Timo Stegemann

RelFinder: Revealing Relationships in RDF Knowledge Bases

The Semantic Web has recently seen a rise of large knowledge bases (such as DBpedia) that are freely accessible via SPARQL endpoints. The structured representation of the contained information opens up new possibilities in the way it can be accessed and queried. In this paper, we present an approach that extracts a graph covering relationships between two objects of interest. We show an interactive visualization of this graph that supports the systematic analysis of the found relationships by providing highlighting, previewing, and filtering features.

Interactive relationship discovery via the semantic web

This paper presents an approach for the interactive discovery of relationships between selected elements via the Semantic Web. It emphasizes the human aspect of relationship discovery by offering sophisticated interaction support. Selected elements are first semi-automatically mapped to unique objects of Semantic Web datasets. These datasets are then crawled for relationships which are presented in detail and overview. Interactive features and visual clues allow for a sophisticated exploration of the found relationships. The general process is described and the RelFinder tool as a concrete implementation and proof-of-concept is presented and evaluated in a user study. The application potentials are illustrated by a scenario that uses the RelFinder and DBpedia to assist a business analyst in decision-making. Main contributions compared to previous and related work are data aggregations on several dimensions, a graph visualization that displays and connects relationships also between more than two given objects, and an advanced implementation that is highly configurable and applicable to arbitrary RDF datasets.

The RelFinder user interface: interactive exploration of relationships between objects of interest

Being aware of the relationships that exist between objects of interest is crucial in many situations. The RelFinder user interface helps to get an overview: Even large amounts of relationships can be visualized, filtered, and analyzed by the user. Common concepts of knowledge representation are exploited in order to support interactive exploration both on the level of global filters and single relationships. The RelFinder is easy-to-use and works on every RDF knowledge base that provides standardized SPARQL access

Investigating Learnability, User Performance, and Preferences of the Path Query Language SemwidgQL Compared to SPARQL

In this paper, we present an empirical comparison of user performance and perceived usability for Sparql versus SemwidgQL, a path-oriented Rdf query language. We developed SemwidgQL to facilitate the formulation of Rdf queries and to enable non-specialist developers and web authors to integrate Linked Data and other semantic data sources into standard web applications. We performed a user study in which participants wrote a set of queries in both languages. We measured both objective performance as well as subjective responses to a set of questionnaire items. Results indicate that SemwidgQL is easier to learn, more efficient, and preferred by learners. To assess the applicability of SemwidgQL in real applications, we analyzed its expressiveness based on a large corpus of observed Sparql queries, showing that the language covers more than 90% of the typical queries performed on Linked Data.

Entdecken und Explorieren von Zusammenhängen im Semantic Web (Discovering and Exploring Relationships in the Semantic Web).

Zusammenfassung Auch wenn das heutige Web eine gewaltige Menge an Informationen bereithält, unterstützt es nur unzureichend die Entdeckung und Exploration von Zusammenhängen. Hier verspricht das Semantic Web durch eine Graphbasierte Informationsrepräsentation prinzipiell bessere Unterstützung. Allerdings müssen die im Semantic Web beschriebenen Zusammenhänge erst extrahiert und in eine für den Nutzer verständ liche Darstellung gebracht werden. Aus diesem Grund wurde der RelFinder entwickelt, der Zusammenhänge in Datenbeständen des Semantic Web auffindet, nachvollziehbar visualisiert und für den Nutzer erfahrbar macht. Um die interaktive Exploration zu unterstützen, wurden neuartige Visualisierungs- und Interak tionsformen umgesetzt, die erst durch die Repräsentationen des Semantic Web ermöglicht werden. Dieser Artikel zeigt anhand einer Nutzerstudie, welche Potenziale sich damit gegenüber den textbasierten Darstellungsformen des heutigen Web ergeben. Es wird deutlich, dass das Semantic Web in Kombination mit intuitiven Darstellungs- und Bedienkonzepten potenziell sehr geeignet ist, um einen schnellen Überblick über Zusammen hänge zwischen Informationsobjekten zu erhalten.