Semantic Web Company

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 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 thesaurus &  Standard 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.

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.

George Anadiotis is an expert on artificial intelligence with academic roots at the Vrije Universiteit, Amsterdam. In February 2009 he took the position as R&D Director at the Greek technology company IMC. I met him in September at I-SEMANTICS 2009 where he and his team contributed to the Triplification Challenge. In their paper Linked Data for the Masses they were pondering about the pragmatic value of Linked Data from an inbound and outbound perspective.  In his words:

We started experimenting with the technical infrastructure needed and created some proof-of-concept applications. Part of this work was enabling Linked Data access for the front-end infrastructure we used, Liferay portal. We decided on the appropriate vocabularies for the type of content we wanted to publish (FOAF, SIOC and MOAT mainly), delved on the internals of Liferay and used D2R to map its relational database to the vocabularies of choice, also using techniques to improve performance as much as possible. Since Liferay itself is also based on the notion of communities, we thought our work would be more widely applicable and useful, so we chose to submit it for review at the Triplification Challenge and make it available to the community as open source software. Our applications have gradually matured and are about to be deployed in our commercial projects, while at the same time we are now making the Liferay Linked Data Module available as a Sourceforge project and we are working with Liferay management in order to disseminate this effort to the community and also include it in a future release of the software.

Read the full interview here.

The Semantic Web Company created a series of online seminars (aka webinars) for you to acquire basic and practical knowledge about methologies, technologies and standards of the Semantic Web. In 90 minute sesseions we will cover the business aspects of topics such as content engineering, Knowledge Management, business intelligence, e-Business and more.

In order to allow for a high level of interaction, the attendance is limited to ten participants and ample time for questions and discussion with our experts is designated. Each webinar works as a stand-alone module, so you can pick and choose some of them or book the whole series of 6 webinars.

We’ll kick off with a session about Semantic Wikis on Thursday 22nd of October. A German language version will be held at 9 a.m., alternatively you can atted an English version at 6 p.m. CET.

Each Thursday we cover a different topic such as Semantic Search, Corporate Thesaurus Management, Text Mining on the Corporate Semantic Web, Linking Open Data and Semantic Advertising.

In order to participate you only need broadband access to the internet, Windows or a Mac and a fairly up-to-date browser. For detailed system requirement see the webinar overview.

We hope to talk to you in one or more of these sessions!

Some new releases around Apple´s iPhone family, like the new OS3.0 or the new 3G S have stimulated another big hype around this “little darling”. I took a look at another facet, namely: Has the Semantic Web entered the iPhone realm yet (or vice versa)? Experts have been talking about the need for semantically enhanced mobile applications for years, so let´s see, if they are in place already.

Searching for “semantic web” in the AppStore delivers six results, one of them called “SemanticWb” is obviously an interesting match. The application “extracts current life sciences and health care knowledge and place them conveniently at your fingertips on your iPhone”. The application offers search suggestions and moderated search and retrieves articles from PubMed or genetic disorders which are related to the search term. Good start, this is a neat iPhone application which should be interesting for medical doctors and related professions.

Another application on the iPhone which is related to the semantic web is the “English wordnet dictionary” based on WordNet from Princeton University.

So, not much semantic web on the iPhone so far – I thought until Evriverse was released some weeks ago. The iPhone version of evri.com offers a new way to find connections between all kind of things. Similar to OpenCalais Evri can extract people, places, organisations, products etc. from unstructured information like news or blogs. The innovation around Evriverse is the way how complex search queries around “anything” can be formulated by just touching the screen. For example, if you are looking for information about “Tim Berners-Lee” the application not only offers auto-complete but also suggests related people, organisations etc. to refine any search query. Such relations are updated constantly and are based on the semantic analysis of news and blogs.

Evriverse offers the most comfortable way to do news research on the iPhone today. It shows how semantic technologies can enhance user experience on a mobile device and it will path the way to more semantic (web) apps on the iPhone.

Jamie Taylor, Metaweb

Andreas Blumauer from Semantic Web Company (SWC) talked with Jamie Taylor, Minister of Information at Metaweb Technologies Inc. about Freebase & Linked Data and Google´s announcement to use RDFa.

SWC: At ISWC 2008 Freebase became “officially” part of the LOD Cloud. What exactly has changed since that time?

Jamie: Since Freebase is a community writable semantic database, the addition of the RDF interface allows anyone to publish data into the LOD cloud. LOD Applications can access any Freebase Topic through the RDF interface by constructing a URI from the Freebase identifier.  But perhaps more importantly, because entities in Freebase can be annotated with multiple identifiers, Freebase Topics can be retrieved by constructed URIs using the identifiers used by other systems and data sets.
For instance, the movie Blade Runner can be referred to as http://rdf.freebase.com/ns/en.blade_runner, but it can also be referenced as http://rdf.freebase.com/ns/authority.netflix.movie.70053131 using the Netflix identifier, http://rdf.freebase.com/ns/authority.imdb.title.tt0083658 using the IMDB identifier, or as http://rdf.freebase.com/ns/wikipedia.en.Dangerous_Days using a Wikipedia wikiword (which in this case is a Wikipedia redirect to the wikiword Blade_Runner).
Freebase also provides a user maintained mapping of how these identifiers can be used to address resources in other LOD systems. The sameas.freebase.com schema can tell an LOD user that the Freebase Blade Runner Topic can also be found in DBpedia using Wikipedia identifiers or how musical artists can be found at the BBC using Musicbrainz identifiers.  In fact, the Freebase RDF interface uses the sameas.freebase.com schema to create the owl:sameAs links in the RDF output allowing the user community to expand the interconnections between Freebase and the LOD Cloud.
Linked Data providers are also using the strong identifiers in Freebase to identify entities such as companies and locations in their own data sets.  When they find an entity that is not represented in Freebase, they simply add the entity to Freebase and use the newly minted Freebase identifier.  This permits anyone using their data to understand how their entities relates to any of the more than 5 million things interconnected within Freebase.

The RDF interface can also be used to reference the Freebase type system, giving LOD data set providers vocabularies across a wide range of subject areas.  And because anyone can expand Freebase’s data model, data providers can use our schema development tools to build and extend these vocabularies to suite their needs.
Freebase was not designed for ephemeral or fast changing data, like weather conditions or stock ticks.  But this type of information is well suited for publication as Linked Data.  Freebase entities representing a location or company can be annotated with references to LOD services that provide these types of volatile data.  Similarly, Linked Data provides a great way to disseminate very fined grained information that might be associated with a scientific study or financial report.  Linked Data provides a seemless transition from Freebase, where a user (or application) can run a query with constraints that run across a wide range of types to find entities of interest along with the LOD services that provide access to temporal or high resolution data not available in Freebase.
We recently demonstrated MQL Extensions which allows the Metaweb Query Language to use data from other systems as a part of the query constraint and result set.  While MQL Extensions are user extensible and work with a wide array of systems,  this capability makes the connection between Freebase and the LOD Cloud even more transparent.
For example, because US companies that are registered with the SEC are annotated CIK code in Freebase and the sameas.freebase.com schema indicates that the CIK annotation can be used to create a URI that is dereferencable at rdfabout.com, it is possible to write a MQL query that asks who is on the board of financial services companies that trade on NASDAQ and are  headquartered in California (and using another MQL Extension, you can ask for their stock price as well!)

SWC: Many organisations are very interested in Linking Open Data now but they are still not sure if they can benefit from publishing data on the web – what´s your experience so far?

Jamie: Linked Open Data provides a simple, standard way for organizations to distribute structured data.  For most organizations, providing access to data is another important outlet to announce the availability of higher value services.  For organizations involved in building or selling physical goods, the bits representing what they provide are not the goods themselves, but a way of attracting potential customers.  Making catalogs and specification sheets available in electronic form, so other applications can connect buyers to their physical goods is simply an effective marketing system.  Even for firms involved in electronic services, providing access to open structured data is generally a lead-in to value added services.  For instance, if I ran a service collecting hard-to-find information about manufacturing relationships between medium sized businesses, I would publish open company profiles covering things like market size, industry, location for the medium-sized businesses I tracked, so potential users the premium data would know I had the coverage they were looking for.

SWC: Just recently Google has announced to use RDFa to enhance their search results. What do you think?

Jamie: We are excited about Google’s announcement. Yahoo’s use of RDFa for Search Monkey and Google’s announcement gives RDFa users tangible benefits. The Search Monkey team was very quick to realize that because users can create data models in Freebase, and because the elements of those models all have strong RDF identifiers, Freebase provides a large and user extensible vocabulary for RDF/RDFa (see the list of vocabularies). When a user wants to create a Search Monkey application that works with their film review site, they need not invent a new vocabulary (that will probably be used only once),  they can use the Freebase Film Domain vocabulary which supports over 63,000 instances in Freebase alone.
Similarly, with over 5 Million well described Topics in Freebase and over 14,000,000 Named Objects (Topics, images, musical tracks and documents) when a user wants to unambiguously identify a subject or object in RDF/RDFa, Freebase has an extremely large collection of identifiers to draw from.  These cover people, places, companies, movies, music, books and wide variety of other subjects.  If Freebase doesn’t have the entity the user is looking for, they can of course add it themselves and make use of the identifier immediately. I think this is why Google used some Freebase identifiers in their examples. We hope that with Yahoo and Google’s support for RDFa the web will become a strongly annotated source of data which can support a wide range of user applications.

SWC: Thank you, Jamie!

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Linked Data is evolving fast. A huge amount of RDF data is available and ready for exciting new applications. Unfortunately, the bottleneck is still the availability of Semantic Web user front-ends which demonstrate the power of linked data. To a certain degree BBC Music beta is the first commercial platform which makes heavy use of linked data. With Parallax David Huynh has shown that one of the most interesting semantic web applications can be built around browse and search applications which offer tools for doing complex search queries.

Andreas Blumauer from Semantic Web Company (SWC) talked with David Huynh, “Interaction Scientist” at Metaweb, the company which developed Freebase, an “open, shared database of the world’s knowledge”.

SWC: David, you have been working for MIT´s Simile Project and now for Metaweb Technologies – two “building blocks” of the Semantic Web. Could you tell us a bit about your ongoing work at Metaweb?

David: My official title at Metaweb is “Interaction Scientist,” and so my main focus is coming up with novel interaction designs for Metaweb’s platform and products, and prototyping them to some extent to evaluate their effectiveness. Parallax was one such prototype that has gathered much excitement within Metaweb and the Semantic Web community at large. And the Freebase query editor 2.0 shows my interaction designs at the other end of the spectrum – targeting developers rather than just end-users.
I’ve also learned that data-centric user interfaces and interaction designs can only be as good as the data allows them to. So I am also dedicating some of my time toward analyzing the data we have and improving its quality so that I can design even better interactions.

Freebase Query Editor 2.0 from David Huynh on Vimeo.

SWC: With Parallax you have introduced a new way to search and explore data: Could you explain the “set-based browsing paradigm”?

David: In the browsing paradigm of the original Web, while looking at a web page, you can only click on one hyperlink to get to one other web page. But in a lot of cases, the hyperlinks on that web page can be grouped into different groups based on what they mean to the human reader: these are the links that lead to reviews, these are the links that lead to authors, these are the links that lead to vendors, etc.
Now if the computer actually knows what these links mean, then you can tell it to follow several of those links that mean the same thing: follow all the links that lead to authors. Think of it as powered browsing: the computer does the work of following several similar browsing paths at the same time – going from a set of things (web pages or data entries) to a similarly related set of things – and making all of that information available for your perusal in one shot. It is a paradigm shift compared to how we browse the Web today. And it’s only possible when the computer is capable of telling which link is similar to which other link. And that capability, in turn, will be made possible by the Data Web.
(See this unpublished paper which goes into depth about this concept)

SWC: Linked Data is evolving fast. A huge amount of RDF data is available and ready for exciting new applications. Unfortunately, one bottleneck is still the availability of Semantic Web user front-ends which demonstrate the power of linked data. Do you think, that the Semantic Web is rather a server-technology than an end-user experience?

David: I have never thought of the Semantic Web as either a server technology or an end-user experience. I only care about usefulness, and then a matching amount of usability to make that usefulness accessible to people, especially those without Computer Science expertise.
I find that it’s so much easier to explain to people and get them excited about “immediate, personal, local benefits” of a particular technology than about “long-term, communal, global benefits” of a vision. For most people, the former must be experienced and felt often before the latter can appear vaguely appealing enough to call for actions. I’m lazy – I don’t like to spend efforts convincing people of visions; I only want entice people into using the tools that I have created.
So if Parallax is considered a success, it is so not just because of its technologies and research contributions, but also because the accompanying screencast explained it in a way that people who cared nothing about the Semantic Web could understand why Parallax would be useful to them. This was achieved by pointing out limitations of existing web technologies as already experienced and understood by a lot of web users, and then illustrating concretely a possible solution enabled by data web technologies.
Perhaps I could venture further and say that the dichotomy of server technologies and end-user experience is what’s holding back Semantic Web user interface efforts. For those who don’t have expertise in design, it is a comfort to think that once the back-end technologies are solid, then it’s just a matter of putting on some polishes, a.k.a. user interfaces from their point of view, to make the whole package appealing. This approach is wrong. The user interface design must inform the back-end design. Otherwise, the user interface will almost always reflect the internal system model, and that’s usually very dissonant with how users think and behave. Recall all the Semantic Web interfaces you have seen that force users to think in terms of triples or of raw URIs. Those were made by starting from the data model, not from user needs.

SWC: Quite often I hear people saying: Where is the Semantic Web? – I still can´t “see” it! How could the linking open data community make use of such user interfaces like Exhibit, Piggy Bank or Parallax? Is the set-based browsing paradigm a universal way to browse linked data or just one possible way?

David: My research prototypes embody a number of UI ideas that are quite transferable to other platforms. Most of my code is open source, too. This, by the way, is rarer than it should be: research prototypes often fall apart as soon as, or even sooner than, the relevant research papers get presented at conferences, and research code rots rather than gets offered free for reuse. This is sad, because reusable data needs reusable code to proliferate even more widely, but there is no reward system for making research code reusable, or for keeping research prototypes running. So perhaps people can’t “see” the Semantic Web because research prototypes are not presented in appealing and comprehensible ways, and they break down and disappear too quickly.
Regarding the set-based browsing paradigm, it is most certainly not the only way to browse linked data. It is just the first good one that came to my mind, around 2005. But it’s not until 2008 that I actually got around to implement it for real. One of the factors so important in its feasibility is the quality of data in Freebase, compared to other data sources that I had access to. Even the simple fact that a lot of Freebase topics have images makes Parallax look a lot more interesting and useful. People like to see pictures rather than raw URIs. And the diversity of types of data helps illustrate the browsing paradigm of Parallax – that ability to shift focus from one set of things to another set of things, even across very seemingly unrelated domains of information, such as from politicians to their celebrity friends in the movie industry.
So, perhaps one of the main challenges in adopting Parallax ideas on any arbitrary RDF data set is curating the data sufficiently for the purpose of presenting it. In fact, if you don’t know how some data is to be presented and used, there’s no way for you to determine if that data is of sufficient quality. User needs and interface designs drive back-end implementation and data curation, not the other way around. It’s a simple idea, really, but it can be hard to adopt if one is fixated on data alone.

SWC: Do you plan new versions of Parallax? When will it become part of Freebase or of even more Linked Data Sources?

David: I’ve done a few further experiments with the ideas in Parallax, but they are not ready for public use, yet. Freebase data makes my job much easier by allowing me to focus mostly on interaction designs rather than mostly on data quality, or rather, fighting the lack of data quality, for the purpose of presenting it. So I’ll start with Freebase data and we’ll see where it takes me.

SWC: What else are you working on at the moment?

David: As mentioned briefly earlier, reusable data needs reusable code to proliferate widely. That gives you a hint at an effort that I’m involved with.

SWC: Many thanks, David!

About David François Huynh

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