OCRIS : online catalogue and repository interoperability study. Final report

The aims and objectives of OCRIS were to: • Survey the extent to which repository content is in scope for institutional library OPACs, and the extent to which it is already recorded there; • Examine the interoperability of OPAC and repository software for the exchange of metadata and other information; • List the various services to institutional managers, researchers, teachers and learners offered respectively by OPACs and repositories; • Identify the potential for improvements in the links (e.g. using link resolver technology) from repositories and/or OPACs to other institutional services, such as finance or research administration; • Make recommendations for the development of possible further links between library OPACs and institutional repositories, identifying the benefits to relevant stakeholder groups

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Multi-device application middleware: leveraging the ubiquity of the Web with webinos

The broad range of connected devices has turned the Internet into a ubiquitous concept. In addition to desktop and laptop PCs, the Internet currently connects mobile devices, home entertainment systems, and even in-car units. From this ubiquitous evolution towards sensor-rich devices, the opportunity arises for various new types of innovative software application. However, alongside rises the issue of managing the increasing diversity of device characteristics and capabilities. As device fragmentation grows, application developers are facing the need to cover a wider variety of target devices and usage scenarios. In result, maintaining a viable balance between development costs and market coverage has turned out to be an important challenge when developing applications for a ubiquitous ecosystem. In this article, we present the webinos platform, a distributed Web runtime platform that leverages the Web for supporting self-adaptive cross-device applications. In order to enable the development of such immersive ubiquitous applications, we introduce and evaluate the concept of a context-aware federated overlay architecture

Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services

Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.Singapore-MIT Alliance (SMA

Composable M&S web services for net-centric applications

Service-oriented architectures promise easier integration of functionality in the form of web services into operational systems than is the case with interface-driven system-oriented approaches. Although the Extensible Markup Language (XML) enables a new level of interoperability among heterogeneous systems, XML alone does not solve all interoperability problems users contend with when integrating services into operational systems. To manage the basic challenges of service interoperation, we developed the Levels of Conceptual Interoperability Model (LCIM) to enable a layered approach and gradual solution improvements. Furthermore, we developed methods of model-based data engineering (MBDE) for semantically consistent service integration as a first step. These methods have been applied in the U.S. in collaboration with industry resulting in proofs of concepts. The results are directly applicable in a net-centric and net-enabled environment

Usage Bibliometrics

Scholarly usage data provides unique opportunities to address the known shortcomings of citation analysis. However, the collection, processing and analysis of usage data remains an area of active research. This article provides a review of the state-of-the-art in usage-based informetric, i.e. the use of usage data to study the scholarly process.Comment: Publisher's PDF (by permission). Publisher web site: books.infotoday.com/asist/arist44.shtm

Collaborative Cloud Computing Framework for Health Data with Open Source Technologies

The proliferation of sensor technologies and advancements in data collection methods have enabled the accumulation of very large amounts of data. Increasingly, these datasets are considered for scientific research. However, the design of the system architecture to achieve high performance in terms of parallelization, query processing time, aggregation of heterogeneous data types (e.g., time series, images, structured data, among others), and difficulty in reproducing scientific research remain a major challenge. This is specifically true for health sciences research, where the systems must be i) easy to use with the flexibility to manipulate data at the most granular level, ii) agnostic of programming language kernel, iii) scalable, and iv) compliant with the HIPAA privacy law. In this paper, we review the existing literature for such big data systems for scientific research in health sciences and identify the gaps of the current system landscape. We propose a novel architecture for software-hardware-data ecosystem using open source technologies such as Apache Hadoop, Kubernetes and JupyterHub in a distributed environment. We also evaluate the system using a large clinical data set of 69M patients.Comment: This paper is accepted in ACM-BCB 202

An information assistant system for the prevention of tunnel vision in crisis management

In the crisis management environment, tunnel vision is a set of bias in decision makers’ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the challenges in the task and the natural limitation in a human being’s cognitive process. An information assistant system is proposed with the purpose of preventing tunnel vision. The system serves as a platform for monitoring the on-going crisis event. All information goes through the system before arrives at the user. The system enhances the data quality, reduces the data quantity and presents the crisis information in a manner that prevents or repairs the user’s cognitive overload. While working with such a system, the users (crisis managers) are expected to be more likely to stay aware of the actual situation, stay open minded to possibilities, and make proper decisions