL and Linked Data are a natural fit for modelling and viewing this graph since there is a mix of concepts plus a lot of instances, many of whom already have a HTTP representation. Also the graph contains a number of transitive relationships , (for example a WSDL may import an Xml Schema which in turn imports another Xml Schema etc …) promoting the use of the owl:TransitiveProperty to help obtain a full picture of all the dependencies a component may have.

Knowledge Extraction

Another advantage of the RDF, OWL, Linked Data approach is the utilization of unique URIs for identifying concepts and instances. This allows information contain in one artifact, e.g. a WSDL, to be extracted as RDF triples which would later be combined with the RDF triples extracted from the JAX-WS annotation of Java source code. The combined RDF triples tell us more about the WSDL and its Java implementation than could be derived from just one of the artifacts.

We have made some progress with knowledge extraction but this is still definitely a work in progress. Sites such as ConverterToRdf, RDFizers and the Virtuoso Sponger provide tools and information on generating RDF from different artifact types. Part of the current experimentation is around finding tools that can be transparently layered over the top of the current software development process. Finding the best way to extract the full set of desired RDF triples from Microsoft Word documents is also proving problematic since some natural language processing is required.

Tools currently being evaluated include:

The Benefits of Linked Data

The prototype showed the benefits of Linked Data for navigating from the requirements for a SOA service through to details of its implementation. Looking at all the information that could be extracted leads on to a broader view of the benefits Linked Data would bring to the SOA software development process.

One specific use being planned is the creation of a Service Registry application providing the following functionality:

  • Linking the services to the implementations running in a given environment, e.g. dev, test and production. This includes linking the specific versions of the requirement, design or implementation artifacts and detailing the runtime dependencies of each service implementation.
  • Listing the consumers of each service and providing summary statistics on the performance, e.g. daily usage figures derived from audit logs.
  • Providing a list of who to contact when a service is not available. This includes notifying consumers of a service outage and also contacting providers if a service is being affected by an external component being offline, e.g. a database or an external web service.
  • Search of the services by different criteria, e.g. business entity
  • Tracking the evolution of services and being able to assist with refactoring, e.g answering questions such as “Are there older versions of the Xml Schemas that can be deprecated?”
  • Simplify the running of a specific Soapui test case for a service operation in a given environment.
  • Provide the equivalent of a class lookup that includes all project classes plus all required infrastructure classes and returns information such as the jar file the class is contained in and JIRA and Subversion information.

Developing a Semantic Web Strategy

Tuesday, August 10th, 2010

In the last chapter of his book “Pull: The Power of the Semantic Web to Transform Your Business” David Siegel outlines some steps for developing a successful Semantic Web strategy for your business or organization.

One approach that worked for me recently was to organize a meeting titled “Developing a Semantic Web Strategy”  and invite along developers, architects, analysts and managers. This was in the context of a government organization and the managers were from the applications development area.

Sharing out books like Semantic Web for the Working Ontologist, Semantic Web For Dummies, Programming the Semantic Web and Semantic Web Programming prior to the meeting helped people get familiar with concepts like URIs as names for things, RDF, RDFS, OWL, SPARQL and RDFa.

To highlight how rapidly the Web of Data is evolving and the amount of information now being published as Linked Open Data, I stepped through Mark Greaves excellent presentation The Maturing Semantic Web: Lessons in Web-Scale Knowledge Representation.

During the meeting I took a business strategy first, technology second approach, taking the time to explore how an approach that has worked for someone else might fit with our organization.

Areas explored included:

Enterprise Modeling

I spent some time comparing RDF / OWL modeling with the UML modeling, highlighting how URIs enable modeling across distributed information sources without the need to consolidate everything in a central repository like you do with UML tools.

Also touched on OWL features such as:

Because it is a government department I highlighted the Federal Enterprise Architecture Reference Model Ontology (FEA-RMO) and how such an ontology could be used to map a parliamentary initiative to the software providing its implementation.

Open Government

Given the current trend for governments to make datasets freely available I presented the Linked Data approaches taken by and as examples to follow in this area.

The business case for Linked Data in this scenario is that Linked Data is seen as the best available approach for publishing data in hugely diverse and distributed environments, in a gradual and sustainable way (see Why Linked Data for for details).

RDFa Based Integration

One example that struck a chord was RDFa and Linked Data in UK Government Websites where job vacancy details  from different sites can easily be combined since each web site publishes their web pages using HTML with RDFa added to annotate the job vacancy. Using RDFa allows the same page to be read as either HTML or RDF. The end result is that integration can be achieved with minimal changes to the original sites.

Search Engine Optimisation (SEO)

For anyone advertising products and services online the business strategy to follow is the example set by which describes its stores and products using the Good Relations ontology and embeds these descriptions into its web pages using RDFa, increasing search engine traffic by 30%.

Enterprise Web of Data

Within our software development process, from project inception to production release and subsequent maintenance release, information is being copied and duplicated in a number of different places. Silos abound, in the form of word documents, spread sheets and the sticky notes that are part of the “Agile” process. There is some good information on our wiki pages but it is unstructured and not machine readable.

The information that forms our internal processes fails David Siegel’s Semantic Web Acid Test:

  • It’s not semantic and
  • It’s not on the web.

Introducing a Semantic Wiki such as Semantic MediaWiki, to hold project information and link this information to other datasources was raised as a candidate for a semantic web proof of concept.


Just scheduling the meeting was in itself a successful outcome since it started discussion around the role Semantic Web technologies could play in our organization. For a number of people, including the Applications Development manager, this is new technology and they need time to absorb it but the end result was agreement that it was technology that couldn’t be ignored.

In order to gain some practical experience two internal prototypes were agreed to,  both with practical value for the organization.

The first is a small application that will show the full set of runtime dependencies for a given software component as well as the other components affected when the specified component is changed. The application will be based on a simple ontology that defines dependencies between components using the owl:TransitiveProperty and uses a reasoner (e.g. Pellet) to infer the full set of dependencies for a component.

The second prototype will trial Semantic MediaWiki for project management (potentially using the Teamwork Ontology). The longer term view is customize Semantic MediaWiki to include artifacts created as part of the software development process, addressing some of the silo problems found in our current internal enterprise web of data.

Once practical knowledge has been gained from the internal prototypes a meeting will be scheduled with the Enterprise Architecture team to canvas the establishment of a wider vision for the use of Linked Data and Semantic Web technologies, potentially leading to its use on the public web sites, actively publishing to the Web of Data.

Understanding the OpenCalais RDF Response

Saturday, September 26th, 2009

I’m using an XML version of an article published by Scoop in February 2000, Senior UN Officials Protest UN Sanctions On Iraq, to understand the OpenCalais RDF response as part of a larger project of linking extracted entities to existing Linked Data datasets.

OpenCalais uses natural language processing (NLP), machine learning and other methods to analyze content and return the entities it finds, such as the cities, countries and people with dereferenceable Linked Data style URIs. The entity types are defined in the OpenCalais RDF Schemas.

When I submit the content to the OpenCalais REST web service (using the default RDF response format) an RDF document is returned. Opened below with TopBraid Composer a portion of the input content and some of the entity types OpenCalais can detect is shown. The numbers in brackets indicate how many instances of an entity type have been detected, for example cle.Person(13) indicates that thirteen people have been detected.

The TopBraid Composer Instances tab contains the URIs of the people  detected. Opening the highlighted URI reveals that it is for a person named Saddam Hussein.

Entity Disambiguation

One of the challenges when analyzing content and extracting entities is entity disambiguation. Can the person named Saddam Hussein be uniquely identified. Usually the context is needed in order to disambiguate similar entities. As described in the OpenCalais FAQ if the “rdf:type rdf:resource” of a given entity contains /er/ the entity has been disambiguated by OpenCalais while if contains /em/ its not.

In the example above cle.Person is <>. There is no obvious link to an “rdf:type rdf:resource” containing /er/. It looks like OpenCalais has been able to determined that the text “Saddam Hussein” equates to a Person, but has not been able to determine specifically who that person is.

In contrast Iraq ( one of three countries detected) is shown below with the Incoming Reference

Opening the URI with either an HTML browser as or with an rdf browser as ( in Tabulator below ) shows that the country has been disambiguated with <rdf:type rdf:resource=””/>.

Linked Data

In the RDF response returned by OpenCalais neither Iraq nor “Saddam Hussein” were linked to other Linked Data datasets. Some OpenCalais entities are. For example Moscow,Russia is linked via owl:sameAs to

Since I know that the context of the article is international news I can safely add some owl:sameAs links such as the following for Dbpedia links for “Saddam Hussein” (below) and Iraq.

Entity Relevance

For both detected entities “Saddam Hussein” and “Iraq” OpenCalais provides an entity relevance score (shown for each respectively in the screen shots below ) The relevance capability detects the importance of each unique entity and assigns a relevance score in the range 0-1 (1 being the most relevant and important). From the screen shots its clear that “Iraq” has been ranked more relevant.

Detection Information

The RDF Response includes the following properties relating to the subjects detection

  • c:docId: URI of the document this mention was detected in.
  • c:subject: URI of the unique entity.
  • c:detection: snippet of the input content where the metadata element was identified
  • c:prefix: snippet of the input content that precedes the current instance
  • c:exact: snippet of the input content in the matched portion of text
  • c:suffix: snippet of the input content that follows the current instance
  • c:offset: the character offset relative to the input content after it has been converted into XML
  • c:length: length of the instance.

The screen shot below for Saddam Hussein provides an example of how these properties work.


OpenCalais is a very impressive tool. It takes awhile though to fully understand the RDF response, especially in the areas of entity disambiguation and the linking of OpenCalais entities to other Linked Data datasets. Most likely there are some subtleties that I have missed or misunderstood so all clarifications welcome.

For entities extracted from international news sources and not linked to other Linked Data datasets it would be interesting to try some equivalence mining.

Australias Government 2.0 Taskforce commissions Semantic Web Project

Saturday, September 5th, 2009

The Australian Government initiated the Government 2.0 Taskforce in June 2009.

The launch video features Lindsay Tanner, Minister for Finance and Deregulation and chair Dr Nicholas Gruen in an enthusiastic presentation, outlining two key themes the government is keen for the taskforce to pursue.

These are:

  • Transparency and Openess. Using technology “to maximise the extent to which government information, data, and material can be put out into the public domain that we can be as accountable as possible, as transparent as possible and that this data is available for use in the general community.”
  • Community Engagement. Improving “the ways in which we engage with people in the wider community; in consultation, in discussion, in dialogue, about regulation, about government decisions, about policy generally.”

Examples of early government innovation include:

On 1 September 2009 the taskforce announced that it was Open for business commissioning six projects and inviting interested parties (individuals or companies) to submit quotes to be received by 9 September 2009.

Early leadership in Semantic Web

Of particular interest is the Early leadership in Semantic Web project. The project deliverable is to be a report which includes:

  • a guide for use by Australian Government agencies that will assist them with proper semantic tagging of datasets;
  • identified Australian Government datasets that could benefit from proper semantic tagging;
  • and a case study on the process and any issues from of applying proper semantic tagging to an indentified agency dataset.

Both this and the fact that government departments such as the Australian Bureau of Statistics are moving to release data under a creative commons license is another encouraging sign that an open web of linked data is in the process of evolving.