Information sharing performance management: a semantic interoperability assessment in the maritime surveillance domain

Information Sharing (IS) is essential for organizations to obtain information in a cost-effective way. If the existing information is not shared among the organizations that hold it, the alternative is to develop the necessary capabilities to acquire, store, process and manage it, which will lead to duplicated costs, especially unwanted if governmental organizations are concerned. The European Commission has elected IS among public administrations as a priority, has launched several IS initiatives, such as the EUCISE2020 project within the roadmap for developing the maritime Common Information Sharing Environment (CISE), and has defined the levels of interoperability essential for IS, which entail Semantic Interoperability (SI). An open question is how can IS performance be managed? Specifically, how can IS as-is, and to-be states and targets be defined, and how can organizations progress be monitored and controlled? In this paper, we propose 11 indicators for assessing SI that contribute to answering these questions. They have been demonstrated and evaluated with the data collected through a questionnaire, based on the CISE information model proposed during the CoopP project, which was answered by five public authorities that require maritime surveillance information and are committed to share information with each other.Postprint (published version

A methodological proposal and tool support for the HL7 standards compliance in the development of health information systems

Health information systems are increasingly complex, and their development is presented as a challenge for software development companies offering quality, maintainable and interoperable products. HL7 (Health level 7) International, an international non-profit organization, defines and maintains standards related to health information systems. However, the modelling languages proposed by HL7 are far removed from standard languages and widely known by software engineers. In these lines, NDT is a software development methodology that has a support tool called NDT-Suite and is based, on the one hand, on the paradigm of model-driven engineering and, on the other hand, in UML that is a widely recognized standard language. This paper proposes an extension of the NDT methodology called MoDHE (Model Driven Health Engineering) to offer software engineers a methodology capable of modelling health information systems conforming to HL7 using UML domain models

Digital Preservation, Archival Science and Methodological Foundations for Digital Libraries

Digital libraries, whether commercial, public or personal, lie at the heart of the information society. Yet, research into their long‐term viability and the meaningful accessibility of their contents remains in its infancy. In general, as we have pointed out elsewhere, ‘after more than twenty years of research in digital curation and preservation the actual theories, methods and technologies that can either foster or ensure digital longevity remain startlingly limited.’ Research led by DigitalPreservationEurope (DPE) and the Digital Preservation Cluster of DELOS has allowed us to refine the key research challenges – theoretical, methodological and technological – that need attention by researchers in digital libraries during the coming five to ten years, if we are to ensure that the materials held in our emerging digital libraries are to remain sustainable, authentic, accessible and understandable over time. Building on this work and taking the theoretical framework of archival science as bedrock, this paper investigates digital preservation and its foundational role if digital libraries are to have long‐term viability at the centre of the global information society.

Interoperable intelligent environmental decision support systems: a framework proposal

In this paper, an approach for the development of Interoperable Intelligent Environmental Decision Support Systems (IEDSS) is proposed. The framework is based upon the cognitive-oriented approach for the development of IEDSS proposed in (Sànchez-Marrè et al., 2008), where three kind of tasks must be built: analysis tasks, synthesis tasks and prognosis tasks. Now, a fourth level will be proposed: the model construction layer, which is normally an off-line task. At each level, interoperability should be possible and inter-level interoperability must be als o achieved. This interoperability is proposed to be obtained using data interchange protocols like Predictive Model Markup Language (PMML), which is a model interc hange protocol based on XML language, using an ontology of data and AI models to characterize data types and AI models and to set-up a common terminology, and using workflows of the whole interoperation scheme. In the future, a Multi-Agent System will be used to implement the software components. An example of use of the pro posed methodology applied to the supervision of a Wastewater Treatment Plant is provided. This Interoperable IEDSS framework will be the first step to an actual interoperability of AI models which will make IEDSS more reliable and accurate to solve complex environmental problems.Peer ReviewedPostprint (published version

Interoperability Maturity Model: Orchestrator Tool for Platform Ecosystems

The orchestration of platform ecosystems is becoming increasingly complex due to the growing number of players, complementary services and technological innovations. Interoperability is an important prerequisite for convincing customer journeys as well as functional and quality-assured data exchange and offers increasing potential for automation, especially with the help of machine learning or artificial intelligence. The interoperability maturity model developed in this study can be used as a conceptual framework to measure the interoperability of current and future platform ecosystem components and complements. The model, developed as an artifact of design science research, was evaluated using an iterative approach with orchestrators of health data platforms and their ecosystem. The results suggest that it can contribute to achieving and sustaining integrated value chains with multiple actors and diverse technologies, and can be used to assess the interoperability of care chains (e.g., care scenarios such as diabetes or cardiac insufficiency) and guide future interoperability considerations

Are Meaningful Use Stage 2 certified EHRs ready for interoperability? Findings from the SMART C-CDA Collaborative

Background and objective Upgrades to electronic health record (EHR) systems scheduled to be introduced in the USA in 2014 will advance document interoperability between care providers. Specifically, the second stage of the federal incentive program for EHR adoption, known as Meaningful Use, requires use of the Consolidated Clinical Document Architecture (C-CDA) for document exchange. In an effort to examine and improve C-CDA based exchange, the SMART (Substitutable Medical Applications and Reusable Technology) C-CDA Collaborative brought together a group of certified EHR and other health information technology vendors. Materials and methods We examined the machine-readable content of collected samples for semantic correctness and consistency. This included parsing with the open-source BlueButton.js tool, testing with a validator used in EHR certification, scoring with an automated open-source tool, and manual inspection. We also conducted group and individual review sessions with participating vendors to understand their interpretation of C-CDA specifications and requirements. Results: We contacted 107 health information technology organizations and collected 91 C-CDA sample documents from 21 distinct technologies. Manual and automated document inspection led to 615 observations of errors and data expression variation across represented technologies. Based upon our analysis and vendor discussions, we identified 11 specific areas that represent relevant barriers to the interoperability of C-CDA documents. Conclusions: We identified errors and permissible heterogeneity in C-CDA documents that will limit semantic interoperability. Our findings also point to several practical opportunities to improve C-CDA document quality and exchange in the coming years

An interoperable workflow-based framework for the automation of building intelligent process control systems

One of the major problems to design and implement a control/supervision system for a process lies in the need to establish an ad-hoc system for each process installation. On the other side, an open challenge related to the deployment of Intelligent Decision Support Systems (IDSSs) is the interoperability of the different methods used, in order to allow interaction and reuse of different data mining methods and the use of methods based on a model or an expert. Thus, this paper proposes the use of visual workflows, to enable the automation of the design task and the implementation of Intelligent Process Control Systems (IPCSs). The framework will allow the user to specify the design and control of a concrete process as well as the required data-driven and expert models using a graphical workflow environment. The framework is based on a three-layer architecture: first, a comprehensive data science flow description layer (dataflow layer) to produce/discover data-driven models from process data; second, a flowchart of the different components of the process (process-design flow layer) to obtain a simulation model from the design. Finally, the on-line IPCS (process control workflow layer), where the different data-driven models, expert-based models and intelligent reasoning methods interoperate to control and supervise the process. Thus, the resulting system can automatically generate both simulation models of the process and programming code to control and supervise the process, using workflows designed for each particular installation. The case study is focused on the supervision of a Wastewater Treatment Plant (WWTP) located in the Barcelona region.The authors acknowledge the partial support of this work by the Industrial Doctorate Programme (2017-DI-006) and the Research Consolidated Groups/Centres Grant (2017 SGR 574) from the Catalan Agency of University and Research Grants Management (AGAUR), from Catalan Government.Peer ReviewedPostprint (author's final draft

Identifying Health Facilities outside the Enterprise: Challenges and Strategies for Supporting Health Reform and Meaningful Use

Objective: To support collation of data for disability determination, we sought to accurately identify facilities where care was delivered across multiple, independent hospitals and clinics. Methods: Data from various institutions' electronic health records were merged and delivered as continuity of care documents to the United States Social Security Administration (SSA). Results: Electronic records for nearly 8000 disability claimants were exchanged with SSA. Due to the lack of standard nomenclature for identifying the facilities in which patients received the care documented in the electronic records, SSA could not match the information received with information provided by disability claimants. Facility identifiers were generated arbitrarily by health care systems and therefore could not be mapped to the existing international standards. Discussion: We propose strategies for improving facility identification in electronic health records to support improved tracking of a patient's care between providers to better serve clinical care delivery, disability determination, health reform and meaningful use. Conclusion: Accurately identifying the facilities where health care is delivered to patients is important to a number of major health reform and improvement efforts underway in many nations. A standardized nomenclature for identifying health care facilities is needed to improve tracking of care and linking of electronic health records