We present iMapping, a diagrammatic zooming and nesting based approach for visually structuring information objects on the desktop with a special focus on personal knowledge management. It was designed based on a set of requirements gathered from the analysis of existing knowledge mapping techniques from a cognitive science point of view. We also briefly introduce a prototypical implementation.

Authors: Ola Leifler and Henrik Eriksson

Abstract: There is a significant gap between the services provided by dedicated information
systems and general desktop systems for document communication and preparation.
This situation is a serious knowledge-management problem, which often results
in information loss, poor communication, and confusion among users. Semantic desktops
promise to bring knowledge-based services to common desktop applications and,
ultimately, to support knowledge management by adding advanced functionality to
familiar computing environments. By custom tailoring these systems to different application
domains, it is possible to provide dedicated services that assist users in combining
document handling and communication with structured workflow processes and
the services provided by dedicated systems. This paper presents a model for developing
custom-tailored document processing for semantic-desktop systems. Our approach
has been applied to the domain of military command and control, which as based on
highly-structured document-driven processes.

Key Words: semantic desktop, document-driven processes, semantic documents,
planning

Category: H.5.3, H.5.4, I.7.1, I.7.5, M.1, M.4

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Authors: Peter Scheir, Chiara Ghidini and Stefanie N. Lindstaedt

Abstract: While it is agreed that semantic enrichment of resources would lead to
better search results, at present the low coverage of resources on the web with semantic
information presents a major hurdle in realizing the vision of search on the Semantic
Web. To address this problem we investigate how to improve retrieval performance
in a setting where resources are sparsely annotated with semantic information. We
suggest employing techniques from associative information retrieval to find relevant
material, which was not originally annotated with the concepts used in a query. We
present an associative retrieval system for the Semantic Desktop and show how the use
of associative retrieval increased retrieval performance.

Key Words: semantic desktop, associative information retrieval

Category: H.3.3, I.2.4, I.2.6, I.2.11

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Authors: Danish Nadeem and Leo Sauermann

Abstract: This paper examines issues on Philosophy of Artificial Intelligence (AI),
Cognitive Science and Mental Models. The paper provides a philosophical grounding
for the researchers in Personal Information Management (PIM). An overview is given on
various philosophical aspects of computer-based activities. Discussions on the theories
relevant to understand the goals for the Semantic Desktop community are elicited.
Philosophical theories are not immediately transparent to the programmers, but the
ideas discussed here are intended to emphasize a theoretical foundation, with respect to
Semantic Desktop long term goals. The goal of this paper is to examine the theories of
Philosophy and to provide a conceptual idea to design user-intuitive Semantic Desktops.
The paper tries to induce scientific curiosity among the Semantic Desktop researchers
as well as to develop the future Semantic Desktops to realize Weak AI.

Key Words: mental model, knowledge management, semantic desktop

Category: H, H.1.0, H.1.2, H.5.0

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Authors: Tudor Groza, Siegfried Handschuh, Knud Moeller, Gunnar Grimnes, Leo Sauermann
Enrico Minack, Mehdi Jazayeri, Cedric Mesnage, Gerald Reif, Rosa Gudjonsdottir

Abstract: This paper introduces the NEPOMUK project which aims to create a
standard and reference implementation for the Social Semantic Desktop. We outline
the requirements and functionalities that were identified for a useful Semantic Desktop
system and present an architecture that fulfills these requirements which was acquired
by incremental refinement of the architecture of existing Semantic Desktop prototypes.
The NEPOMUK project is primarily motivated by three real-life industrial use-cases,
we briefly outline these and the processes used to extract required functionalities from
the people working in these areas today, and we present a selection of typical tasks
where the Semantic Desktop could be of benefit.

Key Words: Semantic Desktop, Personal Information Management, Semantic Middleware

Category: H.3.7, H.5.4

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Authors: Olaf Grebner and Hannes Ebner

Abstract: This paper presents an application that enables loose and ad-hoc task collaboration
for knowledge work and explicitly integrates task metadata into the collaboration process. With
the increasing availability of semantic desktop technology, knowledge workers (KWers) can
organize their personal information in a formalized way, including tasks. In an organization,
KWers need to collaboratively access task-related information and to collaboratively work on
it. In such a scenario, today’s available collaboration support applications, e.g. enterprise
collaboration systems like wikis, either sacrifice end-user experience or semantic richness when
dealing with structured knowledge. The presented collaborative task management (TM) application
circumvents this trade-off by showing how the Kasimir TM client and the Collaborilla
collaboration server interact closely. The TM client supports the KWer’s personal TM and incorporates
collaborative tasks. It invokes the collaboration server which centrally manages the
collaborative tasks. It implements elaborated methods for metadata sharing and collaborative
editing of this shared metadata. We present the detailed proposal for an underlying architecture
of the application, review related work and conclude this paper by pointing out future work.

Keywords: Task Management, Ad-hoc Collaboration, Metadata Sharing, Collaborative
Metadata Editing, Semantic Desktop

Categories: H.1, H.4, M.3, M.4, M.5, M.6

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