2,070 research outputs found

    Ontology as the core discipline of biomedical informatics: Legacies of the past and recommendations for the future direction of research

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    The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable

    What's unusual in online disease outbreak news?

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    Background: Accurate and timely detection of public health events of international concern is necessary to help support risk assessment and response and save lives. Novel event-based methods that use the World Wide Web as a signal source offer potential to extend health surveillance into areas where traditional indicator networks are lacking. In this paper we address the issue of systematically evaluating online health news to support automatic alerting using daily disease-country counts text mined from real world data using BioCaster. For 18 data sets produced by BioCaster, we compare 5 aberration detection algorithms (EARS C2, C3, W2, F-statistic and EWMA) for performance against expert moderated ProMED-mail postings. Results: We report sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), mean alerts/100 days and F1, at 95% confidence interval (CI) for 287 ProMED-mail postings on 18 outbreaks across 14 countries over a 366 day period. Results indicate that W2 had the best F1 with a slight benefit for day of week effect over C2. In drill down analysis we indicate issues arising from the granular choice of country-level modeling, sudden drops in reporting due to day of week effects and reporting bias. Automatic alerting has been implemented in BioCaster available from http://born.nii.ac.jp. Conclusions: Online health news alerts have the potential to enhance manual analytical methods by increasing throughput, timeliness and detection rates. Systematic evaluation of health news aberrations is necessary to push forward our understanding of the complex relationship between news report volumes and case numbers and to select the best performing features and algorithms

    A pattern-based approach to a cell tracking ontology

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    Time-lapse microscopy has thoroughly transformed our understanding of biological motion and developmental dynamics from single cells to entire organisms. The increasing amount of cell tracking data demands the creation of tools to make extracted data searchable and interoperable between experiment and data types. In order to address that problem, the current paper reports on the progress in building the Cell Tracking Ontology (CTO): An ontology framework for describing, querying and integrating data from complementary experimental techniques in the domain of cell tracking experiments. CTO is based on a basic knowledge structure: the cellular genealogy serving as a backbone model to integrate specific biological ontologies into tracking data. As a first step we integrate the Phenotype and Trait Ontology (PATO) as one of the most relevant ontologies to annotate cell tracking experiments. The CTO requires both the integration of data on various levels of generality as well as the proper structuring of collected information. Therefore, in order to provide a sound foundation of the ontology, we have built on the rich body of work on top-level ontologies and established three generic ontology design patterns addressing three modeling challenges for properly representing cellular genealogies, i.e. representing entities existing in time, undergoing changes over time and their organization into more complex structures such as situations

    The evaluation of ontologies: Editorial review vs. democratic ranking

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    Increasingly, the high throughput technologies used by biomedical researchers are bringing about a situation in which large bodies of data are being described using controlled structured vocabularies—also known as ontologies—in order to support the integration and analysis of this data. Annotation of data by means of ontologies is already contributing in significant ways to the cumulation of scientific knowledge and, prospectively, to the applicability of cross-domain algorithmic reasoning in support of scientific advance. This very success, however, has led to a proliferation of ontologies of varying scope and quality. We define one strategy for achieving quality assurance of ontologies—a plan of action already adopted by a large community of collaborating ontologists—which consists in subjecting ontologies to a process of peer review analogous to that which is applied to scientific journal articles

    1st INCF Workshop on Sustainability of Neuroscience Databases

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    The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability

    A black art: Ontology, data, and the Tower of Babel problem

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    Computational ontologies are a new type of emerging scientific media (Smith, 2016) that process large quantities of heterogeneous data about portions of reality. Applied computational ontologies are used for semantically integrating (Heiler, 1995; Pileggi & Fernandez-Llatas, 2012) divergent data to represent reality and in so doing applied computational ontologies alter conceptions of materiality and produce new realities based on levels of informational granularity and abstraction (Floridi, 2011), resulting in a new type of informational ontology (Iliadis, 2013) the critical analysis of which requires new methods and frameworks. Currently, there is a lack of literature addressing the theoretical, social, and critical dimensions of such informational ontologies, applied computational ontologies, and the interdisciplinary communities of practice (Brown & Duguid, 1991; Wenger, 1998) that produce them. This dissertation fills a lacuna in communicative work in an emerging subfield of Science and Technology Studies (Latour & Woolgar, 1979) known as Critical Data Studies (boyd & Crawford, 2012; Dalton & Thatcher, 2014; Kitchin & Lauriault, 2014) by adopting a critical framework to analyze the systems of thought that inform applied computational ontology while offering insight into its realism-based methods and philosophical frameworks to gauge their ethical import. Since the early 1990s, computational ontologies have been used to organize massive amounts of heterogeneous data by individuating reality into computable parts, attributes, and relations. This dissertation provides a theory of computational ontologies as technologies of individuation (Simondon, 2005) that translate disparate data to produce informational cohesion. By technologies of individuation I mean engineered artifacts whose purpose is to partition portions of reality into computable informational objects. I argue that data are metastable entities and that computational ontologies restrain heterogeneous data via a process of translation to produce semantic interoperability. In this way, I show that computational ontologies effectively re-ontologize (Floridi, 2013) and produce reality and thus that have ethical consequences, specifically in terms of their application to social reality and social ontology (Searle, 2006). I use the Basic Formal Ontology (Arp, Smith, & Spear, 2015)—the world’s most widely used upper-level ontology—as a case study and analyze its methods and ensuing ethical issues concerning its social application in the Military Ontology before recommending an ethical framework. “Ontology” is a term that is used in philosophy and computer science in related but different ways—philosophical ontology typically concerns metaphysics while computational ontology typically concerns databases. This dissertation provides a critical history and theory of ontology and the interdisciplinary teams of researchers that came to adopt methods from philosophical ontology to build, persuade, and reason with applied computational ontology. Following a critical communication approach, I define applied computational ontology construction as a solution to a communication problem among scientists who seek to create semantic interoperability among data and argue that applied ontology is philosophical, informational in nature, and communicatively constituted (McPhee & Zaug, 2000). The primary aim is to explain how philosophy informs applied computational ontology while showing how such ontologies became instantiated in material organizations, how to study them, and describe their ethical implications

    Barry Smith an sich

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    Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf Lüthe, Luc Schneider, Peter Simons, Wojciech Żełaniec, and Jan Woleński
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