A backdoor to what you are ‘supposed’ to discover

For centuries libraries and their librarians operated as gatekeepers and experts in preservation. They were the providers of information in a paper paradigm. Libraries held paper copies from books and journals full of knowledge. They held the key to access the information in their resources and refer to other libraries’ resources.  The dominant provision of information has changed with the arrival of the Internet. Most information is now digitally shared and exchanged online. [1]

A growing number of Web 2.0 Services such as MendeleyBibsonomy and citeulike are disclosing information from a huge amount of resources. However it is still a troubling task for users to check all those services one by one as they each provide access to a (small) part of the entire available information ‘cloud’…

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Presentation on RDSRP’11

Last week I presented our work on the I-KNOW 2011 Special Track on Recommendation, Data Sharing, and Research Practices in Science 2.0 in Graz.You can find a link and citation to our publication here. In this post I include the presentation slides including the demo movie used during our session on Wednesday 7th of September. Read more of this post

Explore your Social Circle, improve your Research

If you have a Twitter account and want to register in Grabeeter (or already have), you can now try out and take part in the evaluation of the “Researcher Affinity Browser“. Grabeeter is a tool to archive and search your tweets. The Researcher Affinity Browser is one of the first to expose affinities between Twitter users and is the first web application built on top of a semantic profiling framework. It is intended for researchers who are using Twitter for microblogging and are tweeting about their research, their interests or the conferences they are attending or tracking.

Researcher Affinity Browser

Researcher Affinity Browser

The semantic profiling framework grew throughout this year as my thesis project and information about the evolutions is presented here on this blog.

So if you are a researcher and are using Twitter, you are most welcome to explore people who have already registered themselves in Grabeeter. You can register from inside the application or here. After registration you have to wait a few hours before your data is analysed and suggestions can be made for you. Once you are registered you can start exploring people by selecting your username.
Important Notes

1. You can evaluate the application by filling out the form that can be accessed by clicking on the “Evaluate”-button inside the application or by using this form.

2. You can also evaluate the application with a default user if you feel uncomfortable or don’t want to wait for your data to be analyzed. Just click the Load Persons button without selecting a user in the list. The default user is selected because it has the most conferences.

Progress Report 4

This report is a presentation. I presented it today for members of the research group and fellow thesis students at the KULeuven.

Scientific Profiling Presentation

It explains the evaluation approach for the framework. The term “affinity” is being introduced for the first time. Before terms like shared resources or common entitities and interests were used.

“Affinities” expresses much better the user-centric perspective and the fact that it is a subjective notion. It also means that it is not only linked to a certain person but is also time-sensitive, something that could be called a “user context”.


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Open Innovation Problem Solver Search

This project presents a case in which technical scientists are linked to each other. The intention is to connect scientists that have similar interests. In “Open Innovation” experts of different institutions and companies try to collaborate and increase the rate of technological innovation. M. Stankovic wrote a paper [1] to check if linked data contributes in these efforts. Read more of this post

Are hashtags a good choice as linked data identifiers?

In this project hashtags are used as the most important identifiers to link users. The tags are considered as good identifiers because the user intends and attaches the hash to engage in a conversation in which others use this hashtag. But does it make sense to conclude that they are also good identifiers in linked data?

In the paper “Making Sense of Twitter” [1], David Laniado and Peter Mika first took a look at whether hashtags behave as strong identifiers, and thus whether they could serve as identifiers for the Semantic Web. Twitter users have adopted the convention of adding a hash at the beginning of a word to turn it into a hashtag. Hashtags are meant to be identifiers for discussions that revolve around the same topic. When used appropriately, searching on these hashtags would return messages that belong to the same conversation (even if they don’t contain the same keywords), and thereby solving the aggregation prob- lem. Coincidentally, this is the same function that strong identifiers (URIs) play in the Semantic Web. The questions they asked then is which hashtags behave as strong identifiers (if any), and if they could be mapped to concept identifiers in the Semantic Web? Read more of this post

Progress Report 3

This the third report of my Master Thesis project in Computer Sciences at Graz University of Technology (TUGraz) and the Katholieke Universiteit Leuven (KULeuven). It combines the first two reports and adds a description of the research carried out in december and january. It gives a background overview to situate this report and it discusses the problem statement. An in depth view on the software architecture is given. Some noteworthy implementation details are revealed. Finally an updated project plan is motivated.

Master Thesis Progress Report 3