Towards a general theory of action and time
Artificial Intelligence
Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Toward a New Generation of Semantic Web Applications
IEEE Intelligent Systems
Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Experiments on pattern-based ontology design
Proceedings of the fifth international conference on Knowledge capture
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Experimenting with eXtreme design
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
The cognitive complexity of OWL justifications
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
On the diversity and availability of temporal information in linked open data
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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Most Knowledge Representation (KR) research follows a topdown approach: i) formalisms are designed on the basis of modelling needs and computational considerations, and ii) tools and applications based on these formalisms are realized and tested on application domains. As a result, there has traditionally been little attention in the KR research community to user issues, in particular to the usability of alternative modelling solutions. When statements about the intuitiveness of different solutions are found in the literature, these tend to reflect an author's epistemological standpoint, rather than any concrete user experience. In this paper we take a bottom-up, user-centric perspective and we report on an empirical study where subjects have been asked to represent temporal information and have been provided with alternative design patterns to do so. The study shows that, depending on their experience and level of expertise in KR, users tend to select different patterns for the given modelling problems. In particular, experts appear to choose on the basis of representation power, while naïve users appear to select on the basis of surface features and perceived user-friendliness. Interestingly, while some patterns are indeed perceived to be more intuitive than others, these considerations seem to apply primarily to less experienced users. Indeed, our findings appear to indicate that experts consider issues of 'intuitiveness' as secondary and, in contrast with naïve users, may be happy to apply patterns, which can be regarded as counter-intuitive, if they provide the right tool for the job.