Visual exploration of data enables users and analysts observe interesting patterns that can trigger new research for further investigation. With the increasing availability of Linked Data, facilitating support for making sense of the data via visual exploration tools for hypothesis generation is critical. Time and space play important roles in this because of their ability to illustrate dynamicity, from a spatial context. Yet, Linked Data visualization approaches typically have not made efficient use of time and space together, apart from typical rather static multivisualization approaches and mashups. We developed ELBAR explorer that visualizes a vast amount of scientific observational data about the Brazilian Amazon Rainforest. The core contribution is a novel mechanism for animating between the different observed values, thus illustrating the observed changes themselves.
ELBAR-explorer will be demoed at ISWC2014 in October, 2014. The following paper will give more details:
We will organize a Tutorial on Information Visualization for Innovating Research Methods at Spatial Cognition 2014 (SC2014) conference in Bremen on September 15th, 2014. The teachers of the tutorial are Tomi Kauppinen (Cognitive Systems Group, University of Bremen) and Willem van Hage (SynerScope B.V.).
In the tutorial we will introduce visual approaches for investigating spatial data in the context of other dimensions (such as social or temporal). The goal is to show via examples how information visualization, exploration and interaction support innovating new research methods. The tutorial materials will be made available online at LinkedScience.org/tutorials.
The main tutorial exercises will be done within the morning of the tutorial day. For the afternoon there is an optional session for studying how to apply visual analytics techniques to data brought by participants.
Thus while the focus of hands-on exercises of the morning session is in existing case examples the optional afternoon session is more about brainstorming and exchanging ideas about suitable methods for the data from the participants.
Register to SC2014 and tutorial today here.
We will organize the 4th Workshop on Linked Science 2014 (LISC2014) with the focus on theme Making Sense Out of Data. LISC2014 will collocate with ISWC2014 in Riva del Garda, Trentino, Italy on October 19 or 20, 2014.
We encourage submissions on both
- new results through making use of semantic reasoning or
- making innovative combination of existing technologies (such as visualization, data mining, machine learning, and natural language processing) with Semantic Web technologies to enable better understanding of data.
LISC2014 is organized by
– Jun Zhao, Lancaster University
– Marieke van Erp, VU University Amsterdam
– Carsten Keßler, Hunter College, City University of New York
– Tomi Kauppinen, University of Bremen
– Jacco van Ossenbruggen, CWI and
– Willem Robert van Hage, SynerScope B.V.
Please check the LISC2014 pages for more information and Call for Papers.
Our VisLOD tutorial is arranged on May 26, 2014 in Anissaras (Crete, Greece) at ESWC2014 conference. The idea is to bring together researchers and practitioners interested in visual and interactive techniques for exploring Linked Open Data and Social Media for e-Governance. Our hands-on tutorial will cover technical aspects from two perspectives:
- Social Media analysis and
- Visualisation of Social Media and Linked Data.
The teachers of the VisLOD tutorial are Dr. Vitaveska Lanfranchi and Mr. Suvodeep Mazumdar from the University of Sheffield (UK) and Dr. Tomi Kauppinen from the Aalto University (Finland).
Tutorial on Analyzing and Visualizing Linked Data with R 2013 (LODR2013)
The openly available R package SPARQL
allows to directly connect to Linked Data and use the SPARQL querying language for selecting interesting part of data for analysis. Thus it enables to meet massive and rich data sets with the analytical power of the R language and environment.
This approach and tools contribute to Linked Science and Open Science movements to support the transparency of science and to conduct transdisciplinary research.
In this tutorial we will introduce the idea and concepts about Linked Science, and show via illustrative examples about how to practically query and analyze Linked Data from within R environment for visual and statistical analysis. Tutorial materials will be published online.
Teachers of the tutorial are