Tag Archives: Linked Data

Tutorial on SPARQL Package for R

Tools are major enablers of Linked Science. One crucial aspect is how to access and analyze data, and especially how to get only that part of data which is of interest for a given research question.  Linked Data solves the access part, and SPARQL allows to query only a subset of the data. For statistical computing there are tools like R. As a solution to bridge the two communities, those of statistical computing and  semantic web, there is now a SPARQL Package for R, which enables to get data from Linked Data services to R for analysis. At LinkedScience.org you may now find a tutorial on SPARQL Package for R. By following it you can learn:

  1. how to access and query Linked Spatiotemporal Data of the  deforestation statistics related to the Brazilian Amazon Rainforest, and
  2. how to analyze it within R (which is a free software environment for statistical computing).

First course worldwide on Linked Science at the University of Muenster, Germany

First course worldwide on Linked Science will be held at the Institute for Geoinformatics at the University of Muenster, Germany during the winter semester 2011/2012. This Linked Science course is arranged as a seminar, and the title is “Spatiotemporal and Semantic Modeling for Linked Science” and it is lectured by Dr. Tomi Kauppinen.

The seminar teaches both basics and shows recent advancements of Linked Spatiotemporal Data and Linked Science. The seminar is combined of lectures and demo-sessions showing through examples how spatiotemporal information can be modeled, semantically described and published as Linked Data. The major emphasis is on scientific datasets.

In the course we will also discuss spatiotemporal and semantic reasoning techniques to enrich the data. Students will also  learn how the data can be connected with the help of the SPARQL package for R for statistical analysis, and how and which visualization techniques and tools are available for interacting with the data. Each student will choose a topic for the seminar to create and use Linked Scientific Data of some discipline (e.g.  life sciences, natural and living environment studies, chemistry, biology, crisis management, history and cultural heritage) within the University of Muenster.

The major emphasis is in disciplines where there are interesting spatiotemporal aspects. The results of these student works will be shown and discussed in the demo sessions. The course serves both newcomers in Linked Data techniques and advanced students already knowing the basics and wanting to learn the Linked Science approach. Students will learn theory, techniques, presentation and organizational skills in the seminar.

Spatial.LinkedScience.org opened!

During the last few days and weeks we (Krzysztof Janowicz, Carsten Keßler, Alexander Savelyev and Tomi Kauppinen) created a Linked Data set about the people, papers and proceedings  of the COSIT (Conference on Spatial Information Theory) series.

The result is now opened and can be interacted with at Spatial.LinkedScience.org! We look forward to maintain the portal as a community effort in order to serve back the community, i.e. the researchers of the Spatial Information and Geographic Information Science. 

Would other communities be interested in joining LinkedScience.org? Just contact us, and let us plan it.

Linked Open Science @ Executable Paper Grand Challenge

The following publication will be published in the The Executable Paper Grand Challenge at ICCS 2011 to explain ideas about Linked Open Science:

Tomi Kauppinen and Giovana Mira de Espindola. Linked Open Science—-Communicating, Sharing and Evaluating Data, Methods and Results for Executable Papers. The Executable Paper Grand Challenge, in proceedings of The International Conference on Computational Science (ICCS 2011). Elsevier Procedia Computer Science series, Singapore, June, 2011.

In short, the paper proposes an approach to solve challenges of an executable paper. It is a combination of four “silver bullets”: 1) publication of scientific data, metadata, results, and provenance information using Linked Data principles, 2) an open source environment for executing, validating and exploring research, 3) Cloud Computing for efficient and distributed computing, and 4) Creative Commons for the legal infrastructure.