Semantic processing of EHR data for clinical research

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.Comment: Accepted for publication in Journal of Biomedical Informatics, 2015, preprint versio

Interoperability of Information Systems and Heterogenous Databases Using XML

Interoperabilily of information systerrrs is the most critical issue facing businesse! that need to access information from multiple idormution systems on tlifferent environments ancl diverse platforms. Interoperability has been a basic requirement for the modern information systems in a competitive and volatile business environment, particularly with the advent of distributed network system and the growing relevance of inter-network communications. Our objective in tltis paper is to develop a comprehensiveframework tofacilitate interoperability smong distributed and heterogeneous information systems and to develop prototype software to validate tlte application of XML in interoperability of infurmation systems and databases

Data DNA: The Next Generation of Statistical Metadata

Describes the components of a complete statistical metadata system and suggests ways to create and structure metadata for better access and understanding of data sets by diverse users

Integration of environmental data in BIM tool & linked building data

Environmental assessment is a critical need to ensure building sustainability. In order to enhance the sustainability of building, involved actors should be able to access and share not only information about the building but also data about products and especially their environmental assessment. Among several approaches that have been proposed to achieve that, semantic web technologies stand out from the crowd by their capabilities to share data and enhance interoperability in between the most heterogeneous systems. This paper presents the implementation of a method in which semantic web technologies and particularly Linked Data have been combined with Building Information Modelling (BIM) tools to foster building sustainability by introducing products with their environmental assessment in building data during the modelling phase. Based on Linked Building Data (LBD) vocabularies and environmental data, several ontologies have been generated in order to make both of them available as Resource Description Framework (RDF) graphs. A database access plugin has been developed and installed in a BIM tool. In that way, the LBD generated from the BIM tool contains, for each product a reference to its environmental assessment which is contained in a triplestore

Designing interoperable museum information systems

Museum collections are characterized by heterogeneity, since they usually host a plethora of objects of categories, while each of them requires different description policies and metadata standards. Moreover the museum records, which keep the history and evolution of the hosted collections, request proactive curation in order to preserve this rich and diverse information. In this paper, the architecture of an innovative museum information system, as well as its implementation details is presented. In particular the requirements and the system architecture are presented along with the problems that were encountered. The main directions of the system design are (a) to increase interoperability levels and therefore assist proactive curation and (b) to enhance navigation by the usage of handheld devices. The first direction is satisfied by the design of a rich metadata schema based on the CIDOC/CRM standard. The second direction is fulfilled by the implementation of a module, which integrates the museum database with a subsystem appropriate to support user navigation into the museum floors and rooms. The module is expressed as a navigation functionality, which is accessed through handheld devices and peripherals, such as PDAs and RFID tags. The proposed system is functional and operates into the Solomos Museum, situated in Zakynthos island, Greece

The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility

The Distributed Ontology Language (DOL) is currently being standardized within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37/SC 3. It aims at providing a unified framework for (1) ontologies formalized in heterogeneous logics, (2) modular ontologies, (3) links between ontologies, and (4) annotation of ontologies. This paper presents the current state of DOL's standardization. It focuses on use cases where distributed ontologies enable interoperability and reusability. We demonstrate relevant features of the DOL syntax and semantics and explain how these integrate into existing knowledge engineering environments.Comment: Terminology and Knowledge Engineering Conference (TKE) 2012-06-20 to 2012-06-21 Madrid, Spai

Is a Semantic Web Agent a Knowledge-Savvy Agent?

The issue of knowledge sharing has permeated the field of distributed AI and in particular, its successor, multiagent systems. Through the years, many research and engineering efforts have tackled the problem of encoding and sharing knowledge without the need for a single, centralized knowledge base. However, the emergence of modern computing paradigms such as distributed, open systems have highlighted the importance of sharing distributed and heterogeneous knowledge at a larger scale—possibly at the scale of the Internet. The very characteristics that define the Semantic Web—that is, dynamic, distributed, incomplete, and uncertain knowledge—suggest the need for autonomy in distributed software systems. Semantic Web research promises more than mere management of ontologies and data through the definition of machine-understandable languages. The openness and decentralization introduced by multiagent systems and service-oriented architectures give rise to new knowledge management models, for which we can’t make a priori assumptions about the type of interaction an agent or a service may be engaged in, and likewise about the message protocols and vocabulary used. We therefore discuss the problem of knowledge management for open multi-agent systems, and highlight a number of challenges relating to the exchange and evolution of knowledge in open environments, which pertinent to both the Semantic Web and Multi Agent System communities alike