OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

Institutionalising Ontology-Based Semantic Integration

We address what is still a scarcity of general mathematical foundations for ontology-based semantic integration underlying current knowledge engineering methodologies in decentralised and distributed environments. After recalling the first-order ontology-based approach to semantic integration and a formalisation of ontological commitment, we propose a general theory that uses a syntax-and interpretation-independent formulation of language, ontology, and ontological commitment in terms of institutions. We claim that our formalisation generalises the intuitive notion of ontology-based semantic integration while retaining its basic insight, and we apply it for eliciting and hence comparing various increasingly complex notions of semantic integration and ontological commitment based on differing understandings of semantics

The Information-Flow Approach to Ontology-Based Semantic Integration

In this article we argue for the lack of formal foundations for ontology-based semantic alignment. We analyse and formalise the basic notions of semantic matching and alignment and we situate them in the context of ontology-based alignment in open-ended and distributed environments, like the Web. We then use the mathematical notion of information flow in a distributed system to ground three hypotheses that enable semantic alignment. We draw our exemplar applications of this work from a variety of interoperability scenarios including ontology mapping, theory of semantic interoperability, progressive ontology alignment, and situated semantic alignment

Applying MDE tools to defining domain specific languages for model management

In the model driven engineering (MDE), modeling languages play a central role. They range from the most generic languages such as UML, to more individual ones, called domain-specific modeling languages (DSML). These languages are used to create and manage models and must accompany them throughout their life cycle and evolution. In this paper we propose a domain-specific language for model management, to facilitate the user's task, developed with techniques and tools used in the MDE paradigm.Fil: Pérez, Gabriela. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; ArgentinaFil: Irazábal, Jerónimo. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pons, Claudia Fabiana. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Giandini, Roxana Silvia. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentin

Controlled vocabularies and semantics in systems biology

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments