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Author Archives: paulgroth

Source: Think Links

Technology at its best lets us do what we want to do without being held back by time consuming or complex processes. We see this in great consumer technology: your phone giving you directions to the nearest cafe, your calendar reminding you of a friend’s birthday, or a website telling you what films are on. Good technology removes friction.

While attending the SURF Research day, I was reminded that this idea of removing friction through technology shouldn’t be limited to consumer or business environments but should also be applied in academic research settings. The day showcased a variety of developments in information technology to help researchers do better research. Because SURF is a Dutch organization there was a particular focus on developments here in the Netherlands.

The day began with a fantastic keynote from Cameron Neylon outlining how networks qualitatively change how research can be communicated. A key point was that to create the best networks we need to make research communication as frictionless as possible.  You can find his longer argument here. After Cameron’s talk, Jos Engelen the chairman of the NWO (the Dutch NSF) gave some remarks. For me, the key take-away was that in every one of the Dutch Government’s 9 Priority Sectors, technology has a central role in smoothing both the research process and its transition to practice.

After the opening session, there were four parallel sessions on text analysis, dealing with data, profiling research, and technology for research education. I managed to attend parts of three of the sessions. In the profiling session, the recently released SURF Report on tracking the impact of scholarly publications in the 21st century, sparked my interest.  Finding new faster and broader ways of measuring impact (i.e. altmetrics)  is a way of reducing friction in science communication. The ESCAPE project showed how enriched publications can make it easy to collate and browse related content around traditional articles. The project won SURF’s enriched publication of the year award. Again, the key, simplifying the research process.  Beyond these presentations, there were talks ranging from making it easier to do novel chemistry to helping religious scholars understand groups through online forms. In each case, the technology was successful because it eliminated friction in the research process.

The SURF research day presented not just technology but how, when it’s done right, technology can make research just a bit smoother.

Filed under: academia, altmetrics Tagged: events, ozdag, surffounation

Source: Think Links

I had a nice opportunity to start out this year with a visit to the Information Sciences Institute (ISI) in Southern California’s beautiful Marina del Rey .  I did my postdoc with Yolanda Gil at ISI and we have continued to have an active collaboration, recently, doing work on using workflows for exposing networks from linked data.

I always get a jolt of information visiting ISI. Here are five pointers to things I learned this time:

1. The Karma system [github] is really leading the way on bringing data integration techniques to linked data. I’ll definitely be looking at Karma with respect to our development of the Open PHACTS platform.

2. I’m excited about change detection algorithms in particular edit distance related measures for figuring out how to generate rich provenance information in the Data2Semantics project. These are pretty well studied algorithms but I think we should be able to apply them differently. A good place to start is the paper:

3. Also with respect to provenance, after talking with Greg Ver Steeg, I think Granger Causality and some of the other associated statistical models are worth looking at. Some pointers:

4. Tran Thanh gave a nice overview of his work on Semantic Search. I liked how he combined and extended the information retrieval and database communities work using Semantic Web techniques. Keyword: Steiner Trees

5. MadSciNetwork is a site where scientists answer questions from the public. This has been around since 1995. They have collected over 40,000 answered science questions. This corpus of questions is available at MadSci Network Research. Very cool.

Finally… it’s nice to visit southern california in January when you live in cold Amsterdam :-)

 

 

Filed under: academia, linked data, provenance markup Tagged: pointers

Source: Think Links

I had a nice opportunity to start out this year with a visit to the Information Sciences Institute (ISI) in Southern California’s beautiful Marina del Rey .  I did my postdoc with Yolanda Gil at ISI and we have continued to have an active collaboration, recently, doing work on using workflows for exposing networks from linked data.

I always get a jolt of information visiting ISI. Here are five pointers to things I learned this time:

1. The Karma system [github] is really leading the way on bringing data integration techniques to linked data. I’ll definitely be looking at Karma with respect to our development of the Open PHACTS platform.

2. I’m excited about change detection algorithms in particular edit distance related measures for figuring out how to generate rich provenance information in the Data2Semantics project. These are pretty well studied algorithms but I think we should be able to apply them differently. A good place to start is the paper:

3. Also with respect to provenance, after talking with Greg Ver Steeg, I think Granger Causality and some of the other associated statistical models are worth looking at. Some pointers:

4. Tran Thanh gave a nice overview of his work on Semantic Search. I liked how he combined and extended the information retrieval and database communities work using Semantic Web techniques. Keyword: Steiner Trees

5. MadSciNetwork is a site where scientists answer questions from the public. This has been around since 1995. They have collected over 40,000 answered science questions. This corpus of questions is available at MadSci Network Research. Very cool.

Finally… it’s nice to visit southern california in January when you live in cold Amsterdam :-)

 

 

Filed under: academia, linked data, provenance markup Tagged: pointers

Source: Think Links

The VU University Amsterdam computer science department has been a pioneer at putting structured data and Semantic Web into the undergraduate curriculum through our Web-based Knowledge Representation. I’ve had the pleasure of teaching the class for the past 3 years. The class is done in a short block of 8 weeks (7 weeks if you give them a week for exams). It’s a fairly complicated class for second year undergraduates but each year the technology becomes easier making it easier for the students to ground the concepts of KR and Web-based data into applications.

The class involves 6 lectures covering the major ground of Semantic Web technologies and KR. We then give them 3 1/2 weeks to design and hopefully build a Semantic Web application in pairs. During this time we give one-on-one support through appointments. For most students, this is the first time they’ve come into contact with Semantic Web technologies.

This year they built applications based on The Times Higher Education 2011 World University rankings. They converted databases to RDF, developed their own ontologies, integrated data from the linked data cloud and visualized data using sparql. I was impressed with all the work they did and I wanted to share some of their projects. Here are four screencasts from the applications the students built.

Points of Interest Around Universities

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Filed under: academia, linked data Tagged: education, linked data, semantic web, student, vu university amsterdam, web-based knowledge representation

Source: Think Links

The VU University Amsterdam computer science department has been a pioneer at putting structured data and Semantic Web into the undergraduate curriculum through our Web-based Knowledge Representation. I’ve had the pleasure of teaching the class for the past 3 years. The class is done in a short block of 8 weeks (7 weeks if you give them a week for exams). It’s a fairly complicated class for second year undergraduates but each year the technology becomes easier making it easier for the students to ground the concepts of KR and Web-based data into applications.

The class involves 6 lectures covering the major ground of Semantic Web technologies and KR. We then give them 3 1/2 weeks to design and hopefully build a Semantic Web application in pairs. During this time we give one-on-one support through appointments. For most students, this is the first time they’ve come into contact with Semantic Web technologies.

This year they built applications based on The Times Higher Education 2011 World University rankings. They converted databases to RDF, developed their own ontologies, integrated data from the linked data cloud and visualized data using sparql. I was impressed with all the work they did and I wanted to share some of their projects. Here are four screencasts from the applications the students built.

Points of Interest Around Universities

Guess Which University

Find Universities by Location

SPARQL Query Builder for University Info



Filed under: academia, linked data Tagged: education, linked data, semantic web, student, vu university amsterdam, web-based knowledge representation

Source: Think Links

It’s nice to see where I work (VU University Amsterdam) putting out some nifty promotional videos on YouTube. Here are two from the Computer Science department and the Network Institute both of which I’m happy to be part of.

 

 

Filed under: academia Tagged: computer science, network institute, vu university amsterdam

Source: Think Links

It’s nice to see where I work (VU University Amsterdam) putting out some nifty promotional videos on YouTube. Here are two from the Computer Science department and the Network Institute both of which I’m happy to be part of.

 

 

Filed under: academia Tagged: computer science, network institute, vu university amsterdam

Source: Think Links

This past Tuesday, I had the opportunity to give a webinar for Elsevier Labs giving an overview of altmetrics. It was a fun opportunity to talk to people who have a great chance to influence the next generation of academic measurement. The slides are embedded below.

At the VU, we are also working with Elsevier Labs on the Data2Semantics project where we are trying to enrich data with additional machine understandable metadata. How does this relate to metrics? I believe that metrics (access, usage, etc) can be e a key piece of additional semantics for datasets. I’m keen to see how metrics can make our data more useful, findable and understandable.

 

Filed under: altmetrics Tagged: #altmetrics, data2semantics, presentation

Source: Think Links

This past Tuesday, I had the opportunity to give a webinar for Elsevier Labs giving an overview of altmetrics. It was a fun opportunity to talk to people who have a great chance to influence the next generation of academic measurement. The slides are embedded below.

At the VU, we are also working with Elsevier Labs on the Data2Semantics project where we are trying to enrich data with additional machine understandable metadata. How does this relate to metrics? I believe that metrics (access, usage, etc) can be e a key piece of additional semantics for datasets. I’m keen to see how metrics can make our data more useful, findable and understandable.

 

Filed under: altmetrics Tagged: #altmetrics, data2semantics, presentation

Source: Think Links

The Journal of Web Semantics recently published a special issue on Using Provenance in the Semantic Web edited by myself and Yolanda Gil. (Vol 9, No 2 (2011)). All articles are available on the journal’s preprint server.

The issue highlights top research at the intersection of provenance and the Semantic Web. The papers addressed a range of topics including:

  • tracking provenance of DBpedia back to the underlying Wikipedia edits [Orlandi & Passant];
  • how to enable reproducibility using Semantic techniques [Moreau];
  • how to use provenance to effectively reason over large amounts (1 billion triples) of messy data [Bonatti et al.]; and
  • how to begin to capture semantically the intent of scientists [Pignotti et al.].
 Our editorial highlights a common thread between the papers and sums them up as follows:

A common thread through these papers is the use of already existing provenance ontologies. As the community comes to an increasing agreement on the commonalities of provenance representations through efforts such as the W3C Provenance Working Group, this will further enable new research on the use of provenance. This continues the fruitful interaction between standardization and research that is one of the hallmarks of the Semantic Web.

Overall, this set of papers demonstrates the latest approaches to enabling a Web that provides rich descriptions of how, when, where and why Web resources are produced and shows the sorts of reasoning and applications that these provenance descriptions make possible

Finally, it’s important to note that this issue wouldn’t have been possible without the quick and competent reviews done by the anonymous reviewers. This is my public thank you to them.

I hope you take a chance to take a look at this interesting work.

Filed under: academia, linked data Tagged: journal, linked data, provenance, semantic web