Loki : the semantic wiki for collaborative knowledge engineering

We present Loki, a semantic wiki designed to support the collaborative knowledge engineering process with the use of software engineering methods. Designed as a set of DokuWiki plug-ins, it provides a variety of knowledge representation methods, including semantic annotations, Prolog clauses, and business processes and rules oriented to specific tasks. Knowledge stored in Loki can be retrieved via SPARQL queries, in-line Semantic MediaWiki-like queries, or Prolog goals. Loki includes a number of useful features for a group of experts and knowledge engineers developing the wiki, such as knowledge visualization, ontology storage, or code hint and completion mechanism. Reasoning unit tests are also introduced to validate knowledge quality. The paper is complemented by the formulation of the collaborative knowledge engineering process and the description of experiments performed during Loki development to evaluate its functionality. Loki is available as free software at https://loki.re

Collaborative Decision Support and Documentation in Chemical Safety with KnowSEC

To protect the health of human and environment, the European Union implemented the REACH regulation for chemical substances. REACH is an acronym for Registration, Evaluation, Authorization, and Restriction of Chemicals. Under REACH, the authorities have the task of assessing chemical substances, especially those that might pose a risk to human health or environment. The work under REACH is scientifically, technically and procedurally a complex and knowledge-intensive task that is jointly performed by the European Chemicals Agency and member state authorities in Europe. The assessment of substances under REACH conducted in the German Environment Agency is supported by the knowledge-based system KnowSEC, which is used for the screening, documentation, and decision support when working on chemical substances. The software KnowSEC integrates advanced semantic technologies and strong problem solving methods. It allows for the collaborative work on substances in the context of the European REACH regulation. We discuss the applied methods and process models and we report on experiences with the implementation and use of the system

Improving Knowledge Acquisition in Collaborative Knowledge Construction Tool with Virtual Catalyst

Noctua is a web tool to assist in Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua has an innovation: a Virtual Catalyst designed to facilitate the task of eliciting and validating knowledge. The Virtual Catalyst queries participants, proposing new knowledge, seeking confirmation to the knowledge already elicited, and showing conflicting opinions. The Virtual Catalyst takes into account participants' profiles in order to automatically ask them questions related to each one's field of knowledge or interest. This paper presents Noctua and its Virtual Catalyst. The tool was submitted to experimentation and the analysis of the results showed that the primary goal of increasing the rate of knowledge construction was achieved (up to 144 % in the rate of knowledge creation), and also showed some unexpected beneficial outcomes

at the 14th Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2011)

Technical Report TR-2011/1, Department of Languages and Computation. University of Almeria November 2011. Joaquín Cañadas, Grzegorz J. Nalepa, Joachim Baumeister (Editors)The seventh workshop on Knowledge Engineering and Software Engineering (KESE7) was held at the Conference of the Spanish Association for Artificial Intelligence (CAEPIA-2011) in La Laguna (Tenerife), Spain, and brought together researchers and practitioners from both fields of software engineering and artificial intelligence. The intention was to give ample space for exchanging latest research results as well as knowledge about practical experience.University of Almería, Almería, Spain. AGH University of Science and Technology, Kraków, Poland. University of Würzburg, Würzburg, Germany

Semantic wiki engines: a state of the art

Abstract. This paper is a survey about semantic wikis and the use of semantic Web technologies by wiki engines. First, it presents the main notions related to semantic wikis. Then, twelve active semantic wiki projects are compared, according to various viewpoints such as knowledge representation philosophy, use of semantic Web standards and system usability. Finally, a formal concept analysis approach is carried out to provide a guideline for the choice of semantic wiki engine, given a set of needed features. In conclusion, the paper argues about semantic wiki issues such as the weaknesses of some semantic wiki engine interoperability

An ontology-based universal design knowledge support system

Cataloged from PDF version of article.An effective and efficient knowledge support system is crucial for universal design process, as it has become a major design issue in the last decade with the growth of the elderly population and disabled people. There are a limited number of CAD investigations on the nature of knowledge processing that supports the cognitive activities of universal design process. Therefore, this paper proposes an ontology-based computer-assisted universal design (CAUD) plug-in tool that supports designers in developing satisfactory universal design solutions in the conceptual design phase. The required knowledge processing and representation of the developed tool is motivated by the ontological language. It is based on the multiple divergence-convergence cognitive strategies and cognitive needs of designers in the analysis/synthesis/evaluation operations. The CAUD plug-in tool is the first attempt to interface the universal design knowledge ontologically and respond to the requirements of conceptual design phase. According to the user acceptance study, the tool is assessed as useful, understandable, efficient, supportive and satisfactory

Semantic wikis as flexible database interfaces for biomedical applications

Several challenges prevent extracting knowledge from biomedical resources, including data heterogeneity and the difficulty to obtain and collaborate on data and annotations by medical doctors. Therefore, flexibility in their representation and interconnection is required; it is also essential to be able to interact easily with such data. In recent years, semantic tools have been developed: semantic wikis are collections of wiki pages that can be annotated with properties and so combine flexibility and expressiveness, two desirable aspects when modeling databases, especially in the dynamic biomedical domain. However, semantics and collaborative analysis of biomedical data is still an unsolved challenge. The aim of this work is to create a tool for easing the design and the setup of semantic databases and to give the possibility to enrich them with biostatistical applications. As a side effect, this will also make them reproducible, fostering their application by other research groups. A command-line software has been developed for creating all structures required by Semantic MediaWiki. Besides, a way to expose statistical analyses as R Shiny applications in the interface is provided, along with a facility to export Prolog predicates for reasoning with external tools. The developed software allowed to create a set of biomedical databases for the Neuroscience Department of the University of Padova in a more automated way. They can be extended with additional qualitative and statistical analyses of data, including for instance regressions, geographical distribution of diseases, and clustering. The software is released as open source-code and published under the GPL-3 license at https://github.com/mfalda/tsv2swm

An Integrated Knowledge Engineering Environment for Constraint-based Recommender Systems

Abstract. Constraint-based recommenders support customers in identifying relevant items from complex item assortments. In this paper we present a constraint-based environment already deployed in real-world scenarios that supports knowledge acquisition for recommender applications in a MediaWiki-based context. This technology provides the opportunity do directly integrate informal Wiki content with complementary formalized recommendation knowledge which makes information retrieval for users (readers) easier and less timeconsuming. The user interface supports recommender development on the basis of intelligent debugging and redundancy detection. The results of a user study show the need of automated debugging and redundancy detection even for small-sized knowledge bases

VODRE: Visualisation of drools rules execution

Knowledge-based Systems and Expert Systems, in particular, are expensive to build and difficult to validate and debug because of their complexity and dynamism. Therefore, it is not easy for knowledge engineer and domain expert to identify the gaps and mistakes in knowledge base. Unit testing is unable to cover validation process at all stages, in many cases manual thorough review of decision process is needed. In this paper we spot main approaches to validation and verification issue and describe a component that helps to debug a knowledge base by visualising execution of rules that derive a particular result. This component is developed for Knowledge-based Systems built on Drools Platform1 and we demonstrate application of this component in a knowledge-based engineering system for structural optical design