Steffen Lohmann

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

MUTO: the modular unified tagging ontology

Tagging has become a popular indexing method within the last years and can be considered one of the cornerstones of the Social Web. Several ontologies have been developed that aim to formally describe tagging and folksonomies in order to improve their interoperability and processability. However, each of these ontologies covers different aspects of the domain; finding the right ontology for a certain purpose and aligning it correctly with other ontologies is difficult. This paper critically reviews available tagging ontologies and presents a unified vocabulary that combines the best of these ontologies in one consistent schema. A central goal was to ensure high concept reuse by simultaneously avoiding redundancies. A modular design was chosen to reduce complexity and prevent inconsistencies. It groups the different elements of tagging and separates advanced concepts from the core ontology. Key design decisions are justified and modeling alternatives are discussed, not only to explain the unified ontology but also to contribute to a better understanding of the conceptual space of tagging and folksonomies.

SemLens: visual analysis of semantic data with scatter plots and semantic lenses

Querying the Semantic Web and analyzing the query results are often complex tasks that can be greatly facilitated by visual interfaces. A major challenge in the design of these interfaces is to provide intuitive and efficient interaction support without limiting too much the analytical degrees of freedom. This paper introduces SemLens, a visual tool that combines scatter plots and semantic lenses to overcome this challenge and to allow for a simple yet powerful analysis of RDF data. The scatter plots provide a global overview on an object collection and support the visual discovery of correlations and patterns in the data. The semantic lenses add dimensions for local analysis of subsets of the objects. A demo accessing DBpedia data is used for illustration.

Exploiting the Semantic Web for Interactive Relationship Discovery in Technology Enhanced Learning

This paper presents the concept of Interactive Relationship Discovery (IRD) and illustrates its application potentials in technology enhanced learning. Datasets of the Semantic Web are exploited to support learners in understanding how things are related. The approach is based on a user-oriented process model that has been implemented in an easy-to-use tool. A particular emphasis is on the interactive and subjective aspects of relationship discovery. Evaluation results support the applicability and potential of the approach in learning contexts. Benefits and limitations compared to related work are summarized in a final discussion.

Ontology-Based Representation of Learner Profiles for Accessible OpenCourseWare Systems

The development of accessible web applications has gained significant attention over the past couple of years due to the widespread use of the Internet and the equality laws enforced by governments. Particularly in e-learning contexts, web accessibility plays an important role, as e-learning often requires to be inclusive, addressing all types of learners, including those with disabilities. However, there is still no comprehensive formal representation of learners with disabilities and their particular accessibility needs in e-learning contexts. We propose the use of ontologies to represent accessibility needs and preferences of learners in order to structure the knowledge and to access the information for recommendations and adaptations in e-learning contexts. In particular, we reused the concepts of the ACCESSIBLE ontology and extended them with concepts defined by the IMS Global Learning Consortium. We show how OpenCourseWare systems can be adapted based on this ontology to improve accessibility.

Fostering Accessibility of OpenCourseWare with Semantic Technologies – A Literature Review

Accessibility has become a fundamental requirement for web applications, especially when it comes to e-learning and educational websites for OpenCourseWare. There are various types of disabilities and numerous ways of addressing them. Using semantic technologies to structure and represent the available concepts and taxonomies enables sharing and reusing the knowledge in a variety of systems. This paper provides a literature review of standards and ontologies that were developed to address accessibility requirements. The findings and recommendations reveal missing and future needs for building accessible OpenCourseWare services.

Data-centric interactions on the web

The World Wide Web has become a global database in recent years, with an ever-growing amount of data that is published online every day. Interactions with this data raise a number of research questions and practical challenges that are not yet sufficiently investigated. These issues will be addressed by the International Workshop of Data-Centric Interactions on the Web. It will serve as a platform for researchers, developers, and designers to foster the exchange of experiences and to discuss novel research ideas and results regarding data-centric interactions on the web.

Open design spaces: socially crafting interactive experiences

Engaging end-users and user communities to take an active part in the co-creation, evolution, and appropriation of modern, interactive systems has become an increasingly important issue over the last years. Bringing together existing research and experiences as well as new challenges such as long-term, large-scale, or highly distributed stakeholders has led to the notion of Open Design Spaces (ODS) to frame and reflect current developments of distributed co-design. Several, formerly often separated strands of research covering different aspects of these challenges have emerged and led to a growing community of researchers and practitioners building on concepts such as Participatory Design, Meta-Design, and End-User Development. Building on two successful predecessors on the topic with more than 50 international researchers and practitioners, the workshop at DIS 2010 focuses particularly on social aspects and community co-creation in Open Design Spaces.