Showing papers on "Semantic interoperability published in 2012"

The meaningful use of big data: four perspectives -- four challenges

Abstract: Twenty-five Semantic Web and Database researchers met at the 2011 STI Semantic Summit in Riga, Latvia July 6-8, 2011[1] to discuss the opportunities and challenges posed by Big Data for the Semantic Web, Semantic Technologies, and Database communities. The unanimous conclusion was that the greatest shared challenge was not only engineering Big Data, but also doing so meaningfully. The following are four expressions of that challenge from different perspectives.

E-Government Interoperability: Interaction of Policy, Management, and Technology Dimensions

Abstract: E-Government continues to be recognized as a key strategy for improving government services and the effectiveness of public policies and programs. A key component of e-government initiatives is the ability of multiple government and nongovernment organizations to share and integrate information across their traditional organizational boundaries. E-Government interoperability represents a set of multidimensional, complementary, and dynamic capabilities needed among these networks of organizations in order to achieve successful information sharing. However, this view is complex and provides both researchers and practitioners with the challenge of understanding and developing multiple and very diverse interoperability capabilities. Researchers and practitioners alike are investing in efforts to build that understanding and to create new capability for coordinated action. Drawing on theories and research in the fields of enterprise architecture, capability maturity, information sharing, and system interoperability, the framework presented here provides unique value in both regards.

Model interoperability in building information modelling

Abstract: The exchange of design models in the design and construction industry is evolving away from 2-dimensional computer-aided design (CAD) and paper towards semantically-rich 3-dimensional digital models. This approach, known as Building Information Modelling (BIM), is anticipated to become the primary means of information exchange between the various parties involved in construction projects. From a technical perspective, the domain represents an interesting study in model-based interoperability, since the models are large and complex, and the industry is one in which collaboration is a vital part of business. In this paper, we present our experiences with issues of model-based interoperability in exchanging building information models between various tools, and in implementing tools which consume BIM models, particularly using the industry standard IFC data modelling format. We report on the successes and challenges in these endeavours, as the industry endeavours to move further towards fully digitised information exchange.

Geospatial semantics and linked spatiotemporal data --Past, present, and future

Abstract: The Geosciences and Geography are not just yet another application area for semantic technologies. The vast heterogeneity of the involved disciplines ranging from the natural sciences to the social sciences introduces new challenges in terms of interoperability. Moreover, the inherent spatial and temporal information components also require distinct semantic approaches. For these reasons, geospatial semantics, geo-ontologies, and semantic interoperability have been active research areas over the last 20 years. The geospatial semantics community has been among the early adopters of the Semantic Web, contributing methods, ontologies, use cases, and datasets. Today, geographic information is a crucial part of many central hubs on the Linked Data Web. In this editorial, we outline the research field of geospatial semantics, highlight major research directions and trends, and glance at future challenges. We hope that this text will be valuable for geoscientists interested in semantics research as well as knowledge engineers interested in spatiotemporal data.

Seamless Integration of Heterogeneous Devices and Access Control in Smart Homes

Abstract: The recent trend of ubiquitous access to embedded physical devices over the Internet as well as increasing penetration of wireless protocols such as ZigBee has raised attention to smart homes. These systems consist of sensors, devices and smart appliances that can be monitored and controlled remotely by human users and cloud services. However, the lack of a de facto communication standard for smart homes creates a barrier against the interoperability of devices from different vendors. We address this challenge by proposing a holistic, extensible software architecture that seamlessly integrates heterogeneous protocol- and vendor-specific devices and services, while making these services securely available over the Internet. Our architecture is developed on top of the OSGi framework and incorporates a semantic model of a smart home system. As a result, we achieve semantic interoperability -- the ability to integrate new applications and drivers into the deployed system during runtime. Furthermore, we integrate a new access control model for specific smart home scenarios. As a proof of our concept, we demonstrate the seamless semantic discovery of home devices at runtime by integrating several protocols including X10, Insteon, ZigBee and UPnP into a real test. Using smart phones and cloud services together with our home gateway implementation, we further demonstrate the ease of integration of new applications and drivers.

The knowledge grid : toward cyber-physical society

Abstract: The Knowledge Grid is an intelligent and sustainable interconnection environment that consists of autonomous individuals, self-organized semantic communities, adaptive networking mechanisms, evolving semantic link networks keeping meaningful connection between individuals, flows for dynamic resource sharing, and mechanisms supporting effective resource management and providing appropriate knowledge services for learning, innovation, teamwork, problem solving, and decision making. This book presents its methodology, theory, models and applications systematically for the first time. Its second edition fulfills the ideal of the Knowledge Grid by increasing many up-to-date new contents, including: the systematic method of semantic link network that supports uncertainty management, discovery of semantic links and semantic communities, and autonomous semantic data model; semantic peer-to-peer infrastructures for efficient knowledge sharing; and, a new centrality measure of network and its application in e-science. This new edition will undoubtedly provide refreshing materials for researchers, academics, practitioners and students.

A Minimum Data Set for Sharing Biobank Samples, Information, and Data: MIABIS.

Abstract: Numerous successful scientific results have emerged from projects using shared biobanked samples and data. In order to facilitate the discovery of underutilized biobank samples, it would be helpful if a global biobank register containing descriptive information about the samples existed. But first, for shared data to be comparable, it needs to be harmonized. In compliance with the aim of BBMRI (Biobanking and Biomolecular Resources Research Infrastructure), to harmonize biobanking across Europe, and the conclusion that the move towards a universal information infrastructure for biobanking is directly connected to the issues of semantic interoperability through standardized message formats and controlled terminologies, we have developed an updated version of the minimum data set for biobanks and studies using human biospecimens. The data set called MIABIS (Minimum Information About BIobank data Sharing) consists of 52 attributes describing a biobank's content. The aim is to facilitate data discovery throug...

S-match: an open source framework for matching lightweight ontologies

Abstract: Achieving automatic interoperability among systems with diverse data structures and languages expressing different viewpoints is a goal that has been difficult to accomplish. This paper describes S-Match, an open source semantic matching framework that tackles the semantic interoperability problem by transforming several data structures such as business catalogs, web directories, conceptual models and web services descriptions into lightweight ontologies and establishing semantic correspondences between them. The framework is the first open source semantic matching project that includes three different algorithms tailored for specific domains and provides an extensible API for developing new algorithms, including possibility to plug-in specific background knowledge according to the characteristics of each application domain.

The Digital Earth as knowledge engine

Abstract: The Digital Earth [13] aims at developing a digital representation of the planet. It is motivated by the need for integrating and interlinking vast geo-referenced, multi-thematic, and multi-perspective knowledge archives that cut through domain boundaries. Complex scientific questions cannot be answered from within one domain alone but span over multiple scientific disciplines. For instance, studying disease dynamics for prediction and policy making requires data and models from a diverse body of science ranging from medical science and epidemiology over geography and economics to mining the social Web. The naive assumption that such problems can simply be addressed by more data with a higher spatial, temporal, and thematic resolution fails as long as this more on data is not supported by more knowledge on how to combine and interpret the data. This makes semantic interoperability a core research topic of data-intensive science. While the Digital Earth vision includes processing services, it is, at its very core, a data archive and infrastructure. We propose to redefine the Digital Earth as a knowledge engine and discuss what the Semantic Web has to offer in this context and to Big Data in general.

Semantic interoperability in standardized electronic health record databases

Abstract: Different clinics and hospitals have their own information systems to maintain patient data. This hinders the exchange of data among systems (and organizations). Hence there is a need to provide standards for data exchange. In digitized form, the individual patient's medical record can be stored, retrieved, and shared over a network through enhancement in information technology. Thus, electronic health records (EHRs) should be standardized, incorporating semantic interoperability. A subsequent step requires that healthcare professionals and patients get involved in using the EHRs, with the help of technological developments. This study aims to provide different approaches in understanding some current and challenging concepts in health informatics. Successful handling of these challenges will lead to improved quality in healthcare by reducing medical errors, decreasing costs, and enhancing patient care. The study is focused on the following goals: (1) understanding the role of EHRs; (2) understanding the need for standardization to improve quality; (3) establishing interoperability in maintaining EHRs; (4) examining a framework for standardization and interoperability (the openEHR architecture; (5) identifying the role of archetypes for knowledge-based systems; and (6) understanding the difficulties in querying HER data.

Interoperability in the e-Government Context

Abstract: : Achieving interoperability in an e-government context is difficult. Although the benefits of enabling e-government systems to interoperate are significant, repeated failures to build working systems provide evidence that the tasks necessary to gain those benefits are poorly understood. Many governments have addressed interoperability as primarily a technical issue. However, to address the entirety of the interoperability challenge, development teams must also consider nontechnical factors that influence their efforts to meet interoperability goals. This report describes a proposed model through which to understand interoperability in the e-government context. With this model, system developers should characterize interoperability in six dimensions: Developers need to analyze e-government interoperability requirements at the technical, semantic, and organizational levels, but they should also consider the legal, political, and sociocultural issues with which the e-government system must also interoperate. This report explains some of the challenges associated with achieving interoperability in e-government systems and presents some guidance on how to address interoperability requirements, with the goal of making both policy makers and system developers aware of the depth and breadth of these challenges.

Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources

Abstract: One difficulty in integrating geospatial data sets from different sources is variation in feature classification and semantic content of the data. One step towards achieving beneficial semantic interoperability is to assess the semantic similarity among objects that are categorised within data sets. This article focuses on measuring semantic and structural similarities between categories of formal data, such as Ordnance Survey OS cartographic data, and volunteered geographic information VGI, such as that sourced from OpenStreetMap OSM, with the intention of assessing possible integration. The model involves ‘tokenisation’ to search for common roots of words, and the feature classifications have been modelled as an XML schema labelled rooted tree for hierarchical analysis. The semantic similarity was measured using the WordNet::Similarity package, while the structural similarities between sub-trees of the source and target schemas have also been considered. Along with dictionary and structural matching, the data type of the category itself is a comparison variable. The overall similarity is based on a weighted combination of these three measures. The results reveal that the use of a generic similarity matching system leads to poor agreement between the semantics of OS and OSM data sets. It is concluded that a more rigorous peer-to-peer assessment of VGI data, increasing numbers and transparency of contributors, the initiation of more programs of quality testing and the development of more directed ontologies can improve spatial data integration.

OWL-S Based Semantic Cloud Service Broker

Abstract: Cloud broker is an entity that manages the use, performance and delivery of cloud services and negotiates relationships between cloud providers and cloud consumers. In real life scenarios, automated cloud service brokering is often challenging because the service descriptions may involve complex constraints and require flexible semantic matching. Furthermore, cloud providers often use non-standard formats leading to semantic interoperability issues. In this paper, we formulate cloud service brokering under a service oriented framework, and propose a novel OWL-S based semantic cloud service discovery and selection system. The proposed system supports dynamic semantic matching of cloud services described with complex constraints. We consider a practical cloud service brokering scenario, and show with detailed illustration that our system is promising for real-life applications.

Semantic Interoperability on the Web of Things: The Semantic Smart Gateway Framework

Abstract: The aim of this paper is to present authors' proposal regarding semantic interoperability for interconnected and semantically coordinated smart entities in a Web of Things More specific, the paper presents a use case scenario and requirements related to the semantic registration, coordination and retrieval of smart entities Motivated by these, the paper accentuates the need for, and emphasizes, a framework of Semantic Smart Gateways (SSGF) in the Semantic Web of Things (SWoT), proposing an ontology learning and an ontology alignment method respectively

Linking to linguistic data categories in ISOcat

Abstract: ISO Technical Committee 37, Terminology and other language and content resources established an ISO 12620:2009 based Data Category Registry (DCR), called ISOcat (see http://www.isocat.org), to foster semantic interoperability of linguistic resources. This registry follows a grass roots approach, which means that any linguist can add the data categories (s)he needs. Standardized subsets of these data categories are created by a standardization procedure involving groups of international experts who are members of various Thematic Domain Groups (TDGs) and of the DCR Board. However, the goal of improving semantic interoperability can only be met if the data categories are reused by a wide variety of linguistic resource types. A resource indicates its usage of data categories by linking to them. ISO 12620:2009 specifies a small DC Reference XML vocabulary to annotate XML documents with links to data categories. The link is established by an URI, which servers as the Persistent IDentifier (PID) of a data category. Any XML document can now refer to data categories to explicate the semantics of elements, attributes and values. This paper discusses the efforts to mimic the same approach for RDF-based resources. It also introduces the RDF quad store based Relation Registry RELcat, which enables ontological relationships between data categories not supported by ISOcat and thus adds an extra level of linguistic knowledge.

Intelligence in interoperability with AIDA

Abstract: Healthcare systems have to be addressed in terms of a wide variety of heterogeneous, distributed and ubiquitous systems speaking different languages, integrating medical equipments and customized by different entities, which in turn were set by different people aiming at different goals. Demands of information within the healthcare sector range from clinically valuable patient-specific information to a variety of aggregation levels for follow-up and statistical and/or quantifiable reporting. The main goal is to gathering this information and present it in a readable way to physicians. In this work we show how to achieve interoperability in healthcare institutions using AIDA, an interoperability platform developed by researchers from the University of Minho and being used in some major Portuguese hospitals.

A reference model for sustainable interoperability in networked enterprises: towards the foundation of EI science base

Abstract: Enterprise interoperability EI is a well-established area of applied research studying the problems related with the lack of systems and applications' interoperability in organisations, and proposing novel solutions for EI problems. However, in spite of research efforts to date, the proper scientific needs for EI remain elusive. This lack prevents the generalisation and full reuse of the methods and tools that have been developed so far, and threatens the sustainability of EI. After presenting the motivations for a science-based EI, this article analyses neighbouring scientific domains in which features of interoperability can be identified and evaluated as a benchmark for developing a foundation of EI. It then proposes a conceptual reference model for the principal layers of interoperability practices, including the new practice of sustainability in interoperability on networked enterprises. Drawing upon concepts from complex-systems science, it suggests a CAS-based sustainable interoperability framework CAS-SIF for use in dynamic networks.

Interoperable support for collaborative, mobile, and accessible health care

Abstract: E-Health systems, through their use of Internet and wireless technologies, offer the possibility of near real-time data integration to support the delivery and management of health care. In practice, the wide range of choice in technologies, vendors, protocols, formats, and information representations can make even simple exchanges of information between systems problematic. Much of the focus on healthcare interoperability has been on resolving interoperability issues of system to system information exchanges. But issues around people to people interactions and people to system interactions are just as important to address from an interoperability point of view. In this paper, we identify interoperability deficiencies in collaborative care delivery and develop a methodology in two parts. In the first part, an ontology is developed to represent collaborative care delivery. In the second part, the ontology is used to design an architecture for interoperable clinical information system design. We then use a case study in palliative care to provide a proof of concept of the methodology. The case study provides an inventory of the interoperability requirements for palliative care and a perspective on the design and implementation of a people oriented clinical information system that supports collaborative health care delivery in palliative care.

Interoperability of Corpora and Annotations

Abstract: This paper describes the application of OWL and RDF to address the interoperability of linguistic corpora and linguistic annotations within such corpora. Interoperability of linguistic corpora involves two aspects: Structural interoperability (annotations of different origin are represented using the same formalism) and conceptual interoperability (annotations of different origin are linked to a common vocabulary).

Toward Semantic Interoperability of Electronic Health Records

Abstract: Although the goal of achieving semantic interoperability of electronic health records (EHRs) is pursued by many researchers, it has not been accomplished yet. In this paper, we present a proposal that smoothes out the way toward the achievement of that goal. In particular, our study focuses on medical diagnoses statements. In summary, the main contributions of our ontology-based proposal are the following: first, it includes a canonical ontology whose EHR-related terms focus on semantic aspects. As a result, their descriptions are independent of languages and technology aspects used in different organizations to represent EHRs. Moreover, those terms are related to their corresponding codes in well-known medical terminologies. Second, it deals with modules that allow obtaining rich ontological representations of EHR information managed by proprietary models of health information systems. The features of one specific module are shown as reference. Third, it considers the necessary mapping axioms between ontological terms enhanced with so-called path mappings. This feature smoothes out structural differences between heterogeneous EHR representations, allowing proper alignment of information.

Model driven design and data integration in semantic web information systems

Abstract: The Web is quickly evolving in many ways. It has evolved from a Web of documents into a Web of applications in which a growing number of designers offer new and interactive Web applications with people all over the world. However, application design and implementation remain complex, error-prone and laborious. In parallel there is also an evolution from a Web of documents into a Web of `knowledge' as a growing number of data owners are sharing their data sources with a growing audience. This brings the potential new applications for these data sources, including scenarios in which these datasets are reused and integrated with other existing and new data sources. However, the heterogeneity of these data sources in syntax, semantics and structure represents a great challenge for application designers. The Semantic Web is a collection of standards and technologies that offer solutions for at least the syntactic and some structural issues. If offers semantic freedom and flexibility, but this leaves the issue of semantic interoperability. In this thesis we present Hera-S, an evolution of the Model Driven Web Engineering (MDWE) method Hera. MDWEs allow designers to create data centric applications using models instead of programming. Hera-S especially targets Semantic Web sources and provides a flexible method for designing personalized adaptive Web applications. Hera-S defines several models that together define the target Web application. Moreover we implemented a framework called Hydragen, which is able to execute the Hera-S models to run the desired Web application. Hera-S' core is the Application Model (AM) in which the main logic of the application is defined, i.e. defining the groups of data elements that form logical units or subunits, the personalization conditions, and the relationships between the units. Hera-S also uses a so-called Domain Model (DM) that describes the content and its structure. However, this DM is not Hera-S specific, but instead allows any Semantic Web source representation as its DM, as long as its content can be queried by the standardized Semantic Web query language SPARQL. The same holds for the User Model (UM). The UM can be used for personalization conditions, but also as a source of user-related content if necessary. In fact, the difference between DM and UM is conceptual as their implementation within Hydragen is the same. Hera-S also defines a presentation model (PM) which defines presentation details of elements like order and style. In order to help designers with building their Web applications we have introduced a toolset, Hera Studio, which allows to build the different models graphically. Hera Studio also provides some additional functionality like model checking and deployment of the models in Hydragen. Both Hera-S and its implementation Hydragen are designed to be flexible regarding the user of models. In order to achieve this Hydragen is a stateless engine that queries for relevant information from the models at every page request. This allows the models and data to be changed in the datastore during runtime. We show that one way to exploit this flexibility is by applying aspect-orientation to the AM. Aspect-orientation allows us to dynamically inject functionality that pervades the entire application. Another way to exploit Hera-S' flexibility is in reusing specialized components, e.g. for presentation generation. We present a configuration of Hydragen in which we replace our native presentation generation functionality by the AMACONT engine. AMACONT provides more extensive multi-level presentation generation and adaptation capabilities as well aspect-orientation and a form of semantic based adaptation. Hera-S was designed to allow the (re-)use of any (Semantic) Web datasource. It even opens up the possibility for data integration at the back end, by using an extendible storage layer in our database of choice Sesame. However, even though theoretically possible it still leaves much of the actual data integration issue. As this is a recurring issue in many domains, a broader challenge than for Hera-S design only, we decided to look at this issue in isolation. We present a framework called Relco which provides a language to express data transformation operations as well as a collection of techniques that can be used to (semi-)automatically find relationships between concepts in different ontologies. This is done with a combination of syntactic, semantic and collaboration techniques, which together provide strong clues for which concepts are most likely related. In order to prove the applicability of Relco we explore five application scenarios in different domains for which data integration is a central aspect. This includes a cultural heritage portal, Explorer, for which data from several datasources was integrated and was made available by a mapview, a timeline and a graph view. Explorer also allows users to provide metadata for objects via a tagging mechanism. Another application is SenSee: an electronic TV-guide and recommender. TV-guide data was integrated and enriched with semantically structured data from several sources. Recommendations are computed by exploiting the underlying semantic structure. ViTa was a project in which several techniques for tagging and searching educational videos were evaluated. This includes scenarios in which user tags are related with an ontology, or other tags, using the Relco framework. The MobiLife project targeted the facilitation of a new generation of mobile applications that would use context-based personalization. This can be done using a context-based user profiling platform that can also be used for user model data exchange between mobile applications using technologies like Relco. The final application scenario that is shown is from the GRAPPLE project which targeted the integration of adaptive technology into current learning management systems. A large part of this integration is achieved by using a user modeling component framework in which any application can store user model information, but which can also be used for the exchange of user model data.

The SemSets model for ad-hoc semantic list search

Abstract: The amount of semantic data on the web has been growing rapidly in recent years. One of the key challenges triggered by this growth is the ad-hoc querying, i.e., the ability to retrieve answers from semantic resources using natural language queries. This facilitates interaction with semantic resources for the users so they can benefit from the knowledge covered by semantic data without the complexities of semantic query languages. In this paper, we focus on semantic queries, where the aim is to retrieve objects belonging to a set of semantically related entities. An example of such an ad-hoc type query is "Apollo astronauts who walked on the Moon". In order to address the task, we propose the SemSets retrieval model that exploits and combines traditional document-based information retrieval, link structure of the semantic data and entity membership in semantic sets, in order to provide the answers. The novelty of the approach lies in the utilization of semantic sets, i.e., groups of semantically related entities. We propose two approaches to identify such semantic sets from the knowledge bases; the first one requires involvement of an expert user knowledgeable of the data set structure, the second one is fully automatic and provides results that are comparable with those delivered by the expert users. As demonstrated in the experimental evaluation, the proposed model has the state-of-the-art performance on the SemSearch2011 data set, which has been designed especially for the semantic list search evaluation.