A major part of Open Data concerns statistics such as economic and social indicators. Statistical data are structured in a multidimensional manner creating data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their statistical data on the Web. Many vocabularies have been created to enable modeling data cubes as RDF graphs, and thus creating Linked Open Statistical Data (LOSD). However, the creation of LOSD remains a demanding task mainly because of modeling challenges related either to the conceptual definition of the cube, or to the way of modeling cubes as linked data. The aim of this paper is to identify and clarify (a) modeling challenges related to the creation of LOSD and (b) approaches to address them. Towards this end, nine LOSD experts were involved in an interactive feedback collection and consensus-building process that was based on Delphi method. We anticipate that the results of this paper will contribute towards the formulation of best practices for creating LOSD, and thus facilitate combining and analyzing statistical data from diverse sources on the Web.

The increase in the volume and heterogeneity of biomedical data sources has motivated researchers to embrace Linked Data (LD) technologies to solve the ensuing integration challenges and enhance information discovery. As an integral part of the EU GRANATUM project, a Linked Biomedical Dataspace (LBDS) was developed to semantically interlink data from multiple sources and augment the design of in silico experiments for cancer chemoprevention drug discovery. The different components of the LBDS facilitate both the bioinformaticians and the biomedical researchers to publish, link, query and visually explore the heterogeneous datasets. We have extensively evaluated the usability of the entire platform. In this paper, we showcase three different workflows depicting real-world scenarios on the use of LBDS by the domain users to intuitively retrieve meaningful information from the integrated sources. We report the important lessons that we learned through the challenges encountered and our accumulated experience during the collaborative processes which would make it easier for LD practitioners to create such dataspaces in other domains. We also provide a concise set of generic recommendations to develop LD platforms useful for drug discovery.

A set of well-integrated clinical terminologies is at the core of delivering an efficient clinical trial system. The design and outcomes of a clinical trial can be improved significantly through an unambiguous and consistent set of clinical terminologies used in a participating clinical institute. However, due to lack of generalised legal and technical standards, heterogeneity exists between prominent clinical terminologies as well as within and between clinical systems at several levels, e.g., data, schema, and medical codes. This article specifically addresses the problem of integrating local or proprietary clinical terminologies with the globally defined universal concepts or terminologies. To deal with the problem of ambiguous, inconsistent, and overlapping clinical terminologies, domain and knowledge representation specialists have been repeatedly advocated the use of formal ontologies. We address two key challenges in developing an ontology-based clinical terminology (1) an ontology building methodology for clinical terminologies that are separated in global and local layers, and (2) aligning global and local clinical terminologies. We present Semantic Electronic Health Record (SEHR) ontology that covers multiple sub-domains of Healthcare and Life Sciences (HCLS) through specialisation of the upper-level Basic Formal Ontology (BFO). One of the main features of SEHR is layering and adaptation of local clinical terminologies with the upper-level BFO. Our empirical evaluation shows an agreement of clinical experts confirming SEHR's usability in clinical trials.

Electronic Health Records (EHRs) contain an increasing wealth of medical information. They have the potential to help significantly in advancing medical research, as well as improve health policies, providing society with additional benefits. However, the European healthcare information space is fragmented due to the lack of legal and technical standards, cost effective platforms, and sustainable business models. The vision of Linked2Safety is to advance clinical practice and accelerate medical research, by providing pharmaceutical companies, healthcare professionals and patients with an innovative secure semantic interoperability framework facilitating the efficient and homogenized access to anonymised distributed EHRs in an aggregate form that enables merging multiple data sources into a single analyses. In this paper a first public introduction to the project is provided along with a clear definition of the problems, and proposed architecture. Three usage scenarios are used to demonstrate the potential impact of the outcomes of the project.

Cloud computing is a promising IT paradigm which enables the Internet's evolution into a global market of collaborating services. Cloud computing semantic interoperability plays a key role in making this a reality. Towards this direction, a comprehensive and systematic survey of Cloud computing interoperability efforts by standardization groups, industry and research community is carried out. The main objective of this survey is to derive an initial set of semantic interoperability requirements to be supported by existing as well as next generation Cloud systems. Ôhe survey motivates and encourages the Cloud community to adopt a common Cloud computing interoperability framework with core dimensions the creation of a common data model and a standardized Cloud interface (API), which will constitute the base for the development of a semantically interoperable Cloud environment.

Given the rapid uptake and the great diversity of PaaS offerings, understanding semantic interoperability at the PaaS level is essential for supporting inter-Cloud cooperation, seamless information exchange and application and data portability. In this vein, this paper introduces a PaaS semantic interoperability framework (PSIF). PSIF studies, models and tries to resolve semantic interoperability conflicts raised during the deployment or the migration of an application by defining the following dimensions: Fundamental PaaS Entities, Types of Semantics, and Levels of Semantic Conflicts. In the context of this paper, the development of common PaaS models and standardized management interfaces are raised as primary requirements in this context. PaaS architectures can then be augmented with a semantic layer that would host the common models and would be the link between heterogeneous PaaS offerings.

This paper focuses on the emerging problem of semantic interoperability between heterogeneous cooperating Cloud platforms. We try to pave the way towards a Reference Architecture for Semantically Interoperable Clouds (RASIC). To this end, three fundamental and complementary computing paradigms, namely Cloud computing, Service Oriented Architectures (SOA) and lightweight semantics are used as the main building blocks. The open, generic Reference Architecture for Semantically Interoperable Clouds introduces a scalable, reusable and transferable approach for facilitating the design, deployment and execution of resource intensive SOA services on top of semantically interlinked Clouds. In order to support the development of semantically interoperable Cloud systems based on RASIC, the model of a common Cloud API is also specified.

Interoperability is one of the most challenging problems in modern cross-organizational information systems, which rely on heterogeneous information and process models. Interoperability becomes very important for e-Government information systems that support cross-organizational communication especially in a cross-border setting. The main goal in this context is to seamlessly provide integrated services to the user (citizen). In this paper we focus on Pan European e-Services and issues related with their integration. Our analysis uses basic concepts of the generic public service model of the Governance Enterprise Architecture (GEA) and of the Web Service Modeling Ontology (WSMO), to express the semantic description of the e-services. Based on the above, we present a mediation infrastructure capable of resolving semantic interoperability conflicts at a pan-European level. We provide several examples to illustrate both the need to solve such semantic conflicts and the actual solutions we propose.

The introduction of information and communication technologies (ICTs) in the field of public participation led to the emergence of electronic participation (eparticipation). The area of eparticipation is currently a rapidly evolving one. Although, a few eparticipation-related frameworks have been developed they actually aimed to address specific purposes. As a result, there is no work aiming to model the whole eparticipation domain. In this paper, a first attempt to model the domain of eparticipation is presented. For this purpose, we identify and describe the most significant aspects that characterize the eparticipation domain according to the relevant literature. In addition, we define a domain model in order to formally describe these aspects and the relationships between them. This model is illustrated using a set of Unified Modeling Language (UML) package and class diagrams.

Public administrations all over the world promote ambitious and costly e-government programmes. The required domain analysis is usually conducted on a local and ad hoc basis, due to a lack of commonly accepted domain models - in literature and practice - for the overall governance system. This paper summarizes a broad research modelling effort, which aims at developing a domain description for the overall governance system. We propose the Governance Enterprise Architecture (GEA) as a set of domain models that serve as a top-level enterprise architecture. To this point, the development includes five high-level generic process and objects models. Namely, we present the GEA mega-process model, the GEA interaction model, the GEA public policy formulation object model, the GEA service provision object model and the latest development of the GEA object model for the overall governance system.

The use of Enterprise Architectures is becoming increasingly widespread in the private sector. Borrowing insights from enterprise reference architectures developed during the last decade, IT vendors and companies belonging to specific industries are establishing reference data and process models advancing the standardisation of their businesses and creating a more integrated environment for their activities. Although public administrations share the same problem of non-standardisation, which is being magnified rapidly in a changing and demanding environment, little has been done so far in the direction of integration. This article builds a basis, shows initial directions and attempts to stimulate interest in a PA enterprise framework. Following a top-down approach and employing concepts from the fields of public administration, enterprise integration and generic process and data modeling, the outline of the ArchPad enterprise architecture for Public Administration is presented.

Automatically planning a camera viewpoint for tasks such as inspection in an active robot work-cell is a difficult problem. This paper discusses new methods for computing viewpoints which meet the feature detectability constraints of focus, field-of-view, visibility, and resolution. A theoretical outline of the method is presented, followed by experimental results and a discussion of future work.

This paper presents methods to compute the locus of all viewpoints from which features on known polyhedral objects can be viewed in their entirety without being occluded by anything in the environment. Convex and concave polyhedra with or without holes and the viewing model of perspective projection are employed in this work. Initially, properties of the occlusion-free and occluded loci of viewpoints are determined. Based on these properties, two methods to construct these loci together with their complexity analysis are presented. In the first method, a boundary representation of the occlusion-free locus is obtained. In the second method, the locus of occluded viewpoints is expressed in terms of a constructive solid geometry representation that consists of a union of component solids. Implementation results and comparison of the two methods are given.

A survey of research in the area of vision sensor planning is presented. The problem can be summarized as follows: given information about the environment as well as information about the task that the vision system is to accomplish, develop strategies to automatically determine sensor parameter values that achieve this task with a certain degree of satisfaction. With such strategies, sensor parameters values can be selected and can be purposefully changed in order to effectively perform the task at hand. The focus here is on vision sensor planning for the task of robustly detecting object features. For this task, camera and illumination parameters such as position, orientation, and optical settings are determined so that object features are, for example, visible, in focus, within the sensor field of view, magnified as required, and imaged with sufficient contrast. References to, and a brief description of, representative sensing strategies for the tasks of object recognition and scene reconstruction are also presented. For these tasks, sensor configurations are sought that will prove most useful when trying to identify an object or reconstruct a scene.>

The MVP (machine vision planner) model-based sensor planning system for robotic vision is presented. MVP automatically synthesizes desirable camera views of a scene based on geometric models of the environment, optical models of the vision sensors, and models of the task to be achieved. The generic task of feature detectability has been chosen since it is applicable to many robot-controlled vision systems. For such a task, features of interest in the environment are required to simultaneously be visible, inside the field of view, in focus, and magnified as required. In this paper, we present a technique that poses the vision sensor planning problem in an optimization setting and determines viewpoints that satisfy all previous requirements simultaneously and with a margin. In addition, we present experimental results of this technique when applied to a robotic vision system that consists of a camera mounted on a robot manipulator in a hand-eye configuration.>

Methods for computing the locus of all viewpoints from which features on known polyhedral objects can be viewed in their entirety without being occluded by anything in the environment are presented. Convex and concave polyhedra with or without holes and the viewing model of perspective projection are used in this work. Based on properties of the occlusion-free and occluded loci of viewpoints, two methods for constructing these loci together with their complexity analysis are presented. In one method, a boundary representation of the occlusion-free locus is obtained. In the other, the locus of occluded viewpoints is expressed in terms of a constructive solid geometry representation that consists of a union of component solids. Implementation results are shown.>

The authors present calibration techniques to determine the relationships that map the parameters associated with a camera viewpoint to the parameters that can actually be controlled in a reconfigurable vision system. These relationships can be used to achieve the desired values of the camera viewpoint parameters by setting the controllable parameters to the appropriate values. The sensor setup consisted of a camera lens with zoom, focus, and aperture control. The calibration techniques were applied to the H 6*12.5 R Fujinon zoom lens and experimental results are shown.>

The authors present techniques with which camera viewpoints can be automatically determined in order to satisfy the generic feature detectability requirements of resolution, focus, and field-of-view. These optical constraints are characterized analytically for a general thick lens model, and complete viewpoint loci that satisfy these constraints are obtained. The results discussed are useful for automating the vision system design process, as well as for programming the vision system itself. In addition, such planning techniques can also automate robot imaging systems that reconfigure themselves in an intelligent manner in order to optimize imaging quality.>