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.

Linked Open Data: The Essentials provides answers to the following key questions:

• What do the terms Open Data, Open Government Data and Linked Open Data actually mean, and what are the differences between them?
• What do I need to take into account in developing a LOD strategy?
• What does my organisation need to do technically in order to open up and publish its datasets?
• How can I make sure the data is accessible and digestible for others?
• How can I add value to my own data sets by consuming LOD from others?
• What can be learned existing best practices?
• What are the key potentials of sharing and consuming open datasets?

Read more about this publication and find out how to obtain a copy.

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)

Let me introduce you to SKOSsy. I will explain what this web service can do for you:

SKOSsy generates SKOS based thesauri in German or in English for a domain you are interested in. Not any domain but nearly any: SKOSsy extracts data from DBpedia, so it can cover anything which is in DBpedia. Thus, SKOSsy works well whenever a first seed thesaurus should be generated for a certain organisation or project. If you load the automatically generated thesaurus into an editor like PoolParty Thesaurus Manager (PPT) you can start to enrich the knowledge model by additional concepts, relations and links to other LOD sources. But you don´t have to start in the open countryside with your thesaurus project.

Let me give you an example: Imagine you are working for a company which is an international plant builder and you would like to index several thousands of documents the “semantic way”. You have to walk through the following steps:

1. Identify proper categories in Wikipedia/DBpedia which describe best what your business or your domain is all about. Those categories should contain pages / resources which are related to the documents you would like to index. For example: http://dbpedia.org/resource/Category:Metalworking or http://dbpedia.org/resource/Category:Industrial_automation
2. After you have selected proper categories SKOSsy will traverse DBpedia for you and collect all resources, their hierarchical and non-hierarchical relations, alternative labels, definitions and other properties and put them together as a valid SKOS thesaurus; this step will last a couple of minutes. (Find the resulting vocabulary here)
3. Load the resulting thesaurus into PPT, explore it, improve it and enrich it with additional facts.
4. After you´re done you can generate a tailor-made text extractor by using PoolParty Extractor (PPX) which is the second component of PoolParty product family
5. With PPX and its extraction model especially curated for your special use case you can extract named entities from your documents automatically and index your documents in a meaningful way.
6. After a few seconds your semantic search engine is ready to be used. PoolParty Semantic Search (PPS) which is the third PoolParty component will offer some nice facilities like categorized auto-complete, faceted search, content recommendation (similarity search) and smart search suggestions to ease your life as a knowledge worker.

We have constantly discussed the application of thesauri and other knowledge models to improve search over the last years. Many people understood straight away why thesaurus based search is most often much better than search algorithms purely based on statistics. Of course the big contra always was, “the costs are too high to establish a “good-enough” thesaurus or even a “high-quality” one”.

With SKOSsy in place those kinds of arguments become weaker and weaker. To sum up,

• SKOSsy makes heavy use of Linked Data sources, especially DBpedia
• SKOSsy can generate SKOS thesauri for virtually any domain within a few minutes
• Such thesauri can be improved, curated and extended to one´s individual needs but they serve usually as “good-enough” knowledge models for any semantic search application you like
• SKOSsy based semantic search usually outperform search algorithms based on statistics since they contain high-quality information about relations, labels and disambiguation
• SKOSsy works perfectly together with PoolParty product family

If you are interested in the results produced by SKOSsy, just send us a short note about your domain or your project and we will send you an invitation as beta-tester or prepare a demo for you.

Related articles

• Geological Survey Austria launches thesaurus project (semantic-web.at)
• PoolParty 3.0 and its all new Linked Data framework (semantic-web.at)
• PoolParty DemoZone Content Extractor Semantic Search Thesaurus Manager (poolparty.punkt.at)
• Query DBpedia for multiple keywords (stackoverflow.com)

The Thesaurus Project of the GBA aims to create controlled vocabularies for the semantic harmonization of map-based geodata. The content-related realization of this project is governed by the Thesaurus Editorial Team, which consists of domain experts from the Geological Survey of Austria. With the development of semantically and technically interoperable geo-data the Geological Survey of Austria implements its legal obligation defined by the EU-Directive 2007/2/EC INSPIRE and the national “Geodateninfrastrukturgesetz” (GeoDIG), respectively.

Marcus Ebner, from the GBA Thesaurus Editorial Team

The construction of the thesauri has been done using the PoolParty Thesaurus Manager so they all are based on SKOS and fully compliant to the Linked Data principles. Apart from the standard implementation of SKOS some additions were made to the data model using Dublin Core terms for extra metadata and custom sub properties of skos:related to give some semantic constraints to related properties. This basically means that a big effort was put into the integration of bibliographic references for every concept in the data set using dcterms:source. This aims at the requirements of reuse by the scientific community and incorporation in domain specific data sets. On the other hand rdfs:subProperityOf was used to express how international geologic time scales map on regional concepts.

Currently four thesauri have been published, all are available in English and German and can be used under the cc-by-sa license. Also mappings to DBpedia have been made:

• Lithologic Units
• Geologic Timescale
• Geologic Units
• Lithotectonic Units

With the new PoolParty Release (3.0) the Linked Data front-end has been redesigned and is now highly customizable and extendable. In the GBA Thesaurus Project it is used as an publishing interface for the created controlled vocabularies both for the machine readable RDF version and an custom HTML version for comfortable browsing and searching.

GBA Linked Data frontend

After all it’s satisfying to see a project we’ve supported and worked on for some time now come to live and now we are looking forward to the next steps that will be done in this project.

P.S.: Thanks to Marcus Ebner from GBA for his contribution to his blog post.

The best paper award went to Pablo N. Mendes, Max Jakob, Andrés García-Silva and Christian Bizer for their contribution “DBpedia Spotlight: Shedding Light on the Web of Documents“.

Abstract: The paper impressively shows how Linked Open Data can be utilized  as background knowledge within document-oriented applications such as search and faceted browsing. As a step towards interconnecting the Web of Documents with the Web of Data, the authors developed DBpedia Spotlight, a system for automatically annotating text documents with DBpedia URIs. DBpedia Spotlight allows users to configure the annotations to their specific needs through the DBpedia Ontology and quality measures such as prominence, topical pertinence, contextual ambiguity and disambiguation confidence. They compare their approach with the state of the art in disambiguation, and evaluate their results in light of three baselines and six publicly available annotation systems, demonstrating the competitiveness of the system. DBpedia Spotlight is shared as open source and deployed as a Web Service freely available for public use.

For the 4th time I-SEMANTICS hosted the Triplification Challenge, an event aiming at stimulating the availability of large quantities of RDF data and showcasing practical applications built on top of them. The Challenge consisted of an unspecific “open data track” and a dedicated “open government data track” for which one winner was selected. The prize money of 1000 Euro each was sponsored by Wolters Kluwer Germany.

The “open data track” award went to Daniel Garijo, Boris Villazón and Oscar Corcho for their contribution “A Provenance-Aware Linked Data Application for Trip Management and Organization“.

Abstract: The authors present El Viajero, an application for exploiting, managing and organizing Linked Data in the domain of news and blogs about travelling. El Viajero makes use of several heterogeneous datasets to help users to plan future trips, and relies on the Open Provenance Model for modeling the provenance information of the resources.

The “open government data track” award went to John Erickson, Yongmei Shi, Li Ding, Eric Rozell, Jin Zheng and Jim Hendler for their contribution “TWC International Open Government Dataset Catalog“.

Abstract: The TWC International Open Government Dataset Catalog (IOGDC) integrates a diverse selection of more than 70 government dataset catalogs from around the world. IOGDC demonstrates a practical dataset catalog metadata model for integrating diverse dataset catalogs collected from the real world and linking those catalogs into Linked Data Cloud. IOGDC’s faceted browsing and search interface provides a scalable and reconfigurable solution for finding and browsing open government datasets which also offers a compelling demonstration of the value of a common metadata model for open government dataset catalogs. We believe that the vocabulary choices demonstrated by IOGDC highlight the potential for useful Linked Data applications to be created from open government catalogs and will encourage the adoption of such a standard worldwide.

All papers are available in the ACM Digital Library.

We thank all participants for their contributions and wish the winners all the best for their future work!

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!

Here are three of the most interesting outcomes of this questionnaire – the whole report can be found and downloaded on issuu:

Do you think enterprises and other organizations can significantly benefit from using Linked Data?

The answer is a clear YES. A subsequent question also reveals that all kind of organisation sizes have about the same opinion concerning linked data. Only few people think that linked data is a “niche thing”. In general it can be said, that over 90% of the participants think that most or at least some organisations can benefit from using linked data.

Do you think that search engines which utilize thesauri to improve results will become main-stream

The results of this question are amazing: Two thirds of the participants think that thesaurus based search is already or will become main-stream in the near future. Scepticism towards this development seems to be low – at least it can be stated, that a clear majority thinks that thesaurus based search engines will become main stream in the near future.

How important is the usage of standards like SKOS for controlled vocabularies?

The results speak for themselves. The majority of the participants are convinced that standards like SKOS are important for their daily work. In August 2009 W3C announced the new SKOS standard – now, nearly two years after, it looks like this standard has well arrived. 48.7% stated that standards like SKOS are very important and 29.1% voted for “relevant”.

As an overall result of the survey it can be stated: Semantic Web community has done a great job to convince the controlled vocabulary people to benefit from SKOS and linked data – on the other side only 3-5% are aware of SPARQL as a valuable resource to build standard APIs around controlled vocabularies to lower costs when implementing such knowledge organization systems.

Many thanks to all participants of this survey!

Just recently Alexandre Passant from DERI Galway went public with a new web service called seevl. First impressions after test driving the system reveal that the seevl team is keeping the promises they have made: “Seevl reinvents music discovery. We provide new ways to explore the cultural and musical universe of your favorite artists and to discover new ones by understanding how they are connected. In addition, we let you comment every piece of data about them.”

I was talking with Alexandre and asked a couple of questions:

Q: seevl.net aims to offer a new way of music recommendations. What exactly can the user expect from it?
The main idea is to offer context around the recommendations, while existing systems are opaque, or rely on collaborative filtering techniques. So that a user know why he could / should like X if he’s browsing page about Y. We hope (and we’ve seen it from our user feedback so far) that it can help to discover new bands and hidden connections.

Q: Yes, indeed this is something new. Maybe for the typical users this could be too complicated. This brilliant feature should somehow be hidden – working just like a magic button?
So far, we include this in the “why is related” button, but we’re constantly working on the UI / UX. Also, we only provide text for now, but are working on dataviz interfaces.

Q: seevl offers for developers a Web API. It seems like you don´t use semantic web standards for that?
We use content-negotiation to provide machine-readable data for every page (search results, entity description, related artists, etc.). If by non-SW standards you mean non-RDF, indeed, we provide JSON instead of RDF/XML or N3, etc. But our JSON integrates URI that you can dereference and follows a similar approach than other existing RDF-JSON serialisation. So, why JSON you may ask. Because our developer target is music hackers, and all APIs from this community (last.fm, echonest, etc.) offer JSON, not RDF. Learning a new JSON schema takes 5 min, learning RDF takes much more.
But we believe that a JSON-RDF serialisation combines the best of both worlds. Actually, we could say we provide our data using standards (we’re giving back a graph that follows the RDF abstract model, with links to dereferencable URIS) but not in a (so far) standardised serialisation.

Q: I agree. But mid-term oriented I would go additionally for SPARQL. A lot of people learn how to SPARQL at the moment.
Yes, we have to measure the cost / ROI. Complete SPARQL can lead to complex queries, that’s why they are somehow hidden behind our search interface (that basically construct a controlled SPARQL query). But that could be something provided to advanced customers.

Q: seevl.net is based on linked data sets like DBpedia, MusicBrainz or Freebase. Is seevl itself offering Linked (Open) Data? I can also see heavy use of the open graph protocol. How could a facebook application of seevl could look like?
Yes, we provide our data back at http://developers.seevl.net. We’re using the Music Ontology and a bit of other models (FOAF, etc.). So far, the OGP markup is used for Facebook likes – but we are looking at other things that could be built on top of this.

Q: Which business model are you following? Can one integrate your service into his shop? would you offer this a cloud service? for how much?
We’ll have B2C (new features on the website are coming soon) and a B2B freemium model. We’re currently identifying how much calls we can support as part of the free-calls per day (so that will indeed be cloud-based, our architecture is on EC2). So, integration of our service / data in shop websites, etc. is definitely what we’d like to see and to feature in our upcoming app-gallery ! The only requirement for data-reuse is attribution and linking-back to the service.

Thanks Alex, and I wish you and your team all the best with seevl.net!

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.