359 research outputs found
Deductive Biocomputing
BACKGROUND: As biologists increasingly rely upon computational tools, it is imperative that they be able to appropriately apply these tools and clearly understand the methods the tools employ. Such tools must have access to all the relevant data and knowledge and, in some sense, āunderstandā biology so that they can serve biologists' goals appropriately and āexplainā in biological terms how results are computed. METHODOLOGY/PRINCIPAL FINDINGS: We describe a deduction-based approach to biocomputation that semiautomatically combines knowledge, software, and data to satisfy goals expressed in a high-level biological language. The approach is implemented in an open source web-based biocomputing platform called BioDeducta, which combines SRI's SNARK theorem prover with the BioBike interactive integrated knowledge base. The biologist/user expresses a high-level conjecture, representing a biocomputational goal query, without indicating how this goal is to be achieved. A subject domain theory, represented in SNARK's logical language, transforms the terms in the conjecture into capabilities of the available resources and the background knowledge necessary to link them together. If the subject domain theory enables SNARK to prove the conjectureāthat is, to find paths between the goal and BioBike resourcesāthen the resulting proofs represent solutions to the conjecture/query. Such proofs provide provenance for each result, indicating in detail how they were computed. We demonstrate BioDeducta by showing how it can approximately replicate a previously published analysis of genes involved in the adaptation of cyanobacteria to different light niches. CONCLUSIONS/SIGNIFICANCE: Through the use of automated deduction guided by a biological subject domain theory, this work is a step towards enabling biologists to conveniently and efficiently marshal integrated knowledge, data, and computational tools toward resolving complex biological queries
Towards natural language question generation for the validation of ontologies and mappings
FundaĆ§Ć£o de Amparo Ć Pesquisa do Estado de SĆ£o Paulo (FAPESP)The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-view. However, the growing number of ontologies and their fast evolution over time make manual validation challenging. Methods: We propose a novel semi-automatic approach based on the generation of natural language (NL) questions to support the validation of ontologies and their evolution. The proposed approach includes the automatic generation, factorization and ordering of NL questions from medical ontologies. The final validation and correction is performed by submitting these questions to domain experts and automatically analyzing their feedback. We also propose a second approach for the validation of mappings impacted by ontology changes. The method exploits the context of the changes to propose correction alternatives presented as Multiple Choice Questions. Results: This research provides a question optimization strategy to maximize the validation of ontology entities with a reduced number of questions. We evaluate our approach for the validation of three medical ontologies. We also evaluate the feasibility and efficiency of our mappings validation approach in the context of ontology evolution. These experiments are performed with different versions of SNOMED-CT and ICD9. Conclusions: The obtained experimental results suggest the feasibility and adequacy of our approach to support the validation of interconnected and evolving ontologies. Results also suggest that taking into account RDFS and OWL entailment helps reducing the number of questions and validation time. The application of our approach to validate mapping evolution also shows the difficulty of adapting mapping evolution over time and highlights the importance of semi-automatic validation.The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-vi7115FAPESP - FUNDAĆĆO DE AMPARO Ć PESQUISA DO ESTADO DE SĆO PAULOFundaĆ§Ć£o de Amparo Ć Pesquisa do Estado de SĆ£o Paulo (FAPESP)2014/14890-
A formal verification framework and associated tools for enterprise modeling : application to UEML
The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties
When one Logic is Not Enough: Integrating First-order Annotations in OWL Ontologies
In ontology development, there is a gap between domain ontologies which
mostly use the web ontology language, OWL, and foundational ontologies written
in first-order logic, FOL. To bridge this gap, we present Gavel, a tool that
supports the development of heterogeneous 'FOWL' ontologies that extend OWL
with FOL annotations, and is able to reason over the combined set of axioms.
Since FOL annotations are stored in OWL annotations, FOWL ontologies remain
compatible with the existing OWL infrastructure. We show that for the OWL
domain ontology OBI, the stronger integration with its FOL top-level ontology
BFO via our approach enables us to detect several inconsistencies. Furthermore,
existing OWL ontologies can benefit from FOL annotations. We illustrate this
with FOWL ontologies containing mereotopological axioms that enable new
meaningful inferences. Finally, we show that even for large domain ontologies
such as ChEBI, automatic reasoning with FOL annotations can be used to detect
previously unnoticed errors in the classification
Systems, methods and apparatus for modeling, specifying and deploying policies in autonomous and autonomic systems using agent-oriented software engineering
Systems, methods and apparatus are provided through which in some embodiments, an agent-oriented specification modeled with MaCMAS, is analyzed, flaws in the agent-oriented specification modeled with MaCMAS are corrected, and an implementation is derived from the corrected agent-oriented specification. Described herein are systems, method and apparatus that produce fully (mathematically) tractable development of agent-oriented specification(s) modeled with methodology fragment for analyzing complex multiagent systems (MaCMAS) and policies for autonomic systems from requirements through to code generation. The systems, method and apparatus described herein are illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming systems, method and apparatus described herein may provide faster, higher quality development and maintenance of autonomic systems based on user formulation of policies
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