Tania Tudorache

BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications

The National Center for Biomedical Ontology (NCBO) is one of the National Centers for Biomedical Computing funded under the NIH Roadmap Initiative. Contributing to the national computing infrastructure, NCBO has developed BioPortal, a web portal that provides access to a library of biomedical ontologies and terminologies (http://bioportal.bioontology.org) via the NCBO Web services. BioPortal enables community participation in the evaluation and evolution of ontology content by providing features to add mappings between terms, to add comments linked to specific ontology terms and to provide ontology reviews. The NCBO Web services (http://www.bioontology.org/wiki/index.php/NCBO_REST_services) enable this functionality and provide a uniform mechanism to access ontologies from a variety of knowledge representation formats, such as Web Ontology Language (OWL) and Open Biological and Biomedical Ontologies (OBO) format. The Web services provide multi-layered access to the ontology content, from getting all terms in an ontology to retrieving metadata about a term. Users can easily incorporate the NCBO Web services into software applications to generate semantically aware applications and to facilitate structured data collection.

Supporting Collaborative Ontology Development in Protégé

Ontologies are becoming so large in their coverage that no single person or a small group of people can develop them effectively and ontology development becomes a community-based enterprise. In this paper, we discuss requirements for supporting collaborative ontology development and present Collaborative Protege--a tool that supports many of these requirements, such as discussions integrated with ontology-editing process, chats, and annotations of changes and ontology components. We have evaluated Collaborative Protege in the context of ontology development in an ongoing large-scale biomedical project that actively uses ontologies at the VA Palo Alto Healthcare System. Users have found the new tool effective as an environment for carrying out discussions and for recording references for the information sources and design rationale.

WebProtégé: A collaborative ontology editor and knowledge acquisition tool for the Web

In this paper, we present WebProtégé-a lightweight ontology editor and knowledge acquisition tool for the Web. With the wide adoption of Web 2.0 platforms and the gradual adoption of ontologies and Semantic Web technologies in the real world, we need ontology-development tools that are better suited for the novel ways of interacting, constructing and consuming knowledge. Users today take Web-based content creation and online collaboration for granted. WebProtégé integrates these features as part of the ontology development process itself. We tried to lower the entry barrier to ontology development by providing a tool that is accessible from any Web browser, has extensive support for collaboration, and a highly customizable and pluggable user interface that can be adapted to any level of user expertise. The declarative user interface enabled us to create custom knowledge-acquisition forms tailored for domain experts. We built WebProtégé using the existing Protégé infrastructure, which supports collaboration on the back end side, and the Google Web Toolkit for the front end. The generic and extensible infrastructure allowed us to easily deploy WebProtégé in production settings for several projects. We present the main features of WebProtégé and its architecture and describe briefly some of its uses for real-world projects. WebProtégé is free and open source. An online demo is available at http://webprotege.stanford.edu.

A Generic Ontology for Collaborative Ontology-Development Workflows

As knowledge engineering moves to the Semantic Web, ontologies become dynamic products of collaborative development rather than artifacts produced in a closed environment of a single research group. However, the projects differ--sometimes significantly--in the way the community members can contribute, the different roles they play, the mechanisms they use to carry out discussions and to achieve consensus. We are currently developing a flexible mechanism to support a wide range of collaborative workflows in the Protege environment. In this paper, we analyze workflows for several active projects, and describe the properties of these workflows. We discuss an ontology that we developed to represent different aspects of workflows for collaborative ontology development. This ontology is a key component of the customizable workflow support in Protege. We evaluate the coverage and flexibility of this ontology by using it to represent formally two different collaborative workflows described in the literature, Diligent and BiomedGT. This evaluation demonstrates that our workflow ontology is sufficiently flexible to represent these very different workflows.

Will semantic web technologies work for the development of ICD-11?

The World Health Organization is beginning to use Semantic Web technologies in the development of the 11th revision of the International Classification of Diseases (ICD-11). Health officials use ICD in all United Nations member countries to compile basic health statistics, to monitor health-related spending, and to inform policy makers. While previous revisions of ICD encoded minimal information about a disease, and were mainly published as books and tabulation lists, the creators of ICD-11 envision that it will become a multipurpose and coherent classification ready for electronic health records. Most important, they plan to have ICD-11 applied for a much broader variety of uses than previous revisions. The new requirements entail significant changes in the way we represent disease information, as well as in the technologies and processes that we use to acquire the new content. In this paper, we describe the previous processes and technologies used for developing ICD. We then describe the requirements for the new development process and present the SemanticWeb technologies that we use for ICD-11. We outline the experiences of the domain experts using the software system that we implemented using Semantic Web technologies. We then discuss the benefits and challenges in following this approach and conclude with lessons learned from this experience.

An analysis of collaborative patterns in large-scale ontology development projects

Today, distributed teams collaboratively create and maintain more and more ontologies. To support this type of ontology development, software engineers are introducing a new generation of tools. However, we know relatively little about how existing large-scale collaborative ontology development works and what user workflows the tools must support. In this paper, we analyze our experience in supporting several such projects. We describe a visual and interactive project-management tool that we have developed, which helps ontology developers explore historical ontology change and discussion data. We present the results of qualitative and quantitative studies of the collaborative activity associated with three large-scale ontology-development projects. Based on the analysis, we conclude that domain and ontology experts have different patterns of ontology editing behavior, which has important implications for ontology-development tools.

Ontology development for the masses: creating ICD-11 in WebProtégé

The World Health Organization is currently developing the 11th revision of the International Classification of Diseases (ICD-11). ICD is the standard diagnostic classification used in health care all over the world. In contrast to previous ICD revisions that did not have a formal representation and were mainly available as printed books, ICD-11 uses OWL for the formal representation of its content. In this paper, we report on our work to support the collaborative development of ICD-11 in WebProtege--a web-based ontology browser and editor. WebProtege integrates collaboration features directly into the editing process. We report on the results of the evaluation that we performed during a two-week meeting with the ICD editors in Geneva. We performed the evaluation in the context of the editors learning to use WebProtege to start the ICD-11 development. Participants in the evaluation were optimistic that collaborative development will work in this context, but have raised a number of critical issues.

How ontologies are made: Studying the hidden social dynamics behind collaborative ontology engineering projects

Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

Commentary: State of the art and open challenges in community-driven knowledge curation

In the past decade, ontologies have become central to the construction of intelligent decision-support systems, simulation systems, information-retrieval systems, and natural-language systems [1,2]. With the adoption of ontologies, especially by the broad biomedical community, the further development of ontologies and knowledge bases has evolved into a community-driven process [3]. This resulted in an increased number of knowledge bases published openly on the Web. Ontologies and knowledge bases are now authored and curated by more domain and knowledge experts than ever before. To ensure a high quality of the community-generated content, a well-defined curation process has to become a prominent and integral part of the life cycle of biomedical knowledge artefacts. Several large biomedical projects are trying to apply the ‘‘wisdom of the crowds’’ model for building and curating their knowledge content. This model is already familiar to most experts (e.g., Web 2.0) and has already proved successful in large community projects in other domains (e.g., the Open Source movement). The emergence of different types of collaborative environments, such as Wikis, content management systems, and collaborative ontology editors, enables novel ways of curating knowledge, hence transforming the workflow from being curator-centred to being community-driven. Such systems provide the means for communities of experts in different fields to create, share and reuse knowledge collaboratively. Their goal is to foster long term expansion and maximisation of knowledge curation, extraction and reasoning, by creating live knowledge bases within their specific domains. Based on the immediate goal, there are, in principle, two major types of systems: (i) knowledge curation platforms that focus on externalising knowledge for human consumption and where ontologies are either the foundational support or a byproduct of the curation process; and (ii) ontology curation environments focused explicitly on the collaborative creation and refinement of ontologies, and thus on crystallising knowledge for machine consumption. Independently of the type of platform, there are a series of critical aspects that prevail and that are, usually, the source of

WebProtégé: A Collaborative Web Based Platform for Editing Biomedical Ontologies

UNLABELLED WebProtégé is an open-source Web application for editing OWL 2 ontologies. It contains several features to aid collaboration, including support for the discussion of issues, change notification and revision-based change tracking. WebProtégé also features a simple user interface, which is geared towards editing the kinds of class descriptions and annotations that are prevalent throughout biomedical ontologies. Moreover, it is possible to configure the user interface using views that are optimized for editing Open Biomedical Ontology (OBO) class descriptions and metadata. Some of these views are shown in the Supplementary Material and can be seen in WebProtégé itself by configuring the project as an OBO project. AVAILABILITY AND IMPLEMENTATION WebProtégé is freely available for use on the Web at http://webprotege.stanford.edu. It is implemented in Java and JavaScript using the OWL API and the Google Web Toolkit. All major browsers are supported. For users who do not wish to host their ontologies on the Stanford servers, WebProtégé is available as a Web app that can be run locally using a Servlet container such as Tomcat. Binaries, source code and documentation are available under an open-source license at http://protegewiki.stanford.edu/wiki/WebProtege.