Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Series Title
      Series Title
      Clear All
      Series Title
  • Reading Level
      Reading Level
      Clear All
      Reading Level
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
      More Filters
      Clear All
      More Filters
      Content Type
    • Item Type
    • Is Full-Text Available
    • Subject
    • Publisher
    • Source
    • Donor
    • Language
    • Place of Publication
    • Contributors
    • Location
8,135 result(s) for "Linked data."
Sort by:
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.
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.
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.
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.
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.
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.
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.
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]
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.
Construction of Shipping Linked Data Lifecycle Model and Its Application in Semantic Navigation
As one of the most important government data assets, shipping data has attracted more and more attention from stakeholders. The term linked data refers to a set of best practices for publishing and linking structured data on the web. The application of linked data technology to open the shipping data can promote the transparency and reusability of data. Many shipping data have been placed on the network as linked data. However, the existing construction of shipping linked data does not consider the concept of lifecycle, and the concept of lifecycle naturally lies in the link data itself. Therefore, this paper attempts to propose a linked data lifecycle model to assist in publishing shipping data as linked data on the Web. We first conduct a systematic analysis of the typical lifecycle model. On this basis, a new linked data lifecycle model is proposed, and the role of each step of the model is also explained. In particular, we take domain modeling as the first step of the model and discuss the key role of it in publishing linked data. Taking the voyage data as an example, we show in detail how to use the proposed model to construct shipping linked data. Then, a specific semantic navigation case based on the above data is given to prove the added value of the linked data. The results show that the lifecycle model proposed in this paper is suitable for the publication of shipping data and is convenient for future expansion and maintenance.