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Book Steps Toward Large Scale Data Integration in the Sciences

Download or read book Steps Toward Large Scale Data Integration in the Sciences written by National Research Council and published by National Academies Press. This book was released on 2010-08-01 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Steps Toward Large-Scale Data Integration in the Sciences summarizes a National Research Council (NRC) workshop to identify some of the major challenges that hinder large-scale data integration in the sciences and some of the technologies that could lead to solutions. The workshop was held August 19-20, 2009, in Washington, D.C. The workshop examined a collection of scientific research domains, with application experts explaining the issues in their disciplines and current best practices. This approach allowed the participants to gain insights about both commonalities and differences in the data integration challenges facing the various communities. In addition to hearing from research domain experts, the workshop also featured experts working on the cutting edge of techniques for handling data integration problems. This provided participants with insights on the current state of the art. The goals were to identify areas in which the emerging needs of research communities are not being addressed and to point to opportunities for addressing these needs through closer engagement between the affected communities and cutting-edge computer science.

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Patrick Lambrix and published by Springer Science & Business Media. This book was released on 2010-08-11 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development and increasingly widespread deployment of high-throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The development of these models often requires integration of diverse experimental data resources; once constructed, the models themselves become data and present new integration challenges for tasks such as interpretation, validation and comparison. The Data Integration in the Life Sciences (DILS) Conference series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and in particular, evolution, matching and debugging of ontologies, akeycomponentforsemanticintegration;Web servicesasanimportanttechn- ogy for data integration in the life sciences; data and text mining techniques for discovering and recognizing biomedical entities and relationships between these entities; and information management, introducing data integration solutions for di?erent types of applications related to cancer, systems biology and - croarray experimental data, and an approach for integrating ranked data in the life sciences.

Book Bioinformatics

    Book Details:
  • Author : Zoé Lacroix
  • Publisher : Academic Press
  • Release : 2003-07-18
  • ISBN : 155860829X
  • Pages : 466 pages

Download or read book Bioinformatics written by Zoé Lacroix and published by Academic Press. This book was released on 2003-07-18 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen, and details on the system's strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems that bioinformatics professionals will find valuable. * Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches.-

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Amos Bairoch and published by Springer. This book was released on 2008-06-17 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: For several years now, there has been an exponential growth of the amount of life science data (e. g. , sequenced complete genomes, 3D structures, DNA chips, mass spectroscopy data), most of which are generated by high-throughput - periments. This exponentialcorpusof data is storedand made availablethrough a large number of databases and resources over the Web, but unfortunately still with a high degreeof semantic heterogeneity and varying levels of quality. These data must be combined together and processed by bioinformatics tools deployed on powerful and e?cient platforms to permit the uncovering of patterns, s- ilarities and in general to help in the process of discovery. Analyzing complex, voluminous, and heterogeneous data and guiding the analysis of data are thus of paramount importance and necessitate the involvement of data integration techniques. DILS 2008 was the ?fth in a workshop series that aims at fostering disc- sion, exchange, and innovation in research and development in the area of data integration for the life sciences. Each previous DILS workshop attracted around 100 researchers from all over the world and saw an increase of submitted - pers over the preceding one. This year was not an exception and the number of submitted papers increased to 54. The ProgramCommittee selected 18 of them. The selected papers cover a wide spectrum of theoretical and practical issues including data annotation, Semantic Web for the life sciences, and data mining on integrated biological data.

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Sarah Cohen-Boulakia and published by Springer. This book was released on 2007-06-30 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Data Integration in the Life Sciences, DILS 2007, held in Philadelphia, PA, USA in July 2007. It covers new architectures and experience on using systems, managing and designing scientific workflows, mapping and matching techniques, modeling of life science data, and annotation in data integration.

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Erhard Rahm and published by Springer Science & Business Media. This book was released on 2004-03-18 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Data Integration in the Life Sciences, DILS 2004, held in Leipzig, Germany, in March 2004. The 13 revised full papers and 2 revised short papers presented were carefully reviewed and selected from many submissions. The papers are organized in topical sections on scientific and clinical workflows, ontologies and taxonomies, indexing and clustering, integration tools and systems, and integration techniques.

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Norman W. Paton and published by Springer Science & Business Media. This book was released on 2009-07-21 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data integration in the life sciences continues to be important but challe- ing. The ongoing development of new experimental methods gives rise to an increasingly wide range of data sets, which in turn must be combined to allow more integrative views of biological systems. Indeed, the growing prominence of systems biology, where mathematical models characterize behaviors observed in experiments of di?erent types, emphasizes the importance of data integration to the life sciences. In this context, the representation of models of biological behavior as data in turn gives rise to challenges relating to provenance, data quality, annotation, etc., all of which are associated with signi?cant research activities within computer science. The Data Integration in the Life Sciences (DILS) Workshop Series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences.

Book Big Data Integration

    Book Details:
  • Author : Xin Luna Dong
  • Publisher : Springer Nature
  • Release : 2022-05-31
  • ISBN : 3031018532
  • Pages : 178 pages

Download or read book Big Data Integration written by Xin Luna Dong and published by Springer Nature. This book was released on 2022-05-31 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.

Book Principles of Data Integration

Download or read book Principles of Data Integration written by AnHai Doan and published by Elsevier. This book was released on 2012-06-25 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels. Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand Enables you to build your own algorithms and implement your own data integration applications

Book Big Data Integration

    Book Details:
  • Author : Xin Luna Dong
  • Publisher : Morgan & Claypool Publishers
  • Release : 2015-02-01
  • ISBN : 1627052240
  • Pages : 200 pages

Download or read book Big Data Integration written by Xin Luna Dong and published by Morgan & Claypool Publishers. This book was released on 2015-02-01 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.

Book Frontiers in Massive Data Analysis

Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Book On the Move to Meaningful Internet Systems  OTM 2008 Workshops

Download or read book On the Move to Meaningful Internet Systems OTM 2008 Workshops written by Zahir Tari and published by Springer. This book was released on 2008-11-19 with total page 1113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of 13 international workshops held as part of OTM 2008 in Monterrey, Mexico, in November 2008. The 106 revised full papers presented were carefully reviewed and selected from a total of 171 submissions to the workshops. The volume starts with 19 additional revised poster papers of the OTM 2008 main conferences CoopIS and ODBASE. Topics of the workshop papers are ambient data integration (ADI 2008), agents and web services merging in distributed environment (AWeSoMe 2008), community-based evolution of knowledge-intensive systems (COMBEK 2008), enterprise integration, interoperability and networking (EI2N 2008), system/software architectures (IWSSA 2008), mobile and networking technologies for social applications (MONET 2008), ontology content and evaluation in enterprise & quantitative semantic methods for the internet (OnToContent and QSI 2008), object-role modeling (ORM 2008), pervasive systems (PerSys 2008), reliability in decentralized distributed systems (RDDS 2008), semantic extensions to middleware enabling large scale knowledge (SEMELS 2008), and semantic Web and Web semantics (SWWS 2008).

Book Seeing the Future with Imaging Science

Download or read book Seeing the Future with Imaging Science written by The National Academies Keck Futures Initiatives and published by National Academies Press. This book was released on 2011-05-17 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imaging science has the power to illuminate regions as remote as distant galaxies, and as close to home as our own bodies. Many of the disciplines that can benefit from imaging share common technical problems, yet researchers often develop ad hoc methods for solving individual tasks without building broader frameworks that could address many scientific problems. At the 2010 National Academies Keck Futures Initiative Conference on Imaging Science, researchers from academia, industry, and government formed 14 interdisciplinary teams created to find a common language and structure for developing new technologies, processing and recovering images, mining imaging data, and visualizing it effectively. The teams spent nine hours over two days exploring diverse challenges at the interface of science, engineering, and medicine. NAKFI Seeing the Future with Imaging Science contains the summaries written by each team. These summaries describe the problem and outline the approach taken, including what research needs to be done to understand the fundamental science behind the challenge, the proposed plan for engineering the application, the reasoning that went into it, and the benefits to society of the problem solution.

Book Machine Learning for Health Informatics

Download or read book Machine Learning for Health Informatics written by Andreas Holzinger and published by Springer. This book was released on 2016-12-09 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

Book Refining the Concept of Scientific Inference When Working with Big Data

Download or read book Refining the Concept of Scientific Inference When Working with Big Data written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-03-24 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.

Book Data Integration in the Life Sciences

Download or read book Data Integration in the Life Sciences written by Marcos Da Silveira and published by Springer. This book was released on 2017-11-03 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Conference on Data Integration in the Life Sciences, DILS 2017, held in Luxembourg, in November 2017. The 5 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They cover topics such as: life science data modelling; analysing, indexing, and querying life sciences datasets; annotating, matching, and sharing life sciences datasets; privacy and provenance of life sciences datasets.

Book Computer and Information Sciences

Download or read book Computer and Information Sciences written by Erol Gelenbe and published by Springer Science & Business Media. This book was released on 2010-09-20 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer and Information Sciences is a unique and comprehensive review of advanced technology and research in the field of Information Technology. It provides an up to date snapshot of research in Europe and the Far East (Hong Kong, Japan and China) in the most active areas of information technology, including Computer Vision, Data Engineering, Web Engineering, Internet Technologies, Bio-Informatics and System Performance Evaluation Methodologies.