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Linked data management
\"With the growing popularity of the Semantic Web, more and more semantic data and data sources become available and accessible for everyone. By establishing semantic links between the data, answers to (complex) queries can be evaluated based on the data on multiple providers instead of just one. This book motivates, introduces, and details techniques for processing heterogeneous structured data on the Web by providing a comprehensive overview for database researchers and practitioners about this new publishing paradigm on the web, and show how the abundance of data published as Linked Data can serve as a fertile ground for database research and experimentation\"-- Provided by publisher.
Book
Geospatial Data Science
This introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site: https://ai.di.uoa.gr/geospatial-data-science-book/index.html where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the Knowledge Technologies course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.
eBook
Sharing linked data for health research : toward better decision making
\"The genesis of this project was the experience of the authors working with researchers, data custodians, ethics committees, and linkage units over the past decade or more managing access to government administrative data for research. Our individual backgrounds, experience, and expertise meant that we brought a diverse, interdisciplinary approach to the table. We started to identify the problems: we heard from researchers that there were concerns with unjustified delay and lack of access to data for research that was in the public interest; we heard from data custodians that they found the decision-making process difficult because they did not have sufficient resources or guidance; we heard from ethics committees that they found data linkage projects complex and difficult to assess; and we heard from consumer representatives that there were concerns about privacy, transparency, community awareness, and consultation\"-- Provided by publisher.
Book
Semantic Web for the Working Ontologist, Third Edition
Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no longer a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today. The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way. The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.
eBook
Methodological developments in data linkage
A comprehensive compilation of new developments in data linkage methodology
The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate identifiers, missing data and regulatory issues. Recent developments in data linkage methodology have concentrated on bias and analysis of linked data, novel approaches to organising relationships between databases and privacy-preserving linkage.
Methodological Developments in Data Linkage brings together a collection of contributions from members of the international data linkage community, covering cutting edge methodology in this field. It presents opportunities and challenges provided by linkage of large and often complex datasets, including analysis problems, legal and security aspects, models for data access and the development of novel research areas. New methods for handling uncertainty in analysis of linked data, solutions for anonymised linkage and alternative models for data collection are also discussed.
Key Features:
* Presents cutting edge methods for a topic of increasing importance to a wide range of research areas, with applications to data linkage systems internationally
* Covers the essential issues associated with data linkage today
* Includes examples based on real data linkage systems, highlighting the opportunities, successes and challenges that the increasing availability of linkage data provides
* Novel approach incorporates technical aspects of both linkage, management and analysis of linked data
This book will be of core interest to academics, government employees, data holders, data managers, analysts and statisticians who use administrative data. It will also appeal to researchers in a variety of areas, including epidemiology, biostatistics, social statistics, informatics, policy and public health.
eBook
A survey on question answering systems over linked data and documents
Question Answering (QA) systems aim at supplying precise answers to questions, posed by users in a natural language form. They are used in a wide range of application areas, from bio-medicine to tourism. Their underlying knowledge source can be structured data (e.g. RDF graphs and SQL databases), unstructured data in the form of plain text (e.g. textual excerpts from Wikipedia), or combinations of the above. In this paper we survey the recent work that has been done in the area of stateless QA systems with emphasis on methods that have been applied in RDF and Linked Data, documents, and mixtures of these. We identify the main challenges, we categorize the existing approaches according to various aspects, we review 21 recent systems, and 23 evaluation and training datasets that are most commonly used in the literature categorized according to the type of the domain, the underlying knowledge source, the provided tasks, and the associated evaluation metrics.
Journal Article
Linked Data for the Perplexed Librarian
Linked data has become a punchline in certain circles of the GLAM (galleries, libraries, archives, and museums) community, derided as a much-hyped project that will ultimately never come to fruition.
eBook
Linked Data Interfaces: A Survey
In the era of big data, linked data interfaces play a critical role in enabling access to and management of large-scale, heterogeneous datasets. This survey investigates forty-seven interfaces developed by the semantic web community in the context of the Web of Linked Data, displaying information about general topics and digital library contents. The interfaces are classified based on their interaction paradigm, the type of information they display, and the complexity reduction strategies they employ. The main purpose to be addressed is the possibility of categorizing a great number of available tools so that comparison among them becomes feasible and valuable. The analysis reveals that most interfaces use a hybrid interaction paradigm combining browsing, searching, and displaying information in lists or tables. Complexity reduction strategies, such as faceted search and summary visualization, are also identified. Emerging trends in linked data interface focus on user-centric design and advancements in semantic annotation methods, leveraging machine learning techniques for data enrichment and retrieval. Additionally, an interactive platform is provided to explore and compare data on the analyzed tools. Overall, there is no one-size-fits-all solution for developing linked data interfaces and tailoring the interaction paradigm and complexity reduction strategies to specific user needs is essential.
Journal Article
Knowledge Representation of digital Hermeneutics of archival and literary Sources
Scholarly analysis of archival, library, and literary sources results in a variety of digital artefacts meant to foster knowledge discovery and new research enquiries. Guidelines and standards to formally represent disciplinary information are available (e.g. XML schemas, ontologies, vocabularies). However, digital artefacts rarely address reusable structured information on the hermeneutical approach adopted by scholars when validating hypotheses. As a consequence, reproducibility and assessment of research results is hampered, and comparing online contradictory information is still a hard task. In this work we show how to leverage Semantic Web technologies in a high-level, portable data model for representing hermeneutical aspects related to cross-disciplinary analysis of archival and literary sources. We showcase three representative scenarios in the Cultural Heritage domain where the model is applied, and we describe benefits and limits of our solution. [Publisher's text]
Journal Article
Using population data to understand the epidemiology and risk factors for diabetic ketoacidosis in Australian children with type 1 diabetes
Background Children with type 1 diabetes (T1D) are at risk of diabetic ketoacidosis (DKA) at T1D diagnosis and/or subsequently. Objective The objective is to determine the incidence and prevalence of T1D by the presence of DKA and identify the characteristics of subsequent DKA episodes. Subjects The study population included all children aged <15 years with T1D during a hospital/day‐stay admission in New South Wales, Australia, from 1 January 2001 to 31 December 2013. T1D and DKA were identified using International Classification of Diseases Australian Modification codes. Methods Data sources included routinely collected longitudinally linked population hospitalization and birth records. Chi‐squared analyses, logistic, and multinomial regression were used to determine the association between child characteristics and admissions with and without DKA. Results The point prevalence of T1D among 0‐14‐year olds on 31 December 2013 was 144.2 per 100 000. For children aged 0‐12 years, the incidence of T1D was 16.3 per 100 000 child‐years. One‐third had DKA at T1D diagnosis and were more likely to be readmitted with DKA than those without DKA at T1D diagnosis. Children with more than one readmission for DKA were more likely to be female, reside in an inner regional area or an area of socioeconomic disadvantage, and be Australian‐born. Among all hospitalizations of children with T1D, those with DKA were more likely to be aged 10‐14 years, require intensive care, have longer length of stay, and admitted outside school days. Conclusion Routinely collected administrative health data are a reliable source to monitor incidence and health service use of childhood T1D. Children at risk of repeated DKA, particularly females, adolescents, and those from inner regional or socioeconomically disadvantaged areas, should be targeted during education and follow‐up.
Journal Article