Leonardo Lezcano

Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules

Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach.

Associating Clinical Archetypes Through UMLS Metathesaurus Term Clusters

Clinical archetypes are modular definitions of clinical data, expressed using standard or open constraint-based data models as the CEN EN13606 and openEHR. There is an increasing archetype specification activity that raises the need for techniques to associate archetypes to support better management and user navigation in archetype repositories. This paper reports on a computational technique to generate tentative archetype associations by mapping them through term clusters obtained from the UMLS Metathesaurus. The terms are used to build a bipartite graph model and graph connectivity measures can be used for deriving associations.

Exploring affiliation network models as a collaborative filtering mechanism in e-learning

The online interaction of learners and tutors in activities with concrete objectives provides a valuable source of data that can be analyzed for different purposes. One of these purposes is the use of the information extracted from that interaction to aid tutors and learners in decision making about either the configuration of further learning activities or the filtering of learning resources. This article explores the use of an affiliation network model for such kind of purposes. Concretely, the use of techniques such as blockmodeling – a technique used to derive meaningful patterns of relationships in the network – and the analysis of m-slices – a technique helpful to study cohesion in relationships – are explored as tools to decide on the configuration of topics and/or learner groups. In particular, the results of the case study show that such techniques can be used to (i) filter participants for rearranging groups; (ii) rearrange topics of interest; and (iii) dynamically change the structure of a course. The techniques presented can be considered a case of collaborative filtering based on social network structure.

Social models in open learning object repositories: A simulation approach for sustainable collections

Abstract Learning object repositories (LOR) are digital collections of educational resources and/or metadata aimed at facilitating reuse of materials worldwide. In open repositories, resources are made available at no cost, representing a case of information sharing with an implicit and diffuse social context. In such settings, quality control is in many cases based in some form of community filtering that provides a reliable basis for ranking resources when repositories reach a critical mass of users. However, there have been numerous repository initiatives and projects and many of them did not reached a significant degree of actual usage and growth that made them sustainable in the long term. In consequence, finding models for sustainable collections is a key issue in repository research, and the main problem behind that is understanding the evolution of successful repositories. This in turn requires analyzing experimental models of the behavior of their users that are coherent with the available evidence on their structure and growth patters. This paper provides a partial model for such behavior based on existing reported evidence and on the examination of patterns in a large and mature repository. Agent-based simulation was chosen to allow for contrasting configurations with different parameters. Simulations were devised with the RePast framework and the resulting model implementation constitutes an initial baseline for future studies aimed at contrasting empirical data on repository usage with their community setting. The model described accounts for known user contribution patterns and it is coherent with the implicit social network structure found in an existing large LOR.

A survey on the exchange of linguistic resources: Publishing linguistic linked open data on the Web

Purpose – The purpose of this paper is to provide a literature review of the principal formats and frameworks that have been used in the last 20 years to exchange linguistic resources. It aims to give special attention to the most recent approaches to publishing linguistic linked open data on the Web.Design/methodology/approach – Research papers published since 1990 on the use of various formats, standards, frameworks and methods to exchange linguistic information were divided into two main categories: those proposing specific schemas and syntaxes to suit the requirements of a given type of linguistic data (these are referred to as offline approaches), and those adopting the linked data (LD) initiative and the semantic web technologies to support the interoperability of heterogeneous linguistic resources. For each paper, the type of linguistic resource exchanged, the framework/format used, the interoperability approach taken and the related projects were identified.Findings – The information gathered in t...

Modeling the Context of Scientific Information: Mapping VIVO and CERIF

Institutional repositories (IR) and Current Research Information Systems (CRIS) among other kinds of systems store and manage information on the context in which research activity takes place. Several models, standards and ontologies have been proposed to date as a solution to give coherent semantics to research information. These present a large degree of overlap but also present very different approaches to modeling. This paper presents a contrast of two of the more widespread models, the VIVO ontology and the CERIF standards, and provides directions for mapping them in a way that enables clients to integrate data coming from heterogeneous sources. The majority of mapping problems have risen from the representation of VIVO sub-hierarchies in CERIF as well as from the representation of CERIF attributes in VIVO.

Combining OpenEHR Archetype Definitions with SWRL Rules --- A Translation Approach

The interoperability of electronic healthcare information systems is critical for a more effective healthcare management. Several specifications and standards have been created for facilitating such interoperability at different levels. Among them, the OpenEHR initiative emphasizes the sharing of flexible specifications of healthcare information pieces in the form of archetypes. However, the OpenEHR ADL language does not provide support for rules and inference which are important pieces of clinical knowledge. This paper reports on an approach to convert ADL definitions to OWL and then attach rules to the semantic version of the archetypes. This allows for an automated means to reuse knowledge expressed in the form of rules which is also flexible and follows the same philosophy of sharing archetypes.

Semantic Integration of Sensor Data and Disaster Management Systems: The Emergency Archetype Approach

The Semantic Sensor Web (SSW) allows emergency response management (ERM) systems to consume sensor data and improve response time and effectiveness. It is also a fact that ERM must be carried out as a multiorganizational task to combine sensor data with human decisions and observations. A frequent problem in such scenarios is that current formats for data exchange do not support sensor data in a way that allows semantic interoperability between heterogeneous ERM systems. Therefore, part of the semantic richness coming from the SSW, such as the Semantic Sensor Network Ontology (SSNO), is lost when sensor data is embedded in current ERM messages. To bridge the gap, an application of the two-level paradigm to the ERM domain is proposed. The advantages of using “emergency archetypes” include semantic data integration and flexibility to represent new types of messages, without losing the support for seamless exchange between heterogeneous ERM systems. Emergency archetypes can reuse the terminologies and ontologies available in the ERM domain so that systems based on previous formats can switch to archetypes in a straightforward process. Finally, a method to attach rules to emergency archetypes is explained, allowing not only the semantic interoperability of ERM data but also of the inference knowledge that trigger alerts and support decision making.

Bridging informal tagging and formal semantics via hybrid navigation

The folksonomies resulting from user-generated tag systems feature rapid adaptability, and reflect the information needs of their supporting user communities. However, they suffer from well-known problems, such as polysemy, heteronymy and lack of recall, which have been addressed in controlled vocabularies and ontologies, which in turn follow slower but more controlled evolution processes. These differences have led to the bridging approach described in this paper, which is based on mapping tags to ontology elements. Mappings can be automatically generated or explicitly provided by user-created assertions between tags and ontology elements. The main objective is to combine existing tag navigation, such as that featured in Delicious, with related tag recommendations obtained from ontology relations, in order to provide a hybrid navigation context that benefits folksonomy browsing. The implementation of such integration, combining Delicious and the OpenCyc knowledge base, is described, along with an evaluation of its potential in improving navigation through the user-generated tag system. The results reveal that the new semantic shortcuts and the decrease in dead ends can substantially influence the collaborative bookmarking experience.

Contrasting Knowledge Organization Systems for the Description of Research Products: the Case of Overlapping in the Agricultural Domain

Abstract The use of Knowledge Organization Systems (KOS) as ontologies or terminologies for the description of scholarly contents requires a careful consideration of the domain and the KOS available. KOS in the same domain may differ in several dimensions including purpose, level of formality, structure and language. In consequence, curators of scientific data face the problem of selecting the relevant KOS, developing mappings when appropriate and deciding on their usage for annotating resources. In domains in which more than a KOS is available, curators need tools to help them in the decision making process. Due to the available heterogeneity of KOS, exploratory tools are required for an initial assessment of overlapping and differences. This paper reports on a practical experience using simple mapping analysis and mapping visualizations in the domain of agriculture. These techniques represent promising directions for the development of decision tools based on the contrast of different KOS metrics.