DRIVER Technology Watch Report

This report is part of the Discovery Workpackage (WP4) and is the third report out of four deliverables. The objective of this report is to give an overview of the latest technical developments in the world of digital repositories, digital libraries and beyond, in order to serve as theoretical and practical input for the technical DRIVER developments, especially those focused on enhanced publications. This report consists of two main parts, one part focuses on interoperability standards for enhanced publications, the other part consists of three subchapters, which give a landscape picture of current and surfacing technologies and communities crucial to DRIVER. These three subchapters contain the GRID, CRIS and LTP communities and technologies. Every chapter contains a theoretical explanation, followed by case studies and the outcomes and opportunities for DRIVER in this field

A Conceptual Model for Scholarly Research Activity

This paper presents a conceptual model for scholarly research activity, developed as part of the conceptual modelling work within the ???Preparing DARIAH??? European e-Infrastructures project. It is inspired by cultural-historical activity theory, and is expressed in terms of the CIDOC Conceptual Reference Model, extending its notion of activity so as to also account, apart from historical practice, for scholarly research planning. It is intended as a framework for structuring and analyzing the results of empirical research on scholarly practice and information requirements, encompassing the full research lifecycle of information work and involving both primary evidence and scholarly objects; also, as a framework for producing clear and pertinent information requirements, and specifications of digital infrastructures, tools and services for scholarly research. We plan to use the model to tag interview transcripts from an empirical study on scholarly information work, and thus validate its soundness and fitness for purpose

Querying Semantic Web Resources Using TRIPLE Views

Resources on the Semantic Web are described by metadata based on some formal or informal ontology. It is a common situation that casual users are not familiar with a domain ontology in detail. This makes it difficult for such users (or their user tools) to formulate queries to find the relevant resources. Users consider the resources in their specific context, so the most straightforward solution is to formulate queries in an ontology that corresponds to a user-specific view. We present an approach based on multiple views expressed in ontologies simpler than the domain ontology. This allows users to query heterogeneous data repositories in terms of multiple, relatively simple, view ontologies. Ontology developers can define such view ontologies and the corresponding mapping rules. These ontologies are represented in Semantic Web ontology languages such as RDFS, DAML+OIL, or OWL. We present our approach with examples from the e-learning domain using the Semantic Web query and transformation language TRIPLE

Porqpine: a peer-to-peer search engine

In this paper, we present a fully distributed and collaborative search engine for web pages: Porqpine. This system uses a novel query-based model and collaborative filtering techniques in order to obtain user-customized results. All knowledge about users and profiles is stored in each user node?s application. Overall the system is a multi-agent system that runs on the computers of the user community. The nodes interact in a peer-to-peer fashion in order to create a real distributed search engine where information is completely distributed among all the nodes in the network. Moreover, the system preserves the privacy of user queries and results by maintaining the anonymity of the queries? consumers and results? producers. The knowledge required by the system to work is implicitly caught through the monitoring of users actions, not only within the system?s interface but also within one of the most popular web browsers. Thus, users are not required to explicitly feed knowledge about their interests into the system since this process is done automatically. In this manner, users obtain the benefits of a personalized search engine just by installing the application on their computer. Porqpine does not intend to shun completely conventional centralized search engines but to complement them by issuing more accurate and personalized results.Postprint (published version

Software architecture style for interoperable databases

We propose a layered and component based software architecture style which supports interoperability in multiple databases (DB). The architectural style's building blocks and its constraints are described and the deployment of two design patterns outlined. Components placed in our architectural layers exhibit a linear topology and request/reply processing style. The constraints include communications between components which are not in the adjacent architectural layers and extension of the intuitive many : one bindings between components towards many : many. We comment on similarities with mediation architectures and outline some implementation issues

Interoperability in eLearning Contexts. Interaction between LMS and PLE

The emergence of the Information and Communication Technologies and its application in several areas with varying success, implies the definition of a great number of software systems. Such systems are implemented in very different programming languages, using distinct types of resources, etc. Learning and Teaching is one of those application areas, where there are different learning platforms, repositories, tools, types of content, etc. These systems should interoperate among them to provide better and more useful learning services to students and teachers, and to do so web services and interoperability specifications are needed. This paper presents a service-based framework approach to facilitate the interoperability between Learning Management Systems and Personal Learning Environments, which has been implemented as a proof of concept and evaluated through several pilot experiences. From such experiences it is possible to see that interoperability among the personal and institutional environments it is possible and, in this way, learners can learn independently without accessing to the institutional site and teachers have information about learning that happens in informal activities

LinkedScales : bases de dados em multiescala

Orientador: André SantanchèTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: As ciências biológicas e médicas precisam cada vez mais de abordagens unificadas para a análise de dados, permitindo a exploração da rede de relacionamentos e interações entre elementos. No entanto, dados essenciais estão frequentemente espalhados por um conjunto cada vez maior de fontes com múltiplos níveis de heterogeneidade entre si, tornando a integração cada vez mais complexa. Abordagens de integração existentes geralmente adotam estratégias especializadas e custosas, exigindo a produção de soluções monolíticas para lidar com formatos e esquemas específicos. Para resolver questões de complexidade, essas abordagens adotam soluções pontuais que combinam ferramentas e algoritmos, exigindo adaptações manuais. Abordagens não sistemáticas dificultam a reutilização de tarefas comuns e resultados intermediários, mesmo que esses possam ser úteis em análises futuras. Além disso, é difícil o rastreamento de transformações e demais informações de proveniência, que costumam ser negligenciadas. Este trabalho propõe LinkedScales, um dataspace baseado em múltiplos níveis, projetado para suportar a construção progressiva de visões unificadas de fontes heterogêneas. LinkedScales sistematiza as múltiplas etapas de integração em escalas, partindo de representações brutas (escalas mais baixas), indo gradualmente para estruturas semelhantes a ontologias (escalas mais altas). LinkedScales define um modelo de dados e um processo de integração sistemático e sob demanda, através de transformações em um banco de dados de grafos. Resultados intermediários são encapsulados em escalas reutilizáveis e transformações entre escalas são rastreadas em um grafo de proveniência ortogonal, que conecta objetos entre escalas. Posteriormente, consultas ao dataspace podem considerar objetos nas escalas e o grafo de proveniência ortogonal. Aplicações práticas de LinkedScales são tratadas através de dois estudos de caso, um no domínio da biologia -- abordando um cenário de análise centrada em organismos -- e outro no domínio médico -- com foco em dados de medicina baseada em evidênciasAbstract: Biological and medical sciences increasingly need a unified, network-driven approach for exploring relationships and interactions among data elements. Nevertheless, essential data is frequently scattered across sources with multiple levels of heterogeneity. Existing data integration approaches usually adopt specialized, heavyweight strategies, requiring a costly upfront effort to produce monolithic solutions for handling specific formats and schemas. Furthermore, such ad-hoc strategies hamper the reuse of intermediary integration tasks and outcomes. This work proposes LinkedScales, a multiscale-based dataspace designed to support the progressive construction of a unified view of heterogeneous sources. It departs from raw representations (lower scales) and goes towards ontology-like structures (higher scales). LinkedScales defines a data model and a systematic, gradual integration process via operations over a graph database. Intermediary outcomes are encapsulated as reusable scales, tracking the provenance of inter-scale operations. Later, queries can combine both scale data and orthogonal provenance information. Practical applications of LinkedScales are discussed through two case studies on the biology domain -- addressing an organism-centric analysis scenario -- and the medical domain -- focusing on evidence-based medicine dataDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação141353/2015-5CAPESCNP

Electronic Medical Records

Electronic Medical Record (EMR) relational database is considered to be a major component of any medical care information system. A major problem for researchers in medical informatics is finding the best way to use these databases to extract valued useful information to and about the patient’s diseases and treatments. Integrating different EMR databases is a great achievement that will improve health care systems. This paper presents an AI approach to extract generic EMR from different resources and transfer them to clinical cases. The utilized approach is based on retrieving different relationships between patients’ different data tables (files) and automatically generating EMRs in XML format, then building frame based medical cases to form a case repository that can be used in medical diagnostic systems

Ontology Pattern-Based Data Integration

Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. This dissertation represents a study on how small, self-contained ontologies, called ontology design patterns, can be employed to provide semantic interoperability in a cross-repository data integration system. The idea of this so-called ontology pattern- based data integration is that a collection of ontology design patterns can act as the global schema that still contains sufficient semantics, but is also flexible and simple enough to be used by linked data providers. On the one side, this differs from existing ontology-based solutions, which are based on large, monolithic ontologies that provide very rich semantics, but enforce too restrictive ontological choices, hence are shunned by many data providers. On the other side, this also differs from the purely linked data based solutions, which do offer simplicity and flexibility in data publishing, but too little in terms of semantic interoperability. We demonstrate the feasibility of this idea through the actual development of a large scale data integration project involving seven ocean science data repositories from five institutions in the U.S. In addition, we make two contributions as part of this dissertation work, which also play crucial roles in the aforementioned data integration project. First, we develop a collection of more than a dozen ontology design patterns that capture the key notions in the ocean science occurring in the participating data repositories. These patterns contain axiomatization of the key notions and were developed with an intensive involvement from the domain experts. Modeling of the patterns was done in a systematic workflow to ensure modularity, reusability, and flexibility of the whole pattern collection. Second, we propose the so-called pattern views that allow data providers to publish their data in very simple intermediate schema and show that they can greatly assist data providers to publish their data without requiring a thorough understanding of the axiomatization of the patterns