Tag Archives: Thesaurus

Thomas Schandl

Which kind of controlled vocabularies matter?

by , Category: Calls & Competitions, Knowledge Management, Semantic Web Applications

Looking at intermediate results of the Controlled Vocabularies Survey an interesting finding concerns the question which types of knowledge models are currently best fit for actual use in applications.

So far 143 people whose organization already make use of controlled vocabularies answered the question “Which kind of controlled vocabulary do you use or plan to use in your applications?”.
The results so far show that lightweight models like taxonomies and thesauri are somewhat preferred over ontologies:

Taxonomies are the favorite, as 73.6% of participants use or plan to use them, followed by thesauri (62%) and ontologies (61.2%), while simple glossaries lag considerably behind with a usage of 31.4%.

This survey will close in about a week, so please take this chance to make your opinions on this topic count! You can find the questions here, it will take 5-10 minutes to answer them.

All participants will gain access to a report with the results within the following month. The most interesting results will be made public on this blog.

Thomas Schandl

Linked data based thesaurus management in collaborative settings

by , Category: Corporate Semantic Web, Enterprise 2.0, Knowledge Management, Linked Data & Open Data, Semantic Web Applications, Tools & Software

The creation and management of controlled vocabularies in companies often takes place in a distributed manner. Different departments in different branch offices often rather create their own vocabularies, than have one large central knowledge model, where everyone contributes.

How to model divergent views on one concept?

Such a central model is not only much harder to manage, but there is also the general problem that differerent departments like marketing, quality assurance, R&D, etc. will have divergent views on the model and its concepts. These different perspectives on one and the same concept are hard to unify in a single model.

Think of a company that sells mobile phones and wants to create a model of its line of products. It wants to utilize this model in the context of its online shop as well as in the context of its user support forum. While the structure of the model (i.e. the relationships between the products) might be very similar or the same in both contexts, there will be differences in which properties of the products are actually relevant in the respective contexts.

In the model of the marketing department there might be a concept for a “Phantastax StamiMaxx” cell phone with a definiton “The StamiMaxx has a powerful battery and is great for professionals who travel a lot”. They might relate it to manufacturer “ACME Corporation” and to several concepts representing different features like “Android OS”, “Multi-touch touchscreen”, etc.
The very same phone has different properties that are interesting from the Quality Assurance departement’s perspective. They might call it by a more specific name like “Phantastax i3000 StamiMaxx S”, have a different definition for it like “3G cell phone implementing the new WTF3000 protocol, …” and relate it to concepts representing known problems and their solutions.

Now they face the task to integrate these different models, as it is not desirable to use a bunch of isolated models within one company.

Support of collaborative work on distributed models

To support this kind of collaborative work on distributed knowledge models, we would like to link the concepts of the models, just as is we link documents in the World Wide Web. Fortunately the Simple Knowledge Organisation System (SKOS) offers mapping properties that can be used to define relationships between concepts from different knowledge models.

E.g. when we want to say that concept “Phantastax StamiMaxx” in the product line thesaurus refers to the same real world entity as concept “Phantastax i3000 StamiMaxx S” in the Quality Assurance thesaurus, then we can use skos:exactMatch to express that. If we want to express that the concepts are merly similar, skos:closeMatch could be used.

The other SKOS mapping properties express a hierarchical (narrowMatch, broadMatch) or an associative (relatedMatch) mapping relation between concepts from different concept schemes. With those we can say that my Samsung Galaxy concept has a skos:broadMatch “Smartphone” in the product line vocabulary and a skos:relatedMatch “ACME Corporation” in a controlled vocabulary about Tech companies.

Modularisation of knowledge models

In this way SKOS thesaurus management systems like PoolParty make it possible to modularise knowledge models, represent concepts in their different contexts and consequently enable collaborative work on those models: The marketing guy can work on his model with the concept properties focused on sales without disrupting the work of the quality assurance expert on her own thesaurus. Later one or both of them can create the skos:exactMatch link between the concepts that are the same, like seen in the “Exact Matching Concepts” box in screenshot of PoolParty below.

Enrich your knowledge: Get connected with the LOD Cloud

Going a step further the models could be connected to external knowledge, e.g. a source from the Linked Open Data (LOD) Cloud. Once we establish links to LOD hubs like DBpedia, we can import additional information for their concepts or use it to establish whether similar concepts from different models really refer to the same real world resource.

Thomas Schandl

Transforming spreadsheets into SKOS with Google Refine

by , Category: Tools & Software, Vocabularies & Languages

Looking for high quality enterprise vocabularies we recently turned our attention to the Global Industry Classification Standard (GICS), which is an industry taxonomy designed to categorize any private company. It was developed by Morgan Stanley Capital International and Standard & Poor’s and is mainly used by the global financial community to aid in the investment research process.

It is available for download as .xls spreadsheet files in several languages. Of course it would be much better to have this valuable taxonomy in a standard and machine-readable format. The Simple Knowledge Organization System SKOS is a perfect fit for a taxonomy like GICS. But how to turn a spreadsheet into SKOS with minimal manual effort?

I chose to try Google Refine for this task, as recently a promising RDF extension had been released by DERI‘s Fadi Maali and Richard Cyganiak.

Google Refine is “a power tool for working with messy data, cleaning it up, transforming it from one format into another, extending it with web services, and linking it to databases”. Previously it was known as Freebase Gridworks which is now further developed by Google since its acquisition of Metaweb.

Refine

Google Refine UI

Refine is a very useful tool to filter and consequently transform rows, colums and cells according to customizable patterns.

After applying all necessary transformations to the spreadsheet one can edit the “RDF Skeleton”, where the columns can be mapped to literals, RDF properties and RDF classes (which can be imported from their namespaces).

RDF Sekeleton

Editing the RDF Sekeleton

Once you got your valid SKOS model ready you can export it in RDF/XML or Turtle format. Then you may want to load it into an ontology editor like Protégé or a thesaurus management tool like PoolParty in order to build upon it or connect it to other knowledge models. With PoolParty the GICS taxonomy can also be utilized to tag and categorize documents, provide semantic search and facetted navigation and it can be published as Linked Data without further effort.

GICS in PoolParty screenshot

GICS loaded in PoolParty

Working with Refine and its RDF extension was easy and fun. It’s even possible to isolate and save the transformation steps done with Refine, so one can re-apply them on similar structured spreadsheets. This came in very handy as GICS is published in nine languages and as many separate, identically structured spreadsheets.

Andreas Blumauer

Les Kneebone: “Semantic web technologies are one solution to linking education data in Australia”

by , Category: Semantic Web Applications, Tools & Software, Vocabularies & Languages

Les Kneebone is Project Manager at Education Services Australia Ltd.
Among other projects he is responsible for Schools Online Thesaurus (ScOT).

PoolParty Team asked Les a couple of questions about thesaurus management, linked data and the semantic web. Here is a short summary of this interview:

Why did you choose thesauri to organize your information? What kind of problems are you able to solve with this approach?

A thesaurus approach was chosen rather than a subject headings approach because we assumed (and continue to assume) that post-coordinate indexing will drive vocabulary-assisted discovery.

Which role does SKOS and/or Linked Data play in order to achieve your goals?

ScOT concepts are now published as URIs. This approach solves the problem of different ScOT versions in disparate systems.

What are the most important values you generate for your stakeholders? What kind of applications can be built or have been built on top of your thesauri?

The Achievement Standards Network (ASN) provides a model for profiling curriculum statements and linking those statements to education resources using various rdf vocabularies. By profiling curriculum statements to learning resources, more precise matching is achieved.

What are the most important arguments to use Semantic Web standards and linked data, especially in education?

The Australian education sector is characterized by many disparate systems in different education jurisdictions. Semantic web technologies are one solution to linking education data in Australia.

Why did you choose PoolParty to manage your thesauri?

We had already identified SKOS as an important standard for ScOT so it was natural to select PoolParty as a our new thesaurus management tool.

What are your future plans and next steps? How do you manage to get your thesauri used, how are you going to build an “eco-system” around your work? (Do you plan to publish ScOT on the LOD cloud? Under which licenses?)

Our vocabularies are currently for non-commercial use and we don’t anticipate any change to the license at this stage. The ScOT license requires attribution, permits derivatives that must be shared, and is for non-commercial use.

Read the full interview here.