| Heinrich Herre|
(Alternative names for this author)
|Co-authors||Alexandr Uciteli, Frank Loebe, Janet Kelso, Johann Visagie, Joshua Bacher, Kay Prüfer, Michael Backhaus, Ngomo A.-C.N., Robert Hoehndorf, Sergio Gregorio|
|Authorship||Publications (3), datasets (0), tools (0)|
|Citations||Total (0), average (0), median (0), max (0), min (0)|
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Heinrich Herre is an author.
PublicationsOnly those publications related to wikis are shown here.
|Title||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology||English||2009||MOTIVATION:Ontology development and the annotation of biological data using ontologies are time-consuming exercises that currently require input from expert curators. Open, collaborative platforms for biological data annotation enable the wider scientific community to become involved in developing and maintaining such resources. However, this openness raises concerns regarding the quality and correctness of the information added to these knowledge bases. The combination of a collaborative web-based platform with logic-based approaches and Semantic Web technology can be used to address some of these challenges and concerns.RESULTS:We have developed the BOWiki, a web-based system that includes a biological core ontology. The core ontology provides background knowledge about biological types and relations. Against this background, an automated reasoner assesses the consistency of new information added to the knowledge base. The system provides a platform for research communities to integrate information and annotate data collaboratively.AVAILABILITY:The BOWiki and supplementary material is available at http://www.bowiki.net/. The source code is available under the GNU GPL from http://onto.eva.mpg.de/trac/BoWiki.||0||0|
|Developing consistent and modular software models with ontologies||Formal ontology
|Proceedings of 8th International Conference on New Trends in Software Methodologies, Tools and Techniques, SoMeT 09||English||2009||The development and verification of software models that are applicable across multiple domains remains a difficult problem. We propose a novel approach to model-driven software development based on ontologies and Semantic Web technology. Our approach uses three ontologies to define software models: a task ontology, a domain ontology and a top-level ontology. The task ontology serves as the conceptual model for the software, the domain ontology provides domainspecific knowledge and the top-level ontology integrates the task and domain ontologies. Our method allows the verification of these models both for consistency and ontological adequacy. This verification can be performed both at development and runtime. Domain ontologies are replaceable modules, which enables the comparison and application of the models built using our method across multiple domains. We demonstrate the viability of our approach through the design and implementation of a semantic wiki and a social tagging system, and compare it with model-driven software development to illustrate its benefits.||0||0|
|A Proposal for a Gene Functions Wiki||English||2006||Large knowledge bases integrating different domains can provide a foundation for new applications in biology such as data mining or automated reasoning. The traditional approach to the construction of such knowledge bases is manual and therefore extremely time consuming. The ubiquity of the internet now makes large-scale community collaboration for the construction of knowledge bases, such as the successful online encyclopedia “Wikipedia”, possible. We propose an extension of this model to the collaborative annotation of molecular data. We argue that a semantic wiki provides the functionality required for this project since this can capitalize on the existing representations in biological ontologies. We discuss the use of a different relationship model than the one provided by RDF and OWL to represent the semantic data. We argue that this leads to a more intuitive and correct way to enter semantic content in the wiki. Furthermore, we show how formal ontologies could be used to increase the usability of the software through type-checking and automatic reasoning.||0||0|