With this tutorial you can build an interactive web application with R that fetches up-to-date lecture data from the data.aalto.fi SPARQL endpoint, renders the result both as a table and a calendar-like chart, and offers a way to download data as iCal calendar events.
Linked Science is an approach to interconnect scientific assets in order to enable transparent, reproducible and transdisciplinary research. Tutorial on Linked Science 2012 (TOLSCI2012) will be a half day tutorial comprising of different aspects of Linked Science: semantic description of scientific data (e.g. observations and measurements), existing vocabularies, bridging of statistical analysis and Linked Data, and license and copyright issues about data.
Through exercises and the introductory talk the aim of TOLSCI2012 is to stimulate transdisciplinary discussions among researchers and publishers from various backgrounds on semantic integration of scientific information.
The main part of the tutorial will concentrate in a hands-on session in order to learn how to describe, access and analyze scientific data about scientific observations, and especially how to get only that part of data which is of interest for a given research question.
We will teach
how Linked Data solves the access part, and
how SPARQL allows to query only a subset of the data.
In particular, the participants will learn in a hands-on session
how Linked Data can be connected with the help of the SPARQL package for statistical analysis in R, and
how and which visualization techniques and tools are available for interacting with the data.
Tomi Kauppinen is a postdoctoral researcher in the Muenster Semantic Interoperability Lab (MUSIL) at the Institute for Geoinformatics at the University of Muenster, Germany. He holds a PhD from the Aalto University, Finland with a thesis on reasoning about change and time. He chaired the First International Workshop on Linked Science 2011 at the International Semantic Web Conference (ISWC2011), the track on Interoperability and Semantics of the Geoinformatik 2011 conference, and led the breakout session for Vocabularies for Science at Science Online London 2011 organized by Nature. His research focuses on spatiotemporal and semantic modeling of processes such as deforestation, extreme weather events, changes in administrational borders, digital cultural heritage, and linked science. His current projects include opening and linking of scientific and educational data in LinkedScience.org-project and in the Linked Open Data University of Muenster (LODUM). He coordinates activities as a post-doc in the International Research Training Group on Semantic Integration of Geospatial Information.
Willem Robert van Hage is a researcher in the field of information integration on the web. His main research topics in the past years are geospatio-temporal semantics, ontology alignment, and ontology learning. He is a co-organizer of the Detection, Representation, and Exploitation of Events in the Semantic Web workshop (DeRiVE 2011) and since 2006 he has been a co-organizer of the Ontology Alignment Evaluation Initiative (OAEI), a collaborative benchmarking effort for the evaluation of on- tology alignment techniques. He has led the development of the Simple Event Model (SEM), an ontology for the description of events. In the past years he has worked on the combination of Semantic Web reasoning (RDF(S), OWL) and geospatio-temporal reasoning, developing a spatiotemporal indexing package for the popular SWI-Prolog programming language, which has led to a best paper award at the EKAW 2010 conference, and Semantic Web packages for SPARQL querying and RDF storage for the R statistical programming language. He is the coordinator of the interfaculty Web Science minor at the VU University Amsterdam.
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:
how to access and query Linked Spatiotemporal Data of the deforestation statistics related to the Brazilian Amazon Rainforest, and
how to analyze it within R (which is a free software environment for statistical computing).
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.