Our people weigh in on the issues of the day.

Blue Slate's people think a lot about the challenges facing their industries today. In the process, they often come up with completely unexpected slants on current issues, or new ways of thinking about business problems. Bluespeak is where they share those thoughts. Feel free to read and reflect.

[Any views or opinion represented in this blog are personal and belong solely to the blogger and do not represent those of Blue Slate Solutions.]

Semantic Technology and Business Conference, East 2011 – Reflections

I had the pleasure of attending the Semantic Technology and Business Conference in Washington, DC last week.  I have a strong interest in semantic technology and its capabilities to enhance the way in which we leverage information systems.  There was a good selection of topics discussed by people with a variety of  backgrounds working in different verticals.

To begin the conference I attended the half day “Ontology 101” presented by Elisa Kendall and Deborah McGuinness.  They indicated that this presentation has been given at each semantic technology conference and the interest is still strong.  The implication being that new people continue to want to understand this art.

Their material was very useful and if you are someone looking to get a grounding in ontologies (what are they?  how do you go about creating them?) I recommend attending this session the next time it is offered.  Both leaders clearly have deep experience and expertise in this field.  Also, the discussion was not tied to a technology (e.g. RDF) so it was applicable regardless of underlying implementation details.

I wrapped up the first day with Richard Ordowich who discussed the process of reverse engineering semantics (meaning) from legacy data.  The goal of such projects being to achieve a data harmonization of information across the enterprise.

A point he stressed was that a business really needs to be ready to start such a journey.  This type of work is very hard and very time consuming.  It requires an enterprise wide discipline.  He suggests that before working with a company on such an initiative one should ask for examples of prior enterprise program success (e.g. something like BPM, SDLC).

Fundamentally, a project that seeks to harmonize the meaning of data across an enterprise requires organization readiness to go beyond project execution.  The enterprise must put effective governance in place to operate and maintain the resulting ontologies, taxonomies and metadata.

The full conference kicked off the following day.  One aspect that jumped out for me was that a lot of the presentations dealt with government-related projects.  This could have been a side-effect of the conference being held in Washington, DC but I think it is more indicative that spending in this technology is more heavily weighted to public rather than private industry.

Being government-centric I found any claims of “value” suspect.  A project can be valuable, or show value, without being cost effective.  Commercial businesses have gone bankrupt even though they delivered value to their customers.  More exposure of positive-ROI commercial projects will be important to help accelerate the adoption of these technologies.

Other than the financial aspect, the presentations were incredibly valuable in terms of presenting lessons learned, best practices and in-depth tool discussions.  I’ll highlight a few of the sessions and key thoughts that I believe will assist as we continue to apply semantic technology to business system challenges.

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Wednesday December 07, 2011 | By David Read

Sparql Droid – A Semantic Technology Application for the Android Platform

The semantic technology concepts that comprise what is generally called the semantic web involve paradigm shifts in the ways that we represent data, organize information and compute results. Such shifts create opportunities and present challenges. The opportunities include easier correlation of decentralized information, flexible data relationships and reduced data storage entropy. The challenges include new data management technology, new syntaxes, and a new separation of data and its relationships.

I am a strong advocate of leveraging semantic technology. I believe that this new paradigms provide a more flexible basis for our journey to create meaningful, efficient and effective business automation solutions. However, one challenge that differentiates leveraging semantic technology from more common technology (such as relational databases) is the lack of mature tools supporting a business system infrastructure.

It will take a while for solid solutions to appear. Support for mainstream capabilities such as reporting, BI, workflow, application design and development that all leverage semantic technology are missing or weak at best. Again, this is an opportunity and a challenge. For those who enjoy creating computer software it presents a new world of possibilities. For those looking to leverage mature solutions in order to advance their business vision it will take investment and patience.

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Friday June 24, 2011 | By David Read

Creating a SPARQL Endpoint Using Joseki

Being a consumer of semantic data I thought creating a SPARQL endpoint would be an interesting exercise.  It would require having some data to publish as well as working with a SPARQL library.  For data, I chose a set of mileage information that I have been collecting on my cars for the last 5 years.  For technology, I decided to use the Joseki SPARQL Server, since I was already using Jena.

For those who want to skip the “how” and see the result, the SPARQL endpoint along with sample queries and a link to the ontology and data is at: http://monead.com/semantic/query.html

The first step in this project was to convert my mileage spreadsheets into triples.  I looked briefly for an existing ontology in the automobile domain but didn’t find anything I could use.  I created an ontology that would reflect my approach to recording automobile mileage data.  My data  records the miles traveled between fill-ups as well as the number of gallons used.  I also record the car’s claimed MPG as well as calculating the actual MPG.

The ontology reflects this perspective of calculating the MPG at each fill-up.  This means that the purchase of gas is abstracted to a class with information such as miles traveled, gallons used and date of purchase as attributes.  I abstracted the gas station and location as classes, assuming that over time I might be able to flesh these out (in the spreadsheet I record the name of the station and the town/state).

A trivial Java program converts my spreadsheet (CSV) data into triples matching the ontology.  I then run the ontology and data through Pellet to derive any additional triples from the ontology.  The entire ontology and current data are available at http://monead.com/semantic/data/HybridMileageOntologyAll.Inferenced.xml.

It turns out that the ontology creation and data conversion were the easy parts of this project.  Getting Joseki to work as desired took some time, mostly because I couldn’t find much documentation for deploying it as a servlet rather than using its standalone server feature.  I eventually downloaded the Joseki source in order to understand what was going wrong.  The principle issue is that Joseki doesn’t seem to understand the WAR environment and relative paths (e.g. relative to its own WAR).

I had two major PATH issues: 1) getting Joseki to find its configuration (joseki-config.ttl); and 2) getting Joseki to find the triple store (in this case a flat file).

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Monday November 29, 2010 | By David Read