Tassilo Pellegrini

NYT, Wolters Kluwer Germany and Semantic Universe sponsor Triplification Challenge 2010

3.000 € prize money for the  most promising Linked Data applications


The New York Times, Wolters Kluwer Germany and Semantic Universe sponsor the Triplification Challenge 2010 taking place at the I-SEMANTICS Conference from 1 – 3 September 2010 in Graz / Austria. Together they have provided 3.000 Euro in prize money which will be given to the  most promising application demonstrations and approaches built upon Linked Data.

The Challenge is organized by an international consortium consisting of Juan Sequeda (University of Texas at Austin), Bernhard Schandl (University of Vienna), Sören Auer (University of Leipzig), Ivan Herman (World Wide Web Consortium), Tassilo Pellegrini (Semantic Web Company Vienna) and patroned by Sir Tim Berners-Lee.

Participants can choose between an open track and a special NYT track.

The open track sponsored by Wolters Kluwer Germany and Semantic Universe encourages submissions that fit into one or more of the following categories:

  • novel data sets that are published as part of the Web of Data, according to Linked Data principles, and demonstrating potential benefit of use within applications;
  • novel generic mechanisms, approaches, and technologies that convert certain types and formats of information into triples, interlink them to other data sets, and expose them as Linked Data;
  • applications showcasing the benefits of Linked Data to end-users such as for information syndication, specialized search, browsing, or augmentation of content.

The NYT track invites submissions that make use of the Linked Data published at data.nytimes.com and one or more government datasets that relate to politics. Any dataset qualifies that is produced by any government in the world that would be of interest to a constituent of that government. These can range from the demographics of election districts to campaign finance to corporate spending on political messaging.

The submission deadline for both tracks is 18 May 2010.

All submissions will be reviewed by an international program committee from industry and academia electing two winners in the open track and one winner in the NYT track.

For detailed information on the Triplification Challenge visit

http://i-semantics.tugraz.at/triplification-challenge or

http://triplify.org/Challenge/2010

Cordial thanks to our sponsors:

Tassilo Pellegrini

Linking Open Data to Thesaurus Management

The Vienna-based company punkt. netServices is just about to release a demo version of their PoolParty service, a SKOS-based thesaurus management tool with linked data capabilities. I had the chance to pre-read a white paper and test their service. Here is a brief overview. You can also try a demo.

Purpose

Poolparty was conceived to facilitate various applications like

  • Semantic search engines
  • Recommender systems (similarity search)
  • Corporate bookmarking
  • Annotation- & tag recommender systems
  • Autocomplete services and facetted browsing.

These use cases can be either achieved by using PoolParty stand-alone or by integrating it with existing Enterprise Search Engines and Document Management Systems or Enterprise Wikis.

Thesaurus Management

PoolParty is aiming to be easy to use for people without a strong Semantic Web background or special technical skills. The GUI is entirely web-based and utilizes AJAX so the user can e.g. quickly merge two concepts via drag & drop. An overview over the thesaurus can be gained with a tree or a graph view on the concepts.

poolparty-blueskin

PoolParty also helps to semi-automatically add concepts to a thesaurus as it can be used to analyse documents (e.g. web pages or PDF files) relevant to a thesaurus’ domain in order to glean candidate terms. This is done by the key-phrase extractor of KEA. The extracted terms can be selected by the user, thereby becoming “free concepts” which later can be integrated into the thesaurus, turning them into “approved concepts”.

Documents can be searched in various ways – either by keyword search in the full text, by searching for their tags or by semantic search and similarity search. The latter takes not only a concept’s preferred label into account, but also its synonyms and the labels of its related concepts are considered in the search. The user might manually remove query terms used in semantic search. Boost values for the various relations considered in semantic search may also be adjusted. In the same way the recommendation mechanism for document similarity calculation works.

PoolParty by default also publishes a Semantic Wiki version of its thesauri, which provides an alternative way to browse and edit concepts. Through this feature anyone can get read access to a thesaurus, and optionally also edit, add or delete labels of concepts. Search and autocomplete functions are available here as well. The Wiki’s XHTML source is also enriched with RDFa, thereby exposing all RDF metadata associated with a concept to be picked up by RDF search engines and crawlers. (See two examples: Cocktail thesaurusStandard Thesaurus for Economics)

PoolParty also supports the import of thesauri in SKOS (including several consistency checks) or Zthes format. Those functionalities can also be consumed as stand-alone web services via PoolParty SKOS Services. Additionaly, lists of concepts and their labels can also be imported via CSV files.

Linked (Open) Data

PoolParty not only publishes its thesauri as Linked Open Data (in addition to a SPARQL endpoint), but it also consumes LOD in order to expand thesauri with information from LOD sources.

Concepts in the thesaurus can be linked to e.g. DBpedia  via a service like Georgi Kobilarov‘s DBpedia lookup service, which takes the label of a concept and returns possible matching candidates. The system suggests relevant resources from DBpedia and the user can select the one that matches the concept from his thesaurus, thereby creating a skos:exactMatch relation between the concept URI in PoolParty and the DBpedia URI. The same approach can be used to link to other SKOS thesauri available as Linked Data.

poolparty-lod

Other triples can also be retrieved from the target data source, e.g. the DBpedia abstract can become a skos:definition and geographical coordinates can be imported and be used to display the location of a concept on the map, where appropriate. The DBpedia category information may also be used to retrieve additional concepts of that category as siblings of the concept in focus, in order to populate the thesaurus.

PoolParty is capable of importing a SKOS thesaurus from a Linked Data server, and may also receive updates to thesauri imported this way. This feature has been implemented in the course of the KiWi  project funded by the European Commission. KiWi also contains SKOS thesauri and exposes them as LOD. Both systems can read a thesaurus via the other’s LOD interfaces and may write it to their own store. This is facilitated by special Linked Data URIs that return e.g. all the top-concepts of a thesaurus, with pointers to the URIs of their narrower concepts, which allow other systems to retrieve a complete thesaurus through iterative dereferencing of concept URIs.

Additionally KiWi and PoolParty publish lists of concepts created, modified, merged or deleted within user specified time-frames. With this information the systems can learn about updates to one of their thesauri in an external system. They then can compare the versions of concepts in both stores and may write according updates to their own store.

This means each system decides autonomously which data it accepts and there is no risk of a system pushing data that might lead to inconsistencies into an external store. Data transfer and communication are achieved using REST/HTTP, no other protocols or middleware are necessary. Also no rights management for each external systems is needed, which otherwise would have to be configured separately for each source.

Technology

The software is written in Java and utilizes the SAIL API, so it can be used with various triple stores. The thesaurus management itself (viewing, creating and editing SKOS concepts and their relationships) can be done in an AJAX Frontend based on Yahoo User Interface (YUI). Editing of labels can alternatively be done in a Wiki style HTML frontend. For key-phrase extraction from documents PoolParty uses a modified version of the KEA 5 API, which is extended for the use of controlled vocabularies stored in a SAIL Repository (this module is available under GNU GPL). The analysed documents can be stored and indexed in Lucene/Solr or any other (enterprise) search system along with extracted and semantically related concepts.

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Tassilo Pellegrini

Topic Maps and the Semantic Web

tmraFrom November 11 – 13, 2009 this will be one of the big issues at the 5th International Conference on Topic Maps taking place in Leipzig/Germany. When asked about the relationship between TM and SemWeb conference organizer Lutz Maicher says:

With the vision of the web of data Topic Maps and the Semantic Web move closer over time. Anywhere URIs represent subjects, structured statements are gathered around them. In this context I see subj3ct.com as an interesting ventures. This recently launched service provides URIs for 15 million subjects to be used in structured data. Naturally, linked data hubs like dbpedia or geonames.org are part of it. The crowd is invited to contribute to this collection, also the Topic Maps Lab provides several feeds to register new URIs. Subj3ct.com turns out to be an infrastructure technology for Web 3.0 applications, regardless whether they are based on Topic Maps or other Semantic Web technologies.

Through this convergence the uniqueness of each technology sharpens. Reasoning is the strong point of the Semantic Web. But the strength of Topic Maps are semantic portals and the global federation of facts around subjects. Bringing together all and even contradictory information about each subject – and not building reasoning-ready consistent models of the world – is built into the genes of Topic Maps.

Read the full interview here.

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