A Linked Open Data-Based Terminology to Describe Libre/Free and Open-source Software: Incremental Development Study.

BACKGROUND: There is a variety of libre/free and open-source software (LIFOSS) products for medicine and health care. To support health care and IT professionals select an appropriate software product for given tasks, several comparison studies and web platforms, such as Medfloss.org, are available. However, due to the lack of a uniform terminology for health informatics, ambiguous or imprecise terms are used to describe the functionalities of LIFOSS. This makes comparisons of LIFOSS difficult and may lead to inappropriate software selection decisions. Using Linked Open Data (LOD) promises to address these challenges. OBJECTIVE: We describe LIFOSS systematically with the help of the underlying Health Information Technology Ontology (HITO). We publish HITO and HITO-based software product descriptions using LOD to obtain the following benefits: (1) linking and reusing existing terminologies and (2) using Semantic Web tools for viewing and querying the LIFOSS data on the World Wide Web. METHODS: HITO was incrementally developed and implemented. First, classes for the description of software products in health IT evaluation studies were identified. Second, requirements for describing LIFOSS were elicited by interviewing domain experts. Third, to describe domain-specific functionalities of software products, existing catalogues of features and enterprise functions were analyzed and integrated into the HITO knowledge base. As a proof of concept, HITO was used to describe 25 LIFOSS products. RESULTS: HITO provides a defined set of classes and their relationships to describe LIFOSS in medicine and health care. With the help of linked or integrated catalogues for languages, programming languages, licenses, features, and enterprise functions, the functionalities of LIFOSS can be precisely described and compared. We publish HITO and the LIFOSS descriptions as LOD; they can be queried and viewed using different Semantic Web tools, such as Resource Description Framework (RDF) browsers, SPARQL Protocol and RDF Query Language (SPARQL) queries, and faceted searches. The advantages of providing HITO as LOD are demonstrated by practical examples. CONCLUSIONS: HITO is a building block to achieving unambiguous communication among health IT professionals and researchers. Providing LIFOSS product information as LOD enables barrier-free and easy access to data that are often hidden in user manuals of software products or are not available at all. Efforts to establish a unique terminology of medical and health informatics should be further supported and continued.

SNIK Quiz: A Multiple Choice Game About Information Management in Hospitals.

SNIK is a knowledge base about the management of health information systems generated by extracting Linked Data from textbooks and other sources. SNIK describes functions, roles executing these functions, and entity types, the information used or updated by these functions. We present SNIK Quiz, a browser game in which students answer multiple-choice questions about information management in hospitals based on SNIK. The questions are semi-automatically generated using templates in order to train basic facts, more complex patterns, and connections between textbooks encoded in SNIK.

Towards Precise Descriptions of Medical Free/Libre and Open Source Software.

The web portal Medfloss.org lists over 360 medical free/libre and open source software (MEDFLOSS) projects. These projects are described with the help of a self-developed nomenclature. Due to inconsistencies, the nomenclature shall be replaced by HITO, the Health IT Ontology. HITO is developed iteratively based on different use cases. This paper aims to describe methods and results of the second HITO use case in which HITO is extended to improve the description, retrieval and comparisons of MEDFLOSS projects on Medfloss.org. We use a mixed-methods approach to add concepts and relationships to describe MEDFLOSS precisely. The resulting HITO version stresses functional descriptions based on features and supported enterprise functions, rather than just describing technical characteristics. However, describing a larger number of MEDFLOSS projects requires the commitment of the community.

Open and Linkable Knowledge About Management of Health Information Systems.

Given a care delivery organization, its health information system can be defined as the part of the organization that processes and stores data, information, and knowledge. There is an enormous number of frameworks, textbooks and articles that describe the scope of health information system management from the perspective of medical informatics. Transforming this knowledge to Linked Open Data results in a structured data representation that is accessible for both humans and machines, the Semantic Network of Information Management in Hospitals (SNIK). We present interfaces that are useful for researchers, practitioners and students, depending on their objectives and their Semantic Web skills.

The SNIK Graph: Visualization of a Medical Informatics Ontology.

SNIK, a medical informatics ontology, combines knowledge from different literature sources dealing with the management of hospital information systems (HIS). Concepts and relations were extracted from literature, modeled as an ontology and visualized as a graph on a website. We demonstrate the potential of the graph visualization for tuitional scenarios. SNIK complements teaching and learning with conventional literature by concentrating knowledge that is scattered over different pieces of text around one node of a graph.

Technical Environment for Developing the SNIK Ontology of Information Management in Hospitals.

The SNIK project converts textbooks about information management in hospitals to a domain ontology that provides a shared vocabulary for institutions to model and integrate processes, data and infrastructure. To accommodate user groups with different requirements and technical backgrounds, and to support incremental and cooperative development, we create a system architecture to publish, visualize, browse and query the ontology, as well as to evaluate and improve the data quality.