6 research outputs found
Demonstration of a customizable representation model for graph-based visualizations of ontologies – GIzMO
Visualizations can facilitate the development, exploration, communication, and sense-making of ontologies. Suitable visualizations, however, are highly dependent on individual use cases and targeted user groups. In this demo, we present a methodology that enables customizable definitions for ontology visualizations. We showcase its applicability by introducing GizMO, a representation model for graph-based visualizations in the form of node-link diagrams. Additionally, we present two applications that operate on the GizMO representation model and enable individual customizations for ontology visualizations
Visual exploration of semantic-web-based knowledge structures
Humans have a curious nature and seek a better understanding of the world. Data, in-
formation, and knowledge became assets of our modern society through the information
technology revolution in the form of the internet. However, with the growing size of
accumulated data, new challenges emerge, such as searching and navigating in these large
collections of data, information, and knowledge. The current developments in academic
and industrial contexts target the corresponding challenges using Semantic Web techno-
logies. The Semantic Web is an extension of the Web and provides machine-readable
representations of knowledge for various domains. These machine-readable representations
allow intelligent machine agents to understand the meaning of the data and information;
and enable additional inference of new knowledge.
Generally, the Semantic Web is designed for information exchange and its processing
and does not focus on presenting such semantically enriched data to humans. Visualizations
support exploration, navigation, and understanding of data by exploiting humans’ ability
to comprehend complex data through visual representations. In the context of Semantic-
Web-Based knowledge structures, various visualization methods and tools are available,
and new ones are being developed every year. However, suitable visualizations are highly
dependent on individual use cases and targeted user groups.
In this thesis, we investigate visual exploration techniques for Semantic-Web-Based
knowledge structures by addressing the following challenges: i) how to engage various user
groups in modeling such semantic representations; ii) how to facilitate understanding using
customizable visual representations; and iii) how to ease the creation of visualizations
for various data sources and different use cases. The achieved results indicate that visual
modeling techniques facilitate the engagement of various user groups in ontology modeling.
Customizable visualizations enable users to adjust visualizations to the current needs and
provide different views on the data. Additionally, customizable visualization pipelines
enable rapid visualization generation for various use cases, data sources, and user group
Demonstration of a customizable knowledge graph visualization framework
In the context of the Semantic Web, various visualization methods and tools exist. However, suitable visualizations are highly de-pendent on individual use cases and targeted user groups. Therefore, existing solutions require modifications and adjustments to meet the de-mands of other use cases and user groups. In this demo, we present an approach for a unified framework addressing customizable visual rep-resentations of knowledge graphs. Our approach refines the commonly used steps in the visualization generation process (i.e., data access, map-ping to visual primitives, and rendering) for Semantic Web contexts. Separation of concerns for individual steps and a modular and customiz-able architecture build the foundation for a pipeline-based visualization framework. The framework enables the creation and selection of the right components for the right tasks, realizing a variety of use cases and visual representations in Semantic Web contexts
Collaborative and Cross-Stakeholder Ontology Engineering
One of the major challenges in developing ontologies is to efficiently merge domain knowledge and expert knowledge to enable efficient and effective work on formal modelling of the domain in focus. This paper outlines the current state of developments in the Semantically Connected Semiconductor Supply Chains (SC3) project and its application in the BMBF-funded Cognitive Economy Intelligence Platform for Economic Ecosystem Resilience (CoyPu) project. We are using the SC3 Ontology Platform in CoyPu to promote effective information sharing among the various stakeholders in the development of the ontology. Thus, the application of SC3 Ontology Platform is used to ensure that the knowledge of non-knowledge workers (domain experts) and knowledge workers come together efficiently. This
paper first introduces the CoyPu project and the current ontology development; then the SC3 Ontology Platform and its main components are presented. The paper concludes with the analysis of a first usability evaluation
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"Colearning" - Collaborative Open Learning through OER and Social Media
This chapter introduces the concept of coLearning as well as discussing how open learning networks can produce, share and reuse OER collaboratively through social media.
COLEARNING OBJECTIVES
The aim of this investigation is to identify new forms of collaboration, as well as strategies that can be used to make the production and adaptation processes of OER more explicit for anyone in a social network to contribute.
REUSABILITY
This open content is an adapted version of a conference paper for OCW conference 2012, which was created by the same authors. This chapter can be reused by:
Educators who would like to create reusable OER (images, videos, maps, units)
Learners who are interested in tools for reusing and adapting OER
Content developers who are looking for different media to enrich OER
Social network users who would like to produce and share open media conten