The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online

BACKGROUND

 Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains.

OBJECTIVE

 The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects.

METHODS

 Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups.

RESULTS

 The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

Using formal ontology for the representation of morphological properties of anatomical structures in endoscopic surgery

In this paper we present results to the problem of an adequate and compact symbolic representation of morphological features of anatomical structures that serve as surgical landmarks for automated assistance in endoscopic surgery using the General Formal Ontology (GFO) as a formal framework. For this purpose, we employed a translation from this first-order logic representation to a more compact description logic based formalism with the associated benefits, such as the availability of decidable reasoning procedures, for the purpose of automated landmark recognition in a hybrid symbolic/subsymbolic AI approach.

Ontology patterns for the representation of quality changes of cells in time

Background

Cell tracking experiments, based on time-lapse microscopy, have become an important tool in biomedical research. The goal is the reconstruction of cell migration patterns, shape and state changes, and, comprehensive genealogical information from these data. This information can be used to develop process models of cellular dynamics. However, so far there has been no structured, standardized way of annotating and storing the tracking results, which is critical for comparative analysis and data integration. The key requirement to be satisfied by an ontology is the representation of a cell’s change over time. Unfortunately, popular ontology languages, such as Web Ontology Language (OWL), have limitations for the representation of temporal information. The current paper addresses the fundamental problem of modeling changes of qualities over time in biomedical ontologies specified in OWL.

Results

The presented analysis is a result of the lessons learned during the development of an ontology, intended for the annotation of cell tracking experiments. We present, discuss and evaluate various representation patterns for specifying cell changes in time. In particular, we discuss two patterns of temporally changing information: n-ary relation reification and 4d fluents. These representation schemes are formalized within the ontology language OWL and are aimed at the support for annotation of cell tracking experiments. We analyze the performance of each pattern with respect to standard criteria used in software engineering and data modeling, i.e. simplicity, scalability, extensibility and adequacy. We further discuss benefits, drawbacks, and the underlying design choices of each approach.

Conclusions

We demonstrate that patterns perform differently depending on the temporal distribution of modeled information. The optimal model can be constructed by combining two competitive approaches. Thus, we demonstrate that both reification and 4d fluents patterns can work hand in hand in a single ontology. Additionally, we have found that 4d fluents can be reconstructed by two patterns well known in the computer science community, i.e. state modeling and actor-role pattern.

Spreadsheet Model Generator (SMOG): A Lightweight Tool for Object-Spreadsheet Mapping

In the life science domain, experts are usually familiar with spreadsheet software and often use it in their daily work to collect and structure required domain knowledge. The processing and analysis of spreadsheet data is an important task that must be supported by efficient software solutions. A typical application scenario is for example an integration of spreadsheet data (specified or derived) in an ontology to provide reasoning or search. Different converter tools were developed to support a spreadsheet-to-ontology transformation. Such tools allow often only a relatively simple structure of the spreadsheet template or they require complex mapping processes to map the spreadsheet and ontological entities. In many cases, it is impossible to use the existing converter tools because the spreadsheet data must be processed first before the derived data can be integrated into the ontology. In such cases, an efficient and fast development of customized software solutions is of great importance. In this paper, we present a general spreadsheet processing framework to efficiently read and write spreadsheet data. The Spreadsheet Model Generator (SMOG) provides a simple mechanism to automatically generate the Java object model and mappings between object code and spreadsheet entities. Our solution greatly simplifies the implementation of spreadsheet access methods and enables an efficient development of spreadsheet-based applications. The SMOG has already been used successfully in several biomedical projects under real world conditions.

Ontology-based specification and generation of search queries for post-market surveillance

BACKGROUND

The vigilant observation of medical devices during post-market surveillance (PMS) for identifying safety-relevant incidents is a non-trivial task. A wide range of sources has to be monitored in order to integrate all accessible data about the safety and performance of a medical device. PMS needs to be supported by an efficient search strategy and the possibility to create complex search queries by domain experts.

RESULTS

We use ontologies to support the specification of search queries and the preparation of the document corpus, which contains all relevant documents. In this paper, we present (1) the Search Ontology (SON) v2.0, (2) an Excel template for specifying search queries, and (3) the Search Ontology Generator (SONG), which generates complex queries out of the Excel template. Based on our approach, a service-oriented architecture was designed, which supports and assists domain experts during PMS. Comprehensive testing confirmed the correct execution of all SONG functions. The applicability of our method and of the developed tools was evaluated by domain experts. The test persons concordantly rated our solution after a short period of training as highly user-friendly, intuitive and well applicable for supporting PMS.

CONCLUSIONS

The Search Ontology is a promising domain-independent approach to specify complex search queries. Our solution allows advanced searches for relevant documents in different domains using suitable domain ontologies.

An ontological framework for the formalization, organization and usage of TCM-Knowledge

Background

The traditional Chinese Medicine Language System (TCMLS) is a large-scale terminology system, developed from 2002 on by the Institute of Information of Traditional Chinese Medicine (IITCM). Until now, more than 120,000 concepts, 300,000 terms and 1.27 million semantic relational links are included. Its top-level framework, called TCMLS-semantic network (SN), provides an important basis for the standardization and mapping of traditional Chinese Medicine (TCM) terminology systems. Though, many data produced and stored in TCMLS have poor quality for historical reasons or because of human factors. There is a large number of classification errors or inconsistent expressions of terms remained in the current TCMLS- SN, which hamper an efficient utilization of the data stored in TCMLS in practical applications.

Methods

We start with analyzing the technical specification based on TCMLS, considering some obvious classification errors and problems of ambiguity of semantic expressions in TCMLS-SN, followed with using a top-down approach for building a middle level ontology which is based on the framework General Formal Ontology (GFO), take into account the compatibility with TCM related concepts, turn out the results of a modification of the current TCMLS-SN, called GFO-TCM.

Results

Through comparison with TCMLS-SN, according to viewpoints of GFO, some semantic types and relations were reconstructed within GFO-TCM. We propose a middle level ontology for TCMLS which may support entailment and ensure coherence, we also draw out a mapping which possess a more reasonable framework with a unified semantic criterion, it is application scenarios oriented and can be further updated and extended.

Conclusions

The goal is to construct a formal middle-level ontology that is compatible with both the traditional medical terminology system and modern medical terminology standards. it is intended to satisfy functional requirements which are relevant for natural language processing, information extraction, semantic retrieval, clinical decision support in the field of traditional Chinese medicine. It also provides a foundation and methodology for building a large-scale, unified semantic and extensible knowledge graph platform.

Querying archetype-based EHRs by search ontology-based XPath engineering

Background

Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents.

Methods

A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure. Such query specification method is practically introduced and evaluated by applying concrete research questions formulated in natural language on a data collection for information retrieval purposes. The search is performed by search ontology-based XPath engineering that reuses ontologies and XML-related W3C standards.

Results

The key result is that the specification of research questions can be supported by the usage of search ontology-based XPath engineering. A deeper recognition of entities and a semantic understanding of the content is necessary for a further improvement of precision and recall. Key limitation is that the application of the introduced process requires skills in ontology and software development. In future, the time consuming ontology development could be overcome by implementing a new clinical role: the clinical ontologist.

Conclusion

The introduced Search Ontology XML extension connects Search Terms to certain parts in XML documents and enables an ontology-based definition of queries. Search ontology-based XPath engineering can support research question answering by the specification of complex XPath expressions without deep syntax knowledge about XPaths.

Ontology-Guided Markerless Navigation and Situational Awareness for Endoscopic Surgery

Optical navigation systems help surgeons find their way through the complex anatomy of a patient. However, such systems are accident-sensitive, time-consuming and difficult to use because of their complicated technical requirements such as the setting of optical markers and their intraoperative registration. The BIOPASS project, therefore, provides an innovative localisation system for markerless navigation in endoscopic surgery to support medical decision making. This system comprises several machine learning classifiers to recognise anatomical structures visible in the endoscopic images. To verify the data provided by these classifiers and to alert medical staff about surgical risk situations, we developed a new ontology-based software called OntoSun. Our software improves the precision and the sustainable traceability of the classifiers' results and also provides warning messages that increase situational awareness during surgical interventions.

Ontology-based specification, identification and analysis of perioperative risks

BACKGROUND

Medical personnel in hospitals often works under great physical and mental strain. In medical decision-making, errors can never be completely ruled out. Several studies have shown that between 50 and 60% of adverse events could have been avoided through better organization, more attention or more effective security procedures. Critical situations especially arise during interdisciplinary collaboration and the use of complex medical technology, for example during surgical interventions and in perioperative settings (the period of time before, during and after surgical intervention).

METHODS

In this paper, we present an ontology and an ontology-based software system, which can identify risks across medical processes and supports the avoidance of errors in particular in the perioperative setting. We developed a practicable definition of the risk notion, which is easily understandable by the medical staff and is usable for the software tools. Based on this definition, we developed a Risk Identification Ontology (RIO) and used it for the specification and the identification of perioperative risks.

RESULTS

An agent system was developed, which gathers risk-relevant data during the whole perioperative treatment process from various sources and provides it for risk identification and analysis in a centralized fashion. The results of such an analysis are provided to the medical personnel in form of context-sensitive hints and alerts. For the identification of the ontologically specified risks, we developed an ontology-based software module, called Ontology-based Risk Detector (OntoRiDe).

CONCLUSIONS

About 20 risks relating to cochlear implantation (CI) have already been implemented. Comprehensive testing has indicated the correctness of the data acquisition, risk identification and analysis components, as well as the web-based visualization of results.

Using Fast Healthcare Interoperability Resources (FHIR) for the Integration of Risk Minimization Systems in Hospitals

With the growing strain of medical staff and complexity of patient care, the risk of medical errors increases. In this work we present the use of Fast Healthcare Interoperability Resources (FHIR) as communication standard for the integration of an ontology- and agent-based system to identify risks across medical processes in a clinical environment.

Expert2OWL: A Methodology for Pattern-Based Ontology Development

The formalization of expert knowledge enables a broad spectrum of applications employing ontologies as underlying technology. These include eLearning, Semantic Web and expert systems. However, the manual construction of such ontologies is time-consuming and thus expensive. Moreover, experts are often unfamiliar with the syntax and semantics of formal ontology languages such as OWL and usually have no experience in developing formal ontologies. To overcome these barriers, we developed a new method and tool, called Expert2OWL that provides efficient features to support the construction of OWL ontologies using GFO (General Formal Ontology) as a top-level ontology. This method allows a close and effective collaboration between ontologists and domain experts. Essentially, this tool integrates Excel spreadsheets as part of a pattern-based ontology development and refinement process. Expert2OWL enables us to expedite the development process and modularize the resulting ontologies. We applied this method in the field of Chinese Herbal Medicine (CHM) and used Expert2OWL to automatically generate an accurate Chinese Herbology ontology (CHO). The expressivity of CHO was tested and evaluated using ontology query languages SPARQL and DL. CHO shows promising results and can generate answers to important scientific questions such as which Chinese herbal formulas contain which substances, which substances treat which diseases, and which ones are the most frequently used in CHM.

Light-Weighted Automatic Import of Standardized Ontologies into the Content Management System Drupal

The amount of ontologies, which are utilizable for widespread domains, is growing steadily. BioPortal alone, embraces over 500 published ontologies with nearly 8 million classes. In contrast, the vast informative content of these ontologies is only directly intelligible by experts. To overcome this deficiency it could be possible to represent ontologies as web portals, which does not require knowledge about ontologies and their semantics, but still carries as much information as possible to the end-user. Furthermore, the conception of a complex web portal is a sophisticated process. Many entities must be analyzed and linked to existing terminologies. Ontologies are a decent solution for gathering and storing this complex data and dependencies. Hence, automated imports of ontologies into web portals could support both mentioned scenarios. The Content Management System (CMS) Drupal 8 is one of many solutions to develop web presentations with less required knowledge about programming languages and it is suitable to represent ontological entities. We developed the Drupal Upper Ontology (DUO), which models concepts of Drupal's architecture, such as nodes, vocabularies and links. DUO can be imported into ontologies to map their entities to Drupal's concepts. Because of Drupal's lack of import capabilities, we implemented the Simple Ontology Loader in Drupal (SOLID), a Drupal 8 module, which allows Drupal administrators to import ontologies based on DUO. Our module generates content in Drupal from existing ontologies and makes it accessible by the general public. Moreover Drupal offers a tagging system which may be amplified with multiple standardized and established terminologies by importing them with SOLID. Our Drupal module shows that ontologies can be used to model content of a CMS and vice versa CMS are suitable to represent ontologies in a user-friendly way. Ontological entities are presented to the user as discrete pages with all appropriate properties, links and tags.

Processual Reasoning over Sequences of Situations in Endoscopic Surgery

Minimally invasive surgery is a highly complex and technically demanding alternative to open surgery. Surgical procedures based on this method are characterized by small incisions and allow for a fast recovery of the patient. Such techniques are challenging for surgeons since they do not have a direct view of the surgical area. Systems that provide surgical navigation are well established in clinical practice but depend on external markers allowing a mapping between a surgeon's tools and a patient's medical images. As of today, these systems are prone to inaccuracies, the reasons of which lie in their extensive technical requirements. The BIOPASS project aims to develop an alternative that works without external markers and indirect computation of locations. An ontology has been used to provide an adequate vocabulary describing situations and their temporal relationship. This ontology is expected to relate real time multimodal sensor data and static surgical process models in order to infer movement directions, subsequent actions and hidden anatomical structures that inhere risk for surgical interventions. However, the Web Ontology Language is not capable of modelling temporal conditions, which are necessary to provide such exhaustive situational descriptions as expected by a surgeon. This paper concerns an ontology design pattern developed to overcome this issue by the integration of dynamic ontological classes that are assigned according to the temporal relations between situations.

An Approach to Support Collaborative Ontology Construction

The increasing number of terms used in textbooks for information management (IM) in hospitals makes it difficult for medical informatics students to grasp IM concepts and their interrelations. Formal ontologies which comprehend and represent the essential content of textbooks can facilitate the learning process in IM education. The manual construction of such ontologies is time-consuming and thus very expensive [3]. Moreover, most domain experts lack skills in using a formal language like OWL [2] and usually have no experience with standard editing tools like Protégé <fnr rid="fn001" /><fn id="fn001">http://protege.stanford.edu </fn> [4,5]. This paper presents an ontology modeling approach based on Excel2OWL, a self-developed tool which efficiently supports domain experts in collaboratively constructing ontologies from textbooks. This approach was applied to classic IM textbooks, resulting in an ontology called SNIK. Our method facilitates the collaboration between domain experts and ontologists in the development process. Furthermore, the proposed approach enables ontologists to detect modeling errors and also to evaluate and improve the quality of the resulting ontology rapidly. This approach allows us to visualize the modeled textbooks and to analyze their semantics automatically. Hence, it can be used for e-learning purposes, particularly in the field of IM in hospitals.

OntoStudyEdit: a new approach for ontology-based representation and management of metadata in clinical and epidemiological research

Background

The specification of metadata in clinical and epidemiological study projects absorbs significant expense. The validity and quality of the collected data depend heavily on the precise and semantical correct representation of their metadata.

In various research organizations, which are planning and coordinating studies, the required metadata are specified differently, depending on many conditions, e.g., on the used study management software. The latter does not always meet the needs of a particular research organization, e.g., with respect to the relevant metadata attributes and structuring possibilities.

Methods

The objective of the research, set forth in this paper, is the development of a new approach for ontology-based representation and management of metadata. The basic features of this approach are demonstrated by the software tool OntoStudyEdit (OSE). The OSE is designed and developed according to the three ontology method. This method for developing software is based on the interactions of three different kinds of ontologies: a task ontology, a domain ontology and a top-level ontology.

Results

The OSE can be easily adapted to different requirements, and it supports an ontologically founded representation and efficient management of metadata. The metadata specifications can by imported from various sources; they can be edited with the OSE, and they can be exported in/to several formats, which are used, e.g., by different study management software.

Conclusions

Advantages of this approach are the adaptability of the OSE by integrating suitable domain ontologies, the ontological specification of mappings between the import/export formats and the DO, the specification of the study metadata in a uniform manner and its reuse in different research projects, and an intuitive data entry for non-expert users.

Towards improving phenotype representation in OWL

BACKGROUND

Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected entities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies.

METHODS

We analyze formalizations of complex phenotype descriptions in the Web Ontology Language (OWL) that are based on the EQ model, identify several representational challenges and analyze potential solutions to address these challenges.

RESULTS

In particular, we suggest a novel, role-based approach to represent relational qualities such as concentration of iron in spleen, discuss its ontological foundation in the General Formal Ontology (GFO) and evaluate its representation in OWL and the benefits it can bring to the representation of phenotype annotations.

CONCLUSION

Our analysis of OWL-based representations of phenotypes can contribute to improving consistency and expressiveness of formal phenotype descriptions.

Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology

MOTIVATION

The systematic observation of phenotypes has become a crucial tool of functional genomics, and several large international projects are currently underway to identify and characterize the phenotypes that are associated with genotypes in several species. To integrate phenotype descriptions within and across species, phenotype ontologies have been developed. Applying ontologies to unify phenotype descriptions in the domain of physiology has been a particular challenge due to the high complexity of the underlying domain.

RESULTS

In this study, we present the outline of a theory and its implementation for an ontology of physiology-related phenotypes. We provide a formal description of process attributes and relate them to the attributes of their temporal parts and participants. We apply our theory to create the Cellular Phenotype Ontology (CPO). The CPO is an ontology of morphological and physiological phenotypic characteristics of cells, cell components and cellular processes. Its prime application is to provide terms and uniform definition patterns for the annotation of cellular phenotypes. The CPO can be used for the annotation of observed abnormalities in domains, such as systems microscopy, in which cellular abnormalities are observed and for which no phenotype ontology has been created.

AVAILABILITY AND IMPLEMENTATION

The CPO and the source code we generated to create the CPO are freely available on http://cell-phenotype.googlecode.com.

OBML - Ontologies in Biomedicine and Life Sciences

The OBML 2010 workshop, held at the University of Mannheim on September 9-10, 2010, is the 2^nd in a series of meetings organized by the Working Group “Ontologies in Biomedicine and Life Sciences” of the German Society of Computer Science (GI) and the German Society of Medical Informatics, Biometry and Epidemiology (GMDS). Integrating, processing and applying the rapidly expanding information generated in the life sciences — from public health to clinical care and molecular biology — is one of the most challenging problems that research in these fields is facing today. As the amounts of experimental data, clinical information and scientific knowledge increase, there is a growing need to promote interoperability of these resources, support formal analyses, and to pre-process knowledge for further use in problem solving and hypothesis formulation.

The OBML workshop series pursues the aim of gathering scientists who research topics related to life science ontologies, to exchange ideas, discuss new results and establish relationships. The OBML group promotes the collaboration between ontologists, computer scientists, bio-informaticians and applied logicians, as well as the cooperation with physicians, biologists, biochemists and biometricians, and supports the establishment of this new discipline in research and teaching. Research topics of OBML 2010 included medical informatics, Semantic Web applications, formal ontology, bio-ontologies, knowledge representation as well as the wide range of applications of biomedical ontologies to science and medicine. A total of 14 papers were presented, and from these we selected four manuscripts for inclusion in this special issue.

An interdisciplinary audience from all areas related to biomedical ontologies attended OBML 2010. In the future, OBML will continue as an annual meeting that aims to bridge the gap between theory and application of ontologies in the life sciences. The next event emphasizes the special topic of the ontology of phenotypes, in Berlin, Germany on October 6-7, 2011.

An ontologically founded architecture for information systems in clinical and epidemiological research

This paper presents an ontologically founded basic architecture for information systems, which are intended to capture, represent, and maintain metadata for various domains of clinical and epidemiological research. Clinical trials exhibit an important basis for clinical research, and the accurate specification of metadata and their documentation and application in clinical and epidemiological study projects represents a significant expense in the project preparation and has a relevant impact on the value and quality of these studies.An ontological foundation of an information system provides a semantic framework for the precise specification of those entities which are presented in this system. This semantic framework should be grounded, according to our approach, on a suitable top-level ontology. Such an ontological foundation leads to a deeper understanding of the entities of the domain under consideration, and provides a common unifying semantic basis, which supports the integration of data and the interoperability between different information systems.The intended information systems will be applied to the field of clinical and epidemiological research and will provide, depending on the application context, a variety of functionalities. In the present paper, we focus on a basic architecture which might be common to all such information systems. The research, set forth in this paper, is included in a broader framework of clinical research and continues the work of the IMISE on these topics.

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.

Relations as patterns: bridging the gap between OBO and OWL

BACKGROUND

most biomedical ontologies are represented in the OBO Flatfile Format, which is an easy-to-use graph-based ontology language. The semantics of the OBO Flatfile Format 1.2 enforces a strict predetermined interpretation of relationship statements between classes. It does not allow flexible specifications that provide better approximations of the intuitive understanding of the considered relations. If relations cannot be accurately expressed then ontologies built upon them may contain false assertions and hence lead to false inferences. Ontologies in the OBO Foundry must formalize the semantics of relations according to the OBO Relationship Ontology (RO). Therefore, being able to accurately express the intended meaning of relations is of crucial importance. Since the Web Ontology Language (OWL) is an expressive language with a formal semantics, it is suitable to de ne the meaning of relations accurately.

RESULTS

we developed a method to provide definition patterns for relations between classes using OWL and describe a novel implementation of the RO based on this method. We implemented our extension in software that converts ontologies in the OBO Flatfile Format to OWL, and also provide a prototype to extract relational patterns from OWL ontologies using automated reasoning. The conversion software is freely available at http://bioonto.de/obo2owl, and can be accessed via a web interface.

CONCLUSIONS

explicitly defining relations permits their use in reasoning software and leads to a more flexible and powerful way of representing biomedical ontologies. Using the extended langua0067e and semantics avoids several mistakes commonly made in formalizing biomedical ontologies, and can be used to automatically detect inconsistencies. The use of our method enables the use of graph-based ontologies in OWL, and makes complex OWL ontologies accessible in a graph-based form. Thereby, our method provides the means to gradually move the representation of biomedical ontologies into formal knowledge representation languages that incorporates an explicit semantics. Our method facilitates the use of OWL-based software in the back-end while ontology curators may continue to develop ontologies with an OBO-style front-end.

The ontology of biological sequences

BACKGROUND

Biological sequences play a major role in molecular and computational biology. They are studied as information-bearing entities that make up DNA, RNA or proteins. The Sequence Ontology, which is part of the OBO Foundry, contains descriptions and definitions of sequences and their properties. Yet the most basic question about sequences remains unanswered: what kind of entity is a biological sequence? An answer to this question benefits formal ontologies that use the notion of biological sequences and analyses in computational biology alike.

RESULTS

We provide both an ontological analysis of biological sequences and a formal representation that can be used in knowledge-based applications and other ontologies. We distinguish three distinct kinds of entities that can be referred to as "biological sequence": chains of molecules, syntactic representations such as those in biological databases, and the abstract information-bearing entities. For use in knowledge-based applications and inclusion in biomedical ontologies, we implemented the developed axiom system for use in automated theorem proving.

CONCLUSION

Axioms are necessary to achieve the main goal of ontologies: to formally specify the meaning of terms used within a domain. The axiom system for the ontology of biological sequences is the first elaborate axiom system for an OBO Foundry ontology and can serve as starting point for the development of more formal ontologies and ultimately of knowledge-based applications.

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

MOTIVATION

Ontology 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.

RESULTS

We 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.

AVAILABILITY

The 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.

Foundations of a metadata repository for databases of registers and trials

The planning of case report forms (CRFs) in clinical trials or databases in registers is mostly an informal process starting from scratch involving domain experts, biometricians, and documentation specialists. The Telematikplattform für Medizinische Forschungsnetze, an umbrella organization for medical research in Germany, aims at supporting and improving this process with a metadata repository, covering the variables and value lists used in databases of registers and trials. The use cases for the metadata repository range from a specification of case report forms to the harmonization of variable collections, variables, and value lists through a formal review. The warehouse used for the storage of the metadata should at least fulfill the definition of part 3 "Registry metamodel and basic attributes" of ISO/IEC 11179 Information technology - Metadata registries. An implementation of the metadata repository should offer an import and export of metadata in the Operational Data Model standard of the Clinical Data Interchange Standards Consortium. It will facilitate the creation of CRFs and data models, improve the quality of CRFs and data models, support the harmonization of variables and value lists, and support the mapping of metadata and data.

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

Background

Current 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.

Results

We 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.

Conclusion

Biomedical 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.

[Carbamazepine intoxication. Complication of alcohol detoxification with combined carbamazepine and tiapride]

The advantages of alcohol detoxification treatment with combined carbamazepine and tiapride compared to benzodiazepines or clomethiazole is a lower level of sedation and lack of addictive potential. We report a case of carbamazepine intoxication with serum levels up to 19 mg/l in an otherwise healthy 45-year-old alcohol-dependent male after treatment with 600 mg carbamazepine and 600 mg tiapride per day. Medication was discontinued immediately and a purgative was administered. We were able to combat the intoxication but the assumed good tolerance of the combined treatment with carbamazepine and tiapride for alcohol detoxification still has to be proven.

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 community's 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.

Standardized terminology for clinical trial protocols based on top-level ontological categories

This paper describes a new method for the ontologically based standardization of concepts with regard to the quality assurance of clinical trial protocols. We developed a data dictionary for medical and trial-specific terms in which concepts and relations are defined context-dependently. The data dictionary is provided to different medical research networks by means of the software tool Onto-Builder via the internet. The data dictionary is based on domain-specific ontologies and the top-level ontology of GOL. The concepts and relations described in the data dictionary are represented in natural language, semi-formally or formally according to their use.