Interview with Rudi Studer on “Semantic Technologies”

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Semantics and Web 2.0 - Technologies to Support Business Process Management

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User Interfaces for Personal Knowledge Management with Semantic Technologies

This thesis describes iMapping and QuiKey, two novel user interface concepts for dealing with structured information. iMapping is a visual knowledge mapping technique based on zooming, which combines the advantages of several existing approaches and scales up to very large maps. QuiKey is a text-based tool to interact with graph-structured knowledge bases with very high interaction efficiency. Both tools have been implemented and positively evaluated in user studies

Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

Using Unified Personal Information in Workspaces

Knowledge workers (KWers) deal with personal information and use tools like, e.g., desktop workspaces to support their work. But KWer support is hindered by personal information fragmentation, i.e., applications keep a set of personal information while not interconnecting it. This thesis addresses this in the domains personal task management and meeting management by using a common unified personal information model as offered by the semantic desktop personal information management (PIM) system

Speech-based metadata generation for web map search

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesMetadata is indispensable for data discoverability and interoperability. Most datasets utilize automatic techniques to create metadata; nevertheless, metadata creation still requires manual interventions and editions, yet manually metadata creation is a tedious task. The study proposes a prototype that introduces speech recognition in the metadata creation process. Users can generate content by speaking. Afterward, the prototype transforms it into metadata with JSON-LD format, a popular metadata format and utilized by mainstream search engines. A user study was conducted to understand the impact of speech-based interaction on user performance and user satisfaction. The result showed no signi cant performance di erence between speech-based and typebased by the e ciency, slip rate, and di culty rating evaluation. In the user experience evaluation, participants consider the type-based metadata creation is pragmatic, and speech-based metadata creation is hedonic. It suggests that the mix-mode can complement mutually with the advantages of each and optimize the user experience