Publication statistics
Pub. period:1994-2011
Pub. count:8
Number of co-authors:18
Co-authors
Number of publications with 3 favourite co-authors:
Mark A. Musen:4Angel R. Puerta:3John H. Gennari:3 Productive colleagues
Henrik Eriksson's 3 most productive colleagues in number of publications:
William Wong:21Angel R. Puerta:18Mark A. Musen:16
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Henrik Eriksson
Publications by Henrik Eriksson (bibliography)
Field, Joris, Rankin, Amy, Pal, Jelke van der, Eriksson, Henrik and Wong, William (2011): Variable uncertainty: scenario design for training adaptive and flexible skills. In: Proceedings of the 2011 Annual European Conference on Cognitive Ergonomics 2011. pp. 27-34.
“Motivation -- Today's training systems for crisis management (CM) largely focus on technical and procedural skills. However the dynamic and unpredictable nature of a crisis also requires skills that are flexible, adaptive and creative. Training systems enforce limitations on the freedom of interaction the trainee has compared with the real world, thereby limiting their effectiveness for real world emergencies. Furthermore, the training scenarios are often played out in a linear and rigid manner, limiting the ability to train skills such as adapting to the on-going situation and being flexible in an uncertain and variable environment. Research approach -- The Variable Uncertainty Framework (VUF) has been developed as part of a European project (CRISIS) developing an interactive simulated Virtual Reality (VR) environment for training CM to address some of the challenges faced in training scenario design today. The principles from software systems design have been compared to those of instructional design to develop a framework that can be applied in this project. Findings/Design -- The VUF brings together three important dimensions of real-world emergencies that can be manipulated and controlled in virtual training environments: (1) situational complexity, (2) the number of events occurring simultaneously, and (3) the randomness of these events. By controlling these three dimensions in the training environment, an instructor can design scenarios that are either basic drill oriented, or advanced scenarios where events are complex and combined in un-predictable ways. Take away message -- The VUF is illustrated as a method of achieving the variability and complexity in the training scenario design. It offers an accessible method for instructors to design and adapt training scenarios to optimise the training effectiveness.”
© All rights reserved Field et al. and/or their publisher
Rankin, Amy, Field, Joris, Kovordanyi, Rita, Morin, Magnus, Jenvald, Johan and Eriksson, Henrik (2011): Training systems design: bridging the gap between users and developers using storyboards. In: Proceedings of the 2011 Annual European Conference on Cognitive Ergonomics 2011. pp. 205-212.
“Motivation -- Designing distributed training systems for crisis management (CM) requires an approach with the ability to address a great variety of needs and goals. Crisis responses involve multiple agents, each with different backgrounds, tasks, priorities, goals, responsibilities, organizations, equipment, and approaches. Identifying the different user training needs and translating these into user and functional requirement therefore poses great challenges. Research approach -- In this paper we present experiences of how to enable the collaboration between multiple stakeholders and partners when creating and adapting ideas throughout the design phase. The techniques have been used in a European project aimed at developing an interactive Virtual Reality (VR) environment for training crisis management. Findings/Design -- The focus of the paper is on the initial storyboard iterations and lo-fi prototypes, as this is a crucial stage for expressing ideas in a perceivable way without having to spend too much time and effort on creating detailed prototypes. Take away message -- Experiences using low-cost commercial software for creating storyboards are presented, as these provided the means to create, share, present, adapt and circulate ideas, facilitating the fusing of ideas, shared understanding and distributed working.”
© All rights reserved Rankin et al. and/or their publisher
Eriksson, Henrik (2007): The semantic-document approach to combining documents and ontologies. In International Journal of Human-Computer Studies, 65 (7) pp. 624-639.
“An ontology is a powerful way of representing knowledge for multiple purposes. There are several ontology languages for describing concepts, properties, objects, and relationships. However, ontologies in information systems are not primarily written for human reading and communication among humans. For many business, government, and scientific purposes, written documents are the primary description and communication media for human knowledge communication. Unfortunately, there is a significant gap between knowledge expressed as textual documents and knowledge represented as ontologies. Semantic documents aim at combining documents and ontologies, and allowing users to access the knowledge in multiple ways. By adding annotations to electronic-document formats and including ontologies in electronic documents, it is possible to reconcile documents and ontologies, and to provide new services, such as ontology-based searches of large document databases. To accomplish this goal, semantic documents require tools that support both complex ontologies and advanced document formats. The Protégé ontology editor, together with a custom-tailored documentation-handling extension, enables developers to create semantic documents by linking preexisting documents to ontologies.”
© All rights reserved Eriksson and/or Academic Press
Irestig, Magnus, Eriksson, Henrik and Timpka, Toomas (2004): The impact of participation in information system design: a comparison of contextual placements. In: Clement, Andrew and Besselaar, Peter Van den (eds.) PDC 2004 - Proceedings of the Eighth Conference on Participatory Design July 27-31, 2004, Toronto, Ontario, Canada. pp. 102-111.
Gennari, John H., Musen, Mark A., Fergerson, Ray W., Grosso, William E., Crubezy, Monica, Eriksson, Henrik, Noy, Natalya F. and Tu, Samson W. (2003): The evolution of Protege: an environment for knowledge-based systems development. In International Journal of Human-Computer Studies, 58 (1) pp. 89-123.
“The Protege project has come a long way since Mark Musen first built the
Protege meta-tool for knowledge-based systems in 1987. The original tool was a
small application, aimed at building knowledge-acquisition tools for a few
specialized programs in medical planning. From this initial tool, the Protege
system has evolved into a durable, extensible platform for knowledge-based
systems development and research. The current version, Protege-2000, can be run
on a variety of platforms, supports customized user-interface extensions,
incorporates the Open Knowledge-Base Connectivity (OKBC) knowledge model,
interacts with standard storage formats such as relational databases, XML, and
RDF, and has been used by hundreds of individuals and research groups. In this
paper, we follow the evolution of the Protege project through three distinct
re-implementations. We describe our overall methodology, our design decisions,
and the lessons we have learned over the duration of the project. We believe
that our success is one of infrastructure: Protege is a flexible,
well-supported, and robust development environment. Using Protege, developers
and domain experts can easily build effective knowledge-based systems, and
researchers can explore ideas in a variety of knowledge-based domains.”
© All rights reserved Gennari et al. and/or Academic Press
Rothenfluh, Thomas E., Gennari, John H., Eriksson, Henrik, Puerta, Angel R., Tu, Samson W. and Musen, Mark A. (1996): Reusable Ontologies, Knowledge-Acquisition Tools, and Performance Systems: PROTEGE-II Solutions to Sisyphus-2. In International Journal of Human-Computer Studies, 44 (3) pp. 303-332.
“This paper describes how we applied the PROTEGE-II architecture to build a knowledge-based system that configures elevators. The elevator-configuration task was solved originally with a system that employed the propose-and-revise problem-solving method (VT). A variant of this task, here named the Sisyphus-2 problem, is used by the knowledge-acquisition community for comparative studies. PROTEGE-II is a knowledge-engineering environment that focuses on the use of reusable ontologies and problem-solving methods to generate task-specific knowledge-acquisition tools and executable problem solvers. The main goal of this paper is to describe in detail how we used PROTEGE-II to model the elevator-configuration task. This description provides a starting point for comparison with other frameworks that use abstract problem-solving methods. Beginning with the textual description of the elevator-configuration task, we analysed the domain knowledge with respect to PROTEGE-II's main goal: to build domain-specific knowledge-acquisition tools. We used PROTEGE-II's suite of tools to construct a knowledge-based system, called ELVIS, that includes a reusable domain ontology, a knowledge-acquisition tool, and a propose-and-revise problem-solving method that is optimized to solve the elevator-configuration task. We entered domain-specific knowledge about elevator configuration into the knowledge base with the help of a task-specific knowledge-acquisition tool that PROTEGE-II generated from the ontologies. After we constructed mapping relations to connect the knowledge base with the method's code, the final executable problem solver solved the test case provided with the Sisyphus-2 material. We have found that the development of ELVIS has afforded a valuable test case for evaluating PROTEGE-II's suite of system-building tools. Only projects based on reasonably large problems, such as the Sisyphus-2 task, will allow us to improve the design of PROTEGE-II and its ability to produce reusable components.”
© All rights reserved Rothenfluh et al. and/or Academic Press
Eriksson, Henrik, Puerta, Angel R. and Musen, Mark A. (1994): Generation of Knowledge-Acquisition Tools from Domain Ontologies. In International Journal of Human-Computer Studies, 41 (3) pp. 425-453.
“Metalevel tools can support the software development process by automating the design of task- and application-specific tools. DASH is a metalevel tool that allows developers to generate domain-specific knowledge-acquisition tools from domain ontologies. Domain specialists use the knowledge-acquisition tools generated by DASH to instantiate the concepts and relationships defined in the domain ontologies. The output of the knowledge-acquisition tools is a collection of instances that constitute the knowledge base for a knowledge-based system. To automate the generation of appropriate tools, the DASH architecture uses a dialog-design module to produce a dialog structure that defines the target tool at the editor and window level. Given the dialog structure, a layout-design module completes the window layouts. DASH allows the developer to custom tailor the layout of the knowledge-acquisition tool for its users, and to store such modifications persistently so that they can be reapplied when the target tool is regenerated. The DASH implementation is based on a mapping problem-solving method that defines the tool-design steps. The DASH Development Environment (DDE) is an application-specific environment that supports the configuration of the mapping method and the maintenance of DASH. We have used DASH to generate several knowledge-acquisition tools for a broad range of application tasks.”
© All rights reserved Eriksson et al. and/or Academic Press
Puerta, Angel R., Eriksson, Henrik, Gennari, John H. and Musen, Mark A. (1994): Beyond Data Models for Automated User Interface Generation. In: Cockton, Gilbert, Draper, Steven and Weir, George R. S. (eds.) Proceedings of the Ninth Conference of the British Computer Society Human Computer Interaction Specialist Group - People and Computers IX August 23-26, 1994, Glasgow, Scotland, UK. pp. 353-366.
“Researchers in the area of automated design of user interfaces have shown that the layout of an interface can, in many cases, be generated from the application's data model using an intelligent program that applies design rules. The specification of interface behavior, however, has not been automated in the same manner, and is mostly a programmatic task. Mecano is a model-based user-interface development environment that extends the notion of automating interface design from data models. Mecano uses a domain model -- a high-level knowledge representation that augments significantly the expressiveness of a data model -- to generate automatically both the static layout and the dynamic behavior of an interface. Mecano has been applied successfully to completely generate the layout and the dynamic behavior of relatively large and complex, domain-specific, form- and graph-based interfaces for medical applications and several other domains.”
© All rights reserved Puerta et al. and/or Cambridge University Press
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