Frank Loebe

Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies

BackgroundCurrent efforts within the biomedical ontology community focus on achieving interoperability between various biomedical ontologies that cover a range of diverse domains. Achieving this interoperability will contribute to the creation of a rich knowledge base that can be used for querying, as well as generating and testing novel hypotheses. The OBO Foundry principles, as applied to a number of biomedical ontologies, are designed to facilitate this interoperability. However, semantic extensions are required to meet the OBO Foundry interoperability goals. Inconsistencies may arise when ontologies of properties – mostly phenotype ontologies – are combined with ontologies taking a canonical view of a domain – such as many anatomical ontologies. Currently, there is no support for a correct and consistent integration of such ontologies.ResultsWe have developed a methodology for accurately representing canonical domain ontologies within the OBO Foundry. This is achieved by adding an extension to the semantics for relationships in the biomedical ontologies that allows for treating canonical information as default. Conclusions drawn from default knowledge may be revoked when additional information becomes available. We show how this extension can be used to achieve interoperability between ontologies, and further allows for the inclusion of more knowledge within them. We apply the formalism to ontologies of mouse anatomy and mammalian phenotypes in order to demonstrate the approach.ConclusionBiomedical ontologies require a new class of relations that can be used in conjunction with default knowledge, thereby extending those currently in use. The inclusion of default knowledge is necessary in order to ensure interoperability between ontologies.

A top-level ontology of functions and its application in the Open Biomedical Ontologies

MOTIVATION A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the communitys knowledge about biological functions. RESULTS We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies. AVAILABILITY The Ontology of Functions (OF) can be downloaded in OWL format from http://onto.eva.mpg.de/. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website.

Modeling surgical processes: A four-level translational approach

MOTIVATION The precise and formal specification of surgical interventions is a necessary requirement for many applications in surgery, including teaching and learning, quality assessment and evaluation, and computer-assisted surgery. Currently, surgical processes are modeled by following various approaches. This diversity lacks a commonly agreed-upon conceptual foundation and thus impedes the comparability, the interoperability, and the uniform interpretation of process data. OBJECTIVE However, it would be beneficial if scientific models, in the same context, shared a coherent conceptual and formal mathematical basis. Such a uniform foundation would simplify the acquisition and exchange of data, the transition and interpretation of study results, and the transfer and adaptation of methods and tools. Therefore, we propose a generic, formal framework for specifying surgical processes, which is presented together with its design methodology. METHODS The methodology follows a four-level translational approach and comprises an ontological foundation for the formal level that orients itself by linguistic theories. RESULTS A unifying framework for modeling surgical processes that is ontologically founded and formally and mathematically precise was developed. The expressive power and the unifying capacity of the presented framework are demonstrated by applying it to four contemporary approaches for surgical process modeling by using the common underlying formalization. CONCLUSIONS The presented four-level approach allows for capturing the knowledge of the surgical intervention formally. Natural language terms are consistently translated to an implementation level to support research fields where users express their expert knowledge about processes in natural language, but, in contrast to this, statistical analysis or data mining need to be performed based on mathematically formalized data sets. The availability of such a translational approach is a valuable extension for research regarding the operating room of the future.

GFO-Bio: A biological core ontology

The rapid increase in the number and use of biological ontologies necessitates developing systems for their integration. In this paper we present a core ontology for biology, and outline its application for integrating biological domain ontologies. Our ontology rests on a foundational ontology, which offers higher-order categories and a theory of levels of reality. The core ontology is implemented in two separate components, each of which adheres to OWL-DL. These can be used independently with efficient DL reasoners, but they will be most effective when used together, which necessitates working with an OWL-Full ontology. The ontology is freely available from our website at: http://bioonto.de/pmwiki.php/Main/GFO-Bio.

BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology

MotivationOntology 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.ResultsWe 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.AvailabilityThe 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.

Similarity metrics for surgical process models

OBJECTIVE The objective of this work is to introduce a set of similarity metrics for comparing surgical process models (SPMs). SPMs are progression models of surgical interventions that support quantitative analyses of surgical activities, supporting systems engineering or process optimization. METHODS AND MATERIALS Five different similarity metrics are presented and proven. These metrics deal with several dimensions of process compliance in surgery, including granularity, content, time, order, and frequency of surgical activities. The metrics were experimentally validated using 20 clinical data sets each for cataract interventions, craniotomy interventions, and supratentorial tumor resections. The clinical data sets were controllably modified in simulations, which were iterated ten times, resulting in a total of 600 simulated data sets. The simulated data sets were subsequently compared to the original data sets to empirically assess the predictive validity of the metrics. RESULTS We show that the results of the metrics for the surgical process models correlate significantly (p<0.001) with the induced modifications and that all metrics meet predictive validity. The clinical use of the metrics was exemplarily, as demonstrated by assessment of the learning curves of observers during surgical process model acquisition. CONCLUSION Measuring similarity between surgical processes is a complex task. However, metrics for computing the similarity between surgical process models are needed in many uses in the field of medical engineering. These metrics are essential whenever two SPMs need to be compared, such as during the evaluation of technical systems, the education of observers, or the determination of surgical strategies. These metrics are key figures that provide a solid base for medical decisions, such as during validation of sensor systems for use in operating rooms in the future.

A proposal for a gene functions wiki

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.

A meta-ontological architecture for foundational ontologies

In this paper we present and discuss a meta-ontological architecture for ontologies which centers on abstract core ontologies (ACOs). An ACO is the most abstract part of a foundational ontology. It is useful for an ontologically founded description of ontologies themselves, therefore ACOs are lifted to the meta-level. We propose a three-layered meta-ontological architecture which distinguishes an object level comprising foundational, generic or domain-specific ontologies, a meta-level with abstract core ontologies, and a meta-meta-level employing abstract top ontologies for the formalization of the underlying levels. Moreover, two axiomatic fragments for ACOs are provided, one of which is applied to formal concept lattices [1]. This demonstrates the use of ACOs for the ontological foundation of representation formalisms and illustrates advantages in comparison to the usual direct formal reduction to set theory. Finally, related work with respect to the architecture is briefly discussed.

Axiomatic theories of the ontology of time in GFO

Time is a pervasive notion of high impact in information systems and computer science altogether. Respective understandings of the domain of time are fundamental for numerous areas, frequently in combination with closely related entities such as events, changes and processes. The conception and representation of time entities and reasoning about temporal data and knowledge are thus significant research areas. Each representation of temporal knowledge bears ontological commitments concerning time. Thus it is important to base temporal representations on a foundational ontology that covers general categories of time entities.In this article we introduce and discuss two consecutive ontologies of time that have been developed for the top-level ontology General Formal Ontology (GFO). The first covers intervals, named chronoids, and time boundaries of chronoids, as a kind of time points. One important specialty of time boundaries is their ability to coincide with other time boundaries. The second theory extends the first one by additionally addressing time regions, i.e., mereological sums of chronoids.Both ontologies are partially inspired by ideas of Franz Brentano, especially from his writings about the continuum. In particular, we view continuous time intervals as a genuine phenomenon which should not be identified with intervals (sets) of real numbers. On these grounds the resulting ontologies allow for proposing novel contributions to several problematic issues in temporal representation and reasoning, among others, the Dividing Instant Problem and the problem of persistence and change.Following our general approach to ontology development, both ontologies are axiomatized as formal theories in first-order logic and are analyzed metalogically. We prove the consistency of both ontologies, and completeness and decidability for one. Moreover, standard time theories with points and intervals are covered by both theories.

Management of evolving semantic grid metadata within a collaborative platform

Grid environments, providing distributed infrastructures, computing resources and data storage, usually show a high degree of heterogeneity and change in their metadata. We propose a platform for collaborative management and maintenance of common metadata for grids. As the conceptual foundation of this platform, a meta model is presented which distinguishes structured descriptions and classification structures that both are modifiable. On this basis, the system allows for the creation and editing of grid relevant metadata and provides various search and navigation facilities for grid participants. We applied the platform to the German D-Grid initiative by establishing the D-Grid Ontology (DGO).