The Requirements for Ontologies in Medical Data Integration: A Case Study

Evidence-based medicine is critically dependent on three sources of information: a medical knowledge base, the patients medical record and knowledge of available resources, including where appropriate, clinical protocols. Patient data is often scattered in a variety of databases and may, in a distributed model, be held across several disparate repositories. Consequently addressing the needs of an evidence-based medicine community presents issues of biomedical data integration, clinical interpretation and knowledge management. This paper outlines how the Health-e-Child project has approached the challenge of requirements specification for (bio-) medical data integration, from the level of cellular data, through disease to that of patient and population. The approach is illuminated through the requirements elicitation and analysis of Juvenile Idiopathic Arthritis (JIA), one of three diseases being studied in the EC-funded Health-e-Child project.Comment: 6 pages, 1 figure. Presented at the 11th International Database Engineering & Applications Symposium (Ideas2007). Banff, Canada September 200

Optimizing the computation of overriding

We introduce optimization techniques for reasoning in DLN---a recently introduced family of nonmonotonic description logics whose characterizing features appear well-suited to model the applicative examples naturally arising in biomedical domains and semantic web access control policies. Such optimizations are validated experimentally on large KBs with more than 30K axioms. Speedups exceed 1 order of magnitude. For the first time, response times compatible with real-time reasoning are obtained with nonmonotonic KBs of this size

Ontologies for Intelligent e-Theraoy: Application to Obesity

[EN] In this paper we propose a new approach for mental e-health treatments named intelligent e-therapy (e-it) with capabilities for ambient intelligence and ubiquitous computing. The proposed e-it system supposes an evolution of cybertherapy and telepsychology tools used up to now. The e-it system is based in a knowledge base that includes all the knowledge related to the disorder and its treatment. We introduce the use of ontologies as the best option for the design of this knowledge base. We also present a fist e-it system for obesity treatment called etiobeZaragozá Álvarez, I.; Guixeres Provinciale, J.; Alcañiz Raya, ML. (2009). Ontologies for Intelligent e-Theraoy: Application to Obesity. Lecture Notes in Computer Science. 5518:894-901. doi:10.1007/978-3-642-02481-8_136S8949015518Baños, R.M., Botella, C., Perpiñá, C., Alcañiz, M., Lozano, J.A., Osma, J., Gallardo, M.: Virtual reality treatment of flying phobia. IEEE Transactions on Information Technology in Biomedicine 6(3), 206–212 (2002)Botella, C., Baños, R.M., Perpiña, C., et al.: Virtual reality treatment of claustrophobia: a case report. Behaviour Research & Therapy 36, 239–246 (1998)Hu, B., Dasmahapatra, S., Dupplaw, D., Lewis, P., Shadbolt, N.: Reflections on a medical ontology. International Journal of Human- Computer Studies 65(2007), 569–582 (2007)Rubin, D.L., Shah, N.H., Noy, N.F.: Biomedical ontologies: a functional perspective. Briefings in bioinformatics 9(1), 75–90 (2007)Stevens, R., Egaña Aranguren, M., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, M., Rector, A.: Using OWL to model biological knowledge. International Journal of Human-Computer Studies 65(2007), 583–594 (2007)Park, S., Lee, J.K.: Rule identification using ontology while acquiring rules from Web pages. International Journal of Human-Computer Studies 65(2007), 644–658 (2007)Clark, K.L., McCabe, F.G.: Ontology schema for an agent belief store. International Journal of Human-Computer Studies 65(2007), 625–643 (2007)Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)Franco, C., Bengtsson, B., Johannsson, G.: The GH/IGF-1 Axis in Obesity: Physiological and Pathological aspects. Metabolic syndrome and Related Disorders 4, 51–56 (2006

Using ontologies: understanding the user experience

Drawing on 118 responses to a survey of ontology use, this paper describes the experiences of those who create and use ontologies. Responses to questions about language and tool use illustrate the dominant position of OWL and provide information about the OWL profiles and particular Description Logic features used. The paper suggests that further research is required into the difficulties experienced with OWL constructs, and with modelling in OWL. The survey also reports on the use of ontology visualization software, finding that the importance of visualization to ontology users varies considerably. This is also an area which requires further investigation. The use of ontology patterns is examined, drawing on further input from a follow-up study devoted exclusively to this topic. Evidence suggests that pattern creation and use are frequently informal processes and there is a need for improved tools. A classification of ontology users into four groups is suggested. It is proposed that the categorisation of users and user behaviour should be taken into account when designing ontology tools and methodologies. This should enable rigorous, user-specific use cases

Developing a kidney and urinary pathway knowledge base

<p>Abstract</p> <p>Background</p> <p>Chronic renal disease is a global health problem. The identification of suitable biomarkers could facilitate early detection and diagnosis and allow better understanding of the underlying pathology. One of the challenges in meeting this goal is the necessary integration of experimental results from multiple biological levels for further analysis by data mining. Data integration in the life science is still a struggle, and many groups are looking to the benefits promised by the Semantic Web for data integration.</p> <p>Results</p> <p>We present a Semantic Web approach to developing a knowledge base that integrates data from high-throughput experiments on kidney and urine. A specialised KUP ontology is used to tie the various layers together, whilst background knowledge from external databases is incorporated by conversion into RDF. Using SPARQL as a query mechanism, we are able to query for proteins expressed in urine and place these back into the context of genes expressed in regions of the kidney.</p> <p>Conclusions</p> <p>The KUPKB gives KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. The Semantic Web technologies we use, together with the background knowledge from the domain’s ontologies, allows both rapid conversion and integration of this knowledge base. The KUPKB is still relatively small, but questions remain about scalability, maintenance and availability of the knowledge itself.</p> <p>Availability</p> <p>The KUPKB may be accessed via <url>http://www.e-lico.eu/kupkb</url>.</p

SBOL-OWL: An ontological approach for formal and semantic representation of synthetic biology information

Standard representation of data is key for the reproducibility of designs in synthetic biology. The Synthetic Biology Open Language (SBOL) has already emerged as a data standard to represent information about genetic circuits, and it is based on capturing data using graphs. The language provides the syntax using a free text document that is accessible to humans only. This paper describes SBOL-OWL, an ontology for a machine understandable definition of SBOL. This ontology acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addition to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tools for synthetic biology. This paper demonstrates some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries can be simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cannot be directly retrieved using existing querying mechanisms. This ontological representation of the SBOL standard provides a new perspective to the verification, representation, and querying of information about genetic circuits and is important to incorporate complex design information via the integration of biological ontologies

Current Trends and New Challenges of Databases and Web Applications for Systems Driven Biological Research

Dynamic and rapidly evolving nature of systems driven research imposes special requirements on the technology, approach, design and architecture of computational infrastructure including database and Web application. Several solutions have been proposed to meet the expectations and novel methods have been developed to address the persisting problems of data integration. It is important for researchers to understand different technologies and approaches. Having familiarized with the pros and cons of the existing technologies, researchers can exploit its capabilities to the maximum potential for integrating data. In this review we discuss the architecture, design and key technologies underlying some of the prominent databases and Web applications. We will mention their roles in integration of biological data and investigate some of the emerging design concepts and computational technologies that are likely to have a key role in the future of systems driven biomedical research