Step 1. Generate a thesaurus by using a linked data source like DBpedia

As recently reported SWC has developed a tool called SKOSsy which can be used to extract seed thesauri from DBpedia. In our example I will generate a knowledge model describing the domain of “digital photography“. This step took around 15 minutes.

Step 2. Load the thesaurus into PoolParty and improve it to your needs

After the seed thesaurus has been loaded into PoolParty Thesaurus Manager you have many possibilities to enhance the knowledge model further: Add more categories, synonyms, relations etc. In this example I use the seed-thesaurus without any further improvements. This step took approximately 2 minutes.

Step 3. Generate an automatic text extractor on top of your thesaurus

This step took a couple of seconds and ended up in having generated a fast and reliable text mining application on top of PoolParty Extractor, ready to be used to enrich your documents with data from the LOD cloud.

You can try it out here: PPX Live-Demo

To try the extractor on your own, please take a look at the image above which shows a proper configuration, you have to insert the following UUID in the form: d35d4ddb-adc3-4ea5-b027-deacac03e391

Since our example is all about ‘digital photography’, we recommend to use text samples (or some fragments) like these ones to test the quality of PPX based text analytics:

• Digital Camera Image Noise (Results as HTML, RDF/XML)
• Nikon D3S In-depth Review (Results as HTML, RDF/XML)
• Introduction to Shutter Speed in Digital Photography (Results as HTML, RDF/XML)
• Digital Camera Sensors (Results as HTML, RDF/XML)

Let us know what you think about this straight-forward approach and your opinion about the quality of the results. We believe that thesaurus based text mining is in many cases an alternative to some other approaches, especially if you want to to enrich your content with information from the upcoming web of data.

Of course we would be happy to generate other demos in the areas of your interest! Just get in contact with us by using our contact form.

SWC: Bernhard, you have been working on the Semantic Web and Linked Data for years now. What is the first lesson you usually give when you try to explain the “Semantic Web”?

Maybe I should first clarify that the course I am co-teaching is not a Semantic Web course. The course is about data-centric Web information systems in general and we spent some classes talking about Linked Data and Semantic Web technologies. We start explaining the origins and the fundamental architectural principles of the World Wide Web and then focus on the data-centric aspects of the Web.

“instead of building isolated repository-centric APIs we could also build a globally connected data graph”

After introducing various data exchange formats (XML, JSON & co.) we teach how Web APIs work, and discuss the design principles of RESTful Web Services. Then the conceptual transition to Linked Data is just a small step, because we can argue that instead of building isolated repository-centric APIs we could also build a globally connected data graph, which is based on a uniform data model and can be traversed and queried using SPARQL.

“DBpedia and all the other existing Linked Data projects and tools that came up in recent years really help in explaining and illustrating how things work”

So, I am somehow approaching the “Semantic Web” bottom-up and concentrate on the “visible” parts of the “Semantic Web” vision. DBpedia and all the other existing Linked Data projects and tools that came up in recent years really help in explaining and illustrating how things work. And last but not least, schema.org and the design of the Facebook Open Graph protocol also show the growing importance of having structured data on the Web.

SWC: At least for non-technicians “Linked Data” sounds very technical. Antoine de Saint-Exupery said: “If you want to build a ship, don’t drum up people to collect wood and don’t assign them tasks and work, but rather teach them to long for the endless immensity of the sea.” Is there an “endless immensity of the sea” you try to bring in as well?

If you can access and combine data from the Web you can answer interesting questions and discover previously unknown relationships between things. We thought the best way to learn about Linked Data is to implement simple demo applications. So we asked the students to think about uses cases that bring some benefit for end users and require data from several Web sources to answer certain questions.

“I think it became clear what it means to work with easily accessible structured Web data opposed to working with unstructured data”

One group developed a service which connects safety records with public transport information. Now users can now easily choose the “safest” bus connection between from and to New York City and other cities. Another group combined public school district information with geographic data, which now allows parents to view statistical information about school districts in New York State by using apps like Google Earth. There are many more examples, but most importantly, I think it became clear what it means to work with easily accessible structured Web data opposed to working with unstructured data.

SWC: Instructing how to use the Semantic Web is not only a matter of slide-decks. It is rather a question of concrete use cases in combination with tool skills. What kind of tool skills should students of information sciences acquire to your opinion?

Collecting and making sense out of data is a common scholarly practice in many research areas and the Web is becoming, or is already, the primary medium for publishing and distributing results. I believe that making data accessible as part of a some research activity will become increasingly important in future and the Web will probably be infrastructure for doing this.

So I think that a student who is working with data should at least know (i) how to retrieve and (ii) how to publish data on the Web in way that others can easily discover, access, and use their data. Linked Data is one possible technical approach for doing that.

SWC: As a European who is teaching and working in the U.S., how do you perceive the different approaches between those two systems when it comes to transfer complex fields of knowledge like the semantic web from universities to business environments?

From the experiences I have made in my previous and current working environments I can only tell that the relations between businesses and universities seem to be tighter in the US. I don’t necessarily mean “formal” bounds between institutions but rather informal relations between people, who understand complex fields of knowledge, both in the academia and in business.

“I assume transferring knowledge between two proxies who speak the same ‘language’ makes it a lot easier”

PhD students, for instance, often work in business over the summer and/or continue their career in the research department of some company. Some continue their cooperation with their former professors and academic colleagues and I assume transferring knowledge between two proxies who speak the same “language” makes it a lot easier.

SWC: What are the most important things which are still missing to make linked data technologies an integral part of enterprise information systems?

Quite often I hear the complaint that major database vendors still don’t provide satisfactory RDF support in their products. I don’t think this is a necessary precondition for implementing Linked Data but for some institutions this seems to be very important.

Many thanks!

Related articles

• Linked Learning 2012, collocated with WWW2012 (linkededucation.wordpress.com)
• W3C Library Linked Data Reports (ivan-herman.name)

• automatic annotation of all blog entries displayed as tooltips
• a comfortable search facility with auto-complete over all concepts from the linked thesaurus including semantic search over the whole blog
• an integrated thesaurus browser, plus
• a corresponding linked data frontend including RDF/XML serialization of the underlying thesaurus + SPARQL endpoint

All details about the new version 2.2.3 can be read here.

Related articles

• Using DBpedia to generate SKOS thesauri (ablvienna.wordpress.com)
• PoolParty 3.0 and its all new Linked Data framework (semantic-web.at)

Image based on work by Paolo Mañalac

Thomas Schandl: An especially nice thing about this conference is that it’s co-location attracts people from two separate communities: Knowledge Management and Semantic Web. This serves as a natural facilitator for looking beyond the boundaries of one’s own domain and getting more than a glimpse of what’s currently happening in related fields.

That being said one of the most interesting talks I attended was a talk from KM expert Prof. Martin Eppler and his take on “Sketching at Work“, which introduced loads of sketching methods which can help to solve problems, inspire creativity and support communication.

From the Semantic Web side I enjoyed the innovative approach taken by Hasso Plattner Insitute‘s DBpedia powered quiz game Risq!. It is a Jeopardy-like Facebook game, that (besides being fun) sheds insights as to which facts are especially important to characterize a Linked Data resource. E.g. when the system wants you to guess a specific “female politician” would it help you more to know that she is part of the category yago:LivingPeople or would you rather get the hint that she is dbpedia:Chancellor_of_Germany?
By analyzing the logs of the played games, the researchers can find out which triples have more discriminative power than others.

Through the many personal encounters I also got a lot of input on which new features would be especially interesting for future versions of PoolParty and what we should concentrate on in the LOD interlinking project LASSO that Bernhard Schandl (Gnowsis / Refinder), Stefan Wunder (Neurovation) and me presented at the I-Praxis track.

Andreas Blumauer: Again, this year was absolutely worth coming to Graz also from a business perspective. For me it was the 10th time going to Graz. When I went to the second edition of I-KNOW in 2001 I remember that nearly nobody has ever heard of “semantics”. When I-SEMANTICS came to Graz the first time, this was in 2007, it was still unclear for most visitors how semantic technologies could contribute to a more efficient enterprise knowledge management. Nowadays, 10 years later, there is another question most prominent:

Which kind of semantic technology is solving my problem?

Being most of the time at our exhibition booth I enjoyed talking to visitors who had very concrete plans & ideas about how to use linked data, text mining or knowledge models for their business. The time when we had to explain what the “semantic web” is all about is over.

Christian Dirschl´s (Wolters Kluwer) keynote on Friday was exactly reflecting this fact: It´s good to see how big players have started to integrate the idea of linked data into their processes already. The days when we had to explain the difference between RDF and XML seem to be over. Or at least almost.

Florian Kondert: It was a vibrant atmosphere for me, since I didn’t make it to participate to just one track, but talking to interesting and interested persons at the booth without one break, instead.

From the participant’s perspective the conference as a networking platform was a huge success – and it definitely didn’t stop at dusk! It is worth pointing out the diverse needs and ideas on semantic use cases, that allow us to learn more with every discussion. The bottom line is that semantic solutions are badly needed for many organisations – and they start to realize, that there are no working alternatives at the moment.

On the other hand it is crucial to show up with real life examples, not just with prototypes that might work tentatively! As providers for semantic solutions we face decision makers on the highest level and they demand high level remedies – so, no time to take a break!

Tassilo Pellegrini: As the conference chair I really had an intense, but all in all very positive time at the conference. Interesting people, inspiring talks and a really good time at the socializing events (greetings to Leo Sauermann & Co. – I enjoyed the drinks!). For a general conference overview read my post from a few days ago.

But there is more to such a diverse conference as just talking about semantics. As some of you might know, beside my interest in Semantic Web, I have been involved in some policy consulting lately concerning the topic of net neutrality. At the conference I took the opportunity to talk to some telecommunications-savvy people and had some really great conversations (Harald … I really enjoyed our discussion!). But to my surprise I had to find out that – especially among the engineering guys – there seems to be very little awareness about the pressing social, cultural and economic consequences that an abandoning of net neutrality will have on the Internet as we know it today. For those readers who are into semantic web but not into the net neutrality discourse I want to reduce it to a very simple formula: without net neutrality you can say goodbye to linked open data. And this should really make us think and act!!

Related articles

• Semantic Web Company and punkt. netServices have merged (semantic-web.at)
• Looking back at I-SEMANTICS 2011 (semantic-web.at)

In PoolParty 3.0 we created a Linked Data interlinking editor, making it easier than ever to add your own lookup and interlinking services (even for non-RDF sources) and made the Linked Data publishing front-end fully customizable in design, layout and regards to which parts of your content will be displayed.

But let’s start at the beginning:

Step 1 – Hook into the Linked Data Cloud!

In the era of the rapidly growing Linked Data Cloud your knowledge models don’t need to stay isolated from the outside world anymore. Simply use PoolParty’s new and improved lookup service to find matching resources from the Linked Open Data Cloud (e.g. from DBpedia).

Imagine having different data models that all refer to the same product categories and world regions. Once you have them represented in PoolParty you can use its lookup service to find matching resources from the Linked Data Cloud. In this way you will get globally used identifiers for your product categories and regions, usually in the form of a URI like http://dbpedia.org/resource/Berlin. This eases your internal data integration efforts, and it can aid the data exchange with partners or customers and enables hassle-free distributed management of knowledge models.

Image 1: Lookup of concept ‘Austria’ and selection of properties and values to be imported

With PoolParty 3.0 we increased the number of included lookup services: DBpedia, Geonames, Wordnet, Umbel, Yago, Freebase, Sindice, dmoz and LCSH – BBC Wildlife, Enis and Gemet are available on request.

Step 2 – Pull in Semantic Data!

There is a vast amount of Linked Data out there just waiting to be leveraged for thesaurus creation and extension. To meet that end we had a close look at our interlinking module and decided to enhance it a way that it becomes more of a Linked Data editor.

Once you have a base thesaurus in PoolParty and hooked a couple of your concepts into the cloud as described above, you can proceed to pull in the good stuff that comes with the Linked Data resources you have found.

Image 2: Imported Linked Data for concept ‘London’

As you can see in the image above, you can extend your local thesaurus with labels, definitions and all kinds of other information like e.g. in the case of countries their population, GDP, spoken languages, famous people born there, newspaper articles related to the political situation, and so on.

Now PoolParty 3.0 takes this approach a couple of steps further. You can not only specify which of your local concepts corresponds to which Linked Data resource and grab all semantic information that comes with this resource, but now you are able to selectively pick out the data items you are interested in and even transform the predicates they originally came with. Just switch them to whatever custom properties you created or want to re-use from any ontology (see an example in Image 1).

In this way you can easily enrich your own knowledge models with external information – which in turn can be utilized for better content recommendation, easier data integration and improved search services.

Step 3 – Publish your Linked Data in Style

Previous PoolParty versions already offered the possibility to instantly publish your thesauri, taxonomies or vocabularies and display their concepts as HTML while additionally providing machine-readable RDF versions for them. This means that anyone using PoolParty intuitive GUI can become a W3C standards compliant Linked Data publisher without having to know anything about Semantic Web technicalities.
Of course you don’t need to publish all your valuable models, just choose the parts that safely can be shared with the public and keep everything else behind your firewall, available only to you and trusted partners!

In this new release of PoolParty the design of all pages on the Linked Data front-end is now under your full control. You can use your own style sheets and create views on your data with velocity templates. It is even possible to develop project- and thesaurus-specific templates and layouts, so they can have an individual look and display different predicates and their values.

Take a look at PoolParty´s standard linked data frontend!

The following images show a PoolParty default Linked Data page and a custom-made Linked Data page of a PoolParty concept that has some DBpedia info imported.

Image 3: PoolParty default Linked Data page

Image 4: Custom Linked Data page of ScOT thesaurus (courtesy of Educational Services Australia)

Step 4 – Unlock new Linked Data Sources

With PoolParty 3.0 you are in no way limited to DBpedia, Freebase, Geonames and the other lookup services that PoolParty provides out of the box: you can add your own non-Semantic Web data sources to the mix, thereby enabling you to boldly go where no Linked Data tool has gone before.

Maybe you have a product thesaurus and want to specify which products are related to patents that can be found with Google Patents?
Or you want to interlink concepts from a company taxonomy with related articles from the Guardian’s search service or any other newspaper that provides a search API?

All those sources are not available as RDF, so how can you re-use them easily as data sources for Linked Data style interlinking? For such cases PoolParty introduces the Unified Lookup API, which makes it easy to turn almost any third party Web API into a source for interlinking your concepts with third party resources as described above.

This makes it possible to interlink your concepts with many kinds of data out there, be it New York Times articles, UN data, synonym services, abbreviations, press releases, juridical information – or any web API important for your knowledge domain.

That being said, if you have suggestions for additional lookup services that you think are interesting, let us know!

To gain a first hand impression of the new PoolParty just apply for a demo account!

Thomas Thurner: Over the recent years the LOD movement gained tremendous momentum. As one of the key players in this area how do you perceive this development? Hype or hope?

Sören Auer: From my point of view the momentum LOD gained is deserved. We should strive for a Web, which is more decentralized, democratic, participatory, transparent and inclusive. Linked Open Data is from my point a key technological building block on this road. However, a lot of work is ahead of us. LOD has to find its way directly into mainstream technology such as CMSes, Search Engines, Web Applications, Mash-Ups and we have to show users and stakeholders the direct added-value of this technology.

Thomas Thurner: What is the current state of the LOD cloud from a technological point of view? Where do you see room for improvement?

Sören Auer: Currently, the technological state of LOD seems to be comparable to the early days of the Web. We are still able to draw maps/clouds of the LOD datasets and data links are still sparse and difficult to maintain. This reminds me a lot of the early days of the Web, where we also had problems with broken links (the infamous 404). Later, after content management systems and Web applications automatized the link generation and maintenance this improved a lot and I hope we are on the same road with LOD technologies finding its way into more and more Web systems.

Thomas Thurner: How is the LOD2 project addressing theses issues? What are the project’s key objectives?

Sören Auer: LOD2 is addressing in three ways: First, we develop new research approaches highly relevant for LOD, for example, for Linked Data management, automatic data linking as well as Linked Data enrichment andquality improvement. Second, we implement and integrate these approaches into specialized tools (e.g. SILK, OntoWiki, Virtuoso and DL-Learner) forming together the integrated LOD2 stack. The LOD2 stack can be used by data publishers for the whole life-cycle of Linked Data management ranging from extraction over linking, authoring, enrichment to exploration & search.

Thomas Thurner: What do you think are the most important factors to bring LOD to the masses?

Sören Auer: From my point of view the key factor here is that we manage to integrate the large number of tools and approaches for supporting the Linked Datalife-cycle stages in a synergistic way, where each aspect adds value and triggers a number of other improvements. For example, the establishing of a new data link has a direct effect on search & exploration of Linked Data. We have to directly show these kind of benefits to users so they receive and instant gratification for contributions to the Web of Data. Semantic Wikis, such as Semantic MediaWiki and OntoWiki, are already nicely working in this direction. An application with an enormous potential to bring LOD to the masses would be the creation of a distributed, social semantic network. With OpenId, WebId, FOAF, Semantic Pingback most of the building blocks are available, but the final step integrating these into an easy-to-use social networking application still has to be done.

Thomas Thurner: Compared to other semantic web approaches linked data principles seem to be rather easy to understand. On the other hand some argue that the “linked data cloud” is a big heap of data which cannot be used for professional purposes. What is your point of view?

Sören Auer: Of course the currently available data is not useful for all potential usage scenarios. However, already now Linked Data can be used for many interesting applications: For example, we just completed the development of a prototype for a large search engine, where users searching are assisted with comprehensive background information obtained from the Linked Data Web. For this use case, information available as Linked Data is already very valuable and useful. The criticism of LOD being a “heap of data” also reminds me a lot of the early days of the Web, where people raised similar criticisms for the Web being a medium of un-professionalism. Later it turned out that, of course there is a lot of amateurism, but as Wikipedia impressively demonstrates the working together of many amateurs with the right tools can in the end outperform few professionals.

Thomas Thurner: Linked Data could also become a new paradigm for light-weight enterprise data integration. What are the biggest obstacles today for linked data to being accepted by the business community?

Sören Auer: Using Linked Data for data integration in large enterprises has an enormous potential. Just last week I was invited for a workshop with the IT department of one of the top car makers and the people responsible there for data integration were extremely excited about the opportunities of Linked Data in the large heterogeneous enterprise with more than 3000 different backend systems. Linked Data technologies can easily fill the gap between unstructured Intranet search and expensive & complicated Service-oriented Architectures. Compared to SOA, Linked Data is a pay-as-you-go strategy, where data integration can be performed incementally and in sync with the requirements and evolution of the data structures in the enterprise. In order to realize this vision, we need to continue the maturation of enterprise Linked Data tools – the availability of PoolParty, Sindice Enterprise Edition, Virtuoso, TopBraid are already important steps in that direction.

Thomas Thurner: Automatic mechanisms to curate linked data and to make alignments between datasets possible play a crucial role for the next phase of linked data economics. Which technologies will play a central role? What will be the most critical point – do you see a “wisdom of the crowd” playing a role in this game?

Sören Auer: Definitely! Tapping the wisdom of the crowd for mapping & linking has a huge potential, which is currently unused. We started working in that direction with DBpedia Live and the DBpedia mapping Wiki. In order, to make it really easy for people to contribute we have to dramatically lower the barrier to contributing to the alignment process. In LOD2 we also plan to enable users to create mapping and links between dataset by simply giving examples of correct links and evaluating some automatically generated ones.

Thomas Thurner: At the moment governments all around the world start to publish open data, more and more stakeholders start to understand the benefit of open linked data. On the other hand enterprises haven´t even started with this topic. What could be the dynamics which will trigger projects in industry sectors like financial industries which will make use of open data principles?

Sören Auer: Making statistical and financial information available in structured form and as Linked Data could have a enormous impact in this regard. With the DataCube vocabulary effort a first step in this direction was made, but it would be nice if this vocabulary would get an official stamp of a standardization organization such as W3C. Since the benefit of publishing statistical and financial data in structured form, e.g. as Linked Data, is visible most when done by many, this could be also facilitated by government regulations and industry best-practices.

About INFAI

The Institute for Applied Computer Science (InfAI) at Universität Leipzig hosts research groups in service sciences, knowledge engineering and management as well as natural language processing. The approximately 20 researchers of the Agile Knowledge Engineering and Semantic Web (AKSW) research group at InfAI headed by Dr. Sören Auer are establishing theoretical results and scalable implementations for the field. Particular emphasis is given to areas such as ontology creation and
manipulation, knowledge extraction, ontology learning and information & data integration on the Semantic Data Web. The implemented tools and services (such as DBpedia, OntoWiki, DL-Learner and LinkedGeoData) developed by the group enjoy considerable popularity.

About Sören Auer

Dr. Sören Auer leads the research group Agile Knowledge Engineering and Semantic Web (AKSW) at Universität Leipzig. His research interests include semantic data web technologies, knowledge representation, engineering & management, usability, agile methodologies as well as databases and information systems. He aims to combine strong theoretical results with high-impact practical applications. Sören is author of over 50 peer-reviewed scientific publications resulting in a Hirsch index of 15. Sören is leading the large-scale integrated EU-FP7-ICT research project “LOD2 – Creating Knowledge out of Interlinked Data”. Sören is founder (respectively co-founder) of several high-impact research and community projects such as the Wikipedia semantification project DBpedia or the social Semantic Web toolkit OntoWiki. He is co-organiser of several workshops, programme chair of I-Semantics 2008, OKCON 2010, ESWC 2010 and ICWE 2011, area editor of the Semantic Web Journal, serves as an expert for industry, the European Commission, the W3C and is member of the advisory board of the Open Knowledge Foundation.

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.

The interviewee: Hjalmar is a successful entrepreneur, founder of three startups in the gaming, mobile and web sectors since 1996. Prior to launching DataMarket, Hjalmar worked on new media and business development for companies in the Skipti Group (owners of Iceland Telecom) after their acquisition of his search startup – Spurl. Hjalmar offers a mix of business, strategy and technical expertise.

Drupal is the leading CMS when it comes to implementing Semantic Web standards. What are the reasons for this, what makes Drupal such a good fit for Semantic Web technologies?

Historically, Drupal is known to be web standard compliant. It supported the RDF-based aggregation format known as RSS 1.0 as early as in 2001, which was later upgraded to RSS 2.0. The Drupal community prides itself in valid HTML code, not only for the code generated by Drupal, but also by taking the extra step of automatically fixing faulty HTML entered by its users. Drupal has been using XHTML since its version 4.0 in 2002. The next logical step beyond XHTML was to add a layer of semantics with the RDFa standard, a W3C recommendation published in 2008.

There are definitely many reasons that contributed to the addition of RDFa into Drupal 7. The first comes from the Drupal project lead, Dries Buytaert, who is passionate about the web and open source. Secondly, the growing Drupal community is very web savvy and includes many experts from different backgrounds in accessilibity, CSS, HTML, security etc. As a result, every release of Drupal includes many latest standards. The community meets twice a year at conferences (DrupalCons), thes events play a great role in hashing out what technologies or designs will be incorporated into the next version of Drupal. Because of the flexibility of its internal architecture, Drupal is able to keep up with the latest web standards. Content in Drupal is very structured and provides site administrators with a user interface to build the site structure they want, using entity types, content types, fields and taxonomies for categorization. When it comes to other CMSs, Joomla!’s community appears to be more fragmented with a core software that is not as extensible as Drupal and WordPress is more of a blogging platform, so turning it into a full blown CMS can be challenging. Both WordPress and Joomla! are in fact adapting the concept of Drupal’s Content Construction Kit (CCK) to their software but they have not yet reached the same level of maturity as Drupal.

A common objection to the adoption of Semantic Web technologies is that the learning curve is steep and that it is too complicated for many web developers to get into it. How can Drupal 7 change that? Which features accessible for the average web site operator will it offer?

Semantic Web technologies don’t have to be complicated when applied to simple use cases! We purposely chose only of a subset of semantic web technologies to integrate into the core of Drupal, keeping the learning curve for the Drupal developers and users as low as possible. The main technology is RDFa which includes the notions of vocabularies (a schema, or collection of attributes) as well as Compact URIs (CURIEs) which make the authoring of RDFa easier. In fact, some web developers might have come across these notions before when working with Dublin Core in the meta tags as such dc:title or dc:date.

Which benefits will web site owners get when they switch to a semantics enabled Drupal 7?

Google and Bing increasingly rely on machine-readable structured data from the websites that they crawl. The design of Drupal 7 embeds semantic meta data that makes machine-to-machine (M2M) search native for a Drupal 7 website. RDFa can add value by giving search engines more details such as the latitude and longitude of a venue for display on a map; or providing the ISO date format for localization and proper display in the search results for different countries.

What are your hopes regarding the development of other applications that either provide or consume data from D7 sites? Which improvements of standards, best practices or (lightweight) ontologies in the Semantic Web community would you like to see?

Services like Sig.ma are already able to collect semantic data from different sources and display it in new ways in the form of mash-ups. Eventually, these services that consume semantic data will not be just Drupal specific, as more platforms jump on the semantic web band wagon. What I hope to see as improvements or best practices in the future are more well-maintained vocabularies. Many of the existing vocabularies are over engineered, some fail to de-reference properly. Their is also some work to be done in order to improve the tooling made available to web developers as well as introducing the simple concepts of Linked Data to web developers via easy to read documentation.

Thank you for this interview, Stéphane!

Open Data, Open Government, Open Source, Open Innovation – “Open” everywhere. Today I want to talk about another “Open something”: The “Open Intranet”. This might sound a bit radical but it will also help to reflect a little bit on the term “open” in general.

“Open Intranet” – isn´t this a contradiction by definition? What is understood by “Intranet”? It means a network of computers and users “within” some organisational boundaries. But boundaries don´t necessarily have to be closed as nature teaches us: Organisms aren´t closed systems. A watch would be an example for a closed system but living organisms tend to be open – to survive. Of course they aren´t totally open, in systems theory we are talking about systems which are structurally coupled with their medium when we refer to this special kind of openness. As an example, an immune system, having learned to recognise a class of virus it will remain sensitive to that and similar viruses in future. In contrast to this, imagine a fly walking over a painting of Rembrandt: Since the fly isn´t structurally coupled to the cultural space of human aesthetics it is not “open” to the beauty of Rembrandt´s work.

When we think of today´s intranets, we can see that they tend to be isolated from the world wide web, they don´t seem to perceive the internet as their medium. From a user perspective, those two systems aren´t connected to each other. Typically, when working on the intranet we jump from time to time to be in the “internet mode” and start to Google something, we copy it, jump back and paste it into the intranet. It´s the user who is the only part of the whole system connecting the internet with the intranet. Isn´t this exhausting for us?

And now I start with the good news: Intranets all over the world start to open up, slowly – but they do. It seems like the “pressure” from “the outside” just became too huge. In the first instance it seems that it´s not the data and the information which will “break” in, it´s rather the “cool functions” which web apps offer and which we (as digital natives) would like to have in our intranets too. We want:

• better search,
• more possibilities to interact with information,
• integrated views instead of jumping around,
• and we want more possibilities to self-serve our extensive hunger for more and well structured information.

On the information level intranets are still rather conservative: Typical pieces of information already “injected” from the web into an average intranet would be:

• weather forecasts,
• stock exchange rates,
• time zones and
• jokes.

How could companies use the web to inspire their employees (without opening up totally), how could the web “inject” the right amount of information into an intranet to make an enterprise portal as vivid as the web is being perceived by today´s typical end-user. How could this tremendous amount of data and knowledge on the web be “structurally” coupled with intranet repositories and workflows? What are the advantages a company could gain from publishing (at least some) data on the web?

Let me give you a few examples for intranet apps which have started to consume other information than jokes from the web:

• Enterprise Mashups: Combine CRM systems with social networks like LinkedIn
• Open innovation: Let´s bring the knowledge of consumers and producers together and improve certain products and services. As an example, just recently after BP´s oil spill more than 40.000 people came up with ideas on how to clean up  the oil, more than two dozen were deployed to help clean up the oil
• Content Augmentation: Enrich content which is being edited, let´s say in an enterprise wiki, automatically with some background knowledge from Wikipedia or with news from a news company

Finally I will also give you two examples for use cases where companies expose and publish internal data on the web (without violating privacy) and benefit from it.

• Wisdom of the crowd: The Canadian gold mining group Goldcorp made 400 megabytes of geological survey data available to the public over the Internet. They offered over $500,000 to anyone who could analyze the data and suggest places where gold could be found. The company claims that the contest produced 110 targets, 8 million ounces of gold, worth more than $3 billion.
• Prize economics: Netflix, a movie rental service in the US has published data for a contest to improve their recommender engine. One team out of 50.000 contestants after nearly 3 years has improved the existing recommender engine by more than 10% and won 1 Million dollar

To end with a conclusion: What Tim Berners-Lee has demanded in one of his famous TED talks was “raw data now!”. It has started to become reality. Just think of all the “Open Government Data Initiatives” around the globe which were initiated since then. Now companies with a “Web DNA” have started to understand the value of open data and to contribute their “5 cents” to the global “open data cloud”. I think this will not only be of value for many companies but also will increase tremendously the chances to resolve some global problems in the near future.