Evan Sandhaus (f.l.t.r) busy preparing his talk in the kitchen of SWC, together with Andreas Blumauer (SWC) and Leo Sauermann (Gnowsis).

Mr. Sandhaus in action.

rNews is a RDFa vocabulary, which is basically a carefully selected subset of the very rich IPTC vocabulary and some additional elements that came up during the standardization process. It is now available in version 1.0 and – according to Evan – actively supported by schema.org.

As showed above the data model of rNews is really simple and centered around two classes: the NewsItem and the Concept. This deliberate simplicity is a major advancement compared to standards like NewsML (whose complexity probably prohibited its critical uptake among the news industry). But due to the functional extensions attributed to RDFa, rNews might also be considered more complex than hNews, the microformat equivalent issued by the IPTC in 2009.

Evan mentioned three scenarios that might drive the uptake of rNews for the benefit of news publishers:

1) Better news search

rNews allows you to explicate and differentiate various documents elements like, title, author, text body, picture etc., thus giving the publisher better control of what to expose for indexers and web crawlers. This might not just improve the display of rich snippets in the search results of Google and other search engines, but also allow automated population of faceted search and metadata based similarity search.

2) Better ad placement

As rNews can be applied to any kind of news-relevant media irrespective of its format (grafics, audio, video, etc.) the metadata can be used to avoid “unfortunate juxtapositions” between editorial content and ads. Hence, media agencies could profit from this additional data by fuelling their matching algorithms and gain better insight into the context specificities of content items.

3) Better analytics

By improving the semantic granularity of a news item this additional information can be used to carry the web analytics beyond the page level and provide a better insight into usage patterns. The additional data can be applied for visualization and exploration purposes i.e. for search engine optimization, sentiment detection and many more.

This is just a small fraction of things rNews could be used for. All in all it is exciting to see that IPTC has finally started to provide publishers with a standard that is relatively easy to implement and help them to overcome the obstacles of existing technologies without disrupting existing publishing workflows. In multi-sided markets like the news industry this might be a crucial success factor!

Alltogether this is another very important building block for an even broader adoption of the semantic web – and the Semantic Web Company is proud of being able to welcome some of the proponents of rNews in Vienna.

Tomorrow at our first “Open House” event (which is proudly presented by the Vienna Semantic Web Meetup) not only our guest list but also the speakers list is very promising:

• Evan Sandhaus, IPTC Delegate and Lead Architect For Semantic Platforms at The New York Times Company
• Andreas Gebhard, Member of the Board of Directors of the IPTC and a Managing Editor at Getty Images
• Stuart Myles, Lead of the Semantic Web Working Group of the IPTC and Deputy Director of Schema Standards at The Associated Press
• Marco Neumann, Lotico

Live Stream on Justin.tv

We will report about the talks on “the day after” but we are sure that this meetup will bring a lot of light into the ongoing discussion why media and press companies finally should start to adopt semantic web standards.

Related articles

• Impressions on the Schema.org Workshop (w3.org)
• The Semantic Web Media Summit (theconferencecircuit.com)
• New W3C Community Groups in the Semantic Web World (w3.org)

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.

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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• Putting Freebase in a Star Schema (gen5.info)
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You can live-edit the input from several cameras – this can also be achieved by logging in on different computers at a time, thus using the input from several built-in webcams at a time. You can drag and drop the video input channels into your scene, make the embedded videos smaller to achieve a screen-in-screen effect, create your own TV design and virtual studio from graphics…. wow, wow, wow.

I played with it today, not being quite as adventurous as Luca, in that I used only one camera (see what he achieved yesterday with multiple screens), nor did I interrupt and restart the recording (which I could have), but even though, I find the visual result, i.e. the ‘studio’ I built from the book cover, impressive enough.

So here is it: My introduction of the Social Semantic Web publication (which is in German, which is why the audio is in German, too, but you don’t need to understand what I am saying to be impressed by Make.tv). Jump to seconds 3:30 to 4:30 to see how you can switch between different screens while doing the web cast.

P.S. That’s an image below – you can embed the video, but you cannot (yet) deactivate that it starts automatically if you embed it, so I’ve decided to use an image on the blog instead. Click here, or the image, to launch the webcast on the Make.tv website.

Btw, I am not sure whether I said XML or XHTML in the webcast, but of course I meant XHTML when talking about the benefits of RDFa.

In creating the modern generation of enterprise and web applications, we typically integrate information from multiple sources. Relating data from disparate sources presents a challenge of deriving information. However, semantic tools and technologies are evolving that enable us to understand information derived by linking data from different sources, including data from applications, databases, ontologies and content management systems. Semantic technologies and tools support techniques such as tagging online information to make it more readily accessible for data integration. This makes it easier to understand data in relation to other data, even if some of this data is inside your firewall, some is in a business partner’s system, and some is part of the growing collection of useful publicly available data on the web.

LinkedData Planet provides insights into those technologies that enableus to:

• connect data contained in silos within organizations in a meaningful way
• extract and correlate data from web sites and databases for purposes such as analyzing trends and decision support, customer and vendor relationship management, and social networking

The concept of linked data is gaining mindshare with developers, users and the more than 200 software companies developing semantic tools. A community including architects, developers and web builders is advancing the evolution of the World Wide Web from “linked documents” to a web of “linked data”. Organizations such as Adobe, Google, OpenLink Software, Oracle, SAP, the W3C and the grassroots Linking Open Data community have provided technology and thought leadership during the embryonic stages of this transition. Semantic technology has gained traction in the enterprise and linked data is accessible via the web. Notable examples include DBpedia, the Zoominfo search engine, the Bambora travel recommendation site, social networking sites, semantic web services and SPARQL query language and protocol-compliant servers and data management systems. There are also linked data browsers and a growing number of sites exposing machine-readable data using micro-formats, RDFa, and GRDDL.

LinkedData Planet sessions will cover topics such as:

• Retrieval technologies: XQuery, SPARQL, and SQL
• Middleware: SQL-RDF mapping, GRDDL, RDFa, and other RDF data converters (RDFizers)
• Tools, RDF browsers, linked data search engines, publishing tools
• Open Data Ontologies and OWL
• Semantic web services exploiting social networking technology
• Combining data from SQL databases, GIS and content management systems

The LinkedData Planet audience will include system architects, enterprise architects, web site designers, software developers, consultants and technical managers, all looking to learn more about linking the growing collection of available data sources and technologies to get more value from their data for their organizations.

Conference Venue:
Roosevelt Hotel
45 E 45th St
New York, New York 10017
Co-chairs: Bob DuCharme, Ken North

Conference producer: Jupitermedia Corporation