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| data management conference 2023: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| data management conference 2023: Data Management Technologies and Applications Slimane Hammoudi, Christoph Quix, Jorge Bernardino, 2021-07-22 This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity. |
| data management conference 2023: Graph Data Management George Fletcher, Jan Hidders, Josep Lluís Larriba-Pey, 2018-10-31 This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains. The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions. The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs. |
| data management conference 2023: Data Leadership Anthony J. Algmin, 2020-10-14 Data has never been more important to your success than it is today, yet you are surrounded with data you can't trust, and the overwhelming burden of fixing it. Everyone deserves data that helps-not hurts-their organization. |
| data management conference 2023: CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality Pietro Capone, Vito Getuli , Farzad Pour Rahimian, Nashwan Dawood , Alessandro Bruttini, Tommaso Sorbi, Within the overarching theme of “Managing the Digital Transformation of Construction Industry” the 23rd International Conference on Construction Applications of Virtual Reality (CONVR 2023) presented 123 high-quality contributions on the topics of: Virtual and Augmented Reality (VR/AR), Building Information Modeling (BIM), Simulation and Automation, Computer Vision, Data Science, Artificial Intelligence, Linked Data, Semantic Web, Blockchain, Digital Twins, Health & Safety and Construction site management, Green buildings, Occupant-centric design and operation, Internet of Everything. The editors trust that this publication can stimulate and inspire academics, scholars and industry experts in the field, driving innovation, growth and global collaboration among researchers and stakeholders. |
| data management conference 2023: Engaging Researchers with Data Management Connie Clare, Maria J. Cruz, Elli Papadopoulou, James Savage (Research associate), Marta Teperek, Yan Wang, Iza Witkowska, Joanne Yeomans, 2019 Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences. |
| data management conference 2023: Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023) Nadeem Akhtar, Azah Kamilah Draman, Mohd Faizal Abdollah, 2023-07-25 This is an open access book.The 3rd International Conference on Public Management and Intelligent Society(PMIS 2023) will be held on March 10-12, 2023 in Shanghai, China. PMIS 2021 and PMIS 2022 have been successfully held in the last 2 years, providing an academic exchange platform for participants from all over the world. The conference discussed the latest topics in the field of public management and intelligent society, and the wonderful presentations were given by invited distinguished speakers and praised by scholars. Building an intelligent society and studying public management have always been a leading and hot issue. PMIS 2023 will focus on public management in an intelligent society, technological innovation in an intelligent society and advanced intelligent transportation system to discuss further. The aim of PMIS 2023 is to bring together innovative academics and industrial experts in the field of Public Management and Intelligent Society to a common forum. The primary goal to promote research and developmental activities and another goal is to promote scientific information interchange between researchers, developers, students, and practitioners in related fields. |
| data management conference 2023: Proceedings of the International Conference on Big Data, IoT, and Machine Learning Mohammad Shamsul Arefin, M. Shamim Kaiser, Anirban Bandyopadhyay, Md. Atiqur Rahman Ahad, Kanad Ray, 2021-12-03 This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field. |
| data management conference 2023: Data Governance John Ladley, 2019-11-08 Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition |
| data management conference 2023: Space Data Management Agostino Cortesi, |
| data management conference 2023: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| data management conference 2023: Data Analytics and Management Ashish Khanna, Deepak Gupta, Zdzisław Pólkowski, Siddhartha Bhattacharyya, Oscar Castillo, 2021-01-04 This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2020), held at Jan Wyzykowski University, Poland, during June 2020. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. |
| data management conference 2023: Data Management, Analytics and Innovation Neha Sharma, |
| data management conference 2023: Data Governance Dimitrios Sargiotis, |
| data management conference 2023: International Conference on Intelligent and Smart Computing in Data Analytics Siddhartha Bhattacharyya, Janmenjoy Nayak, Kolla Bhanu Prakash, Bighnaraj Naik, Ajith Abraham, 2021-03-12 This book is a collection of best selected research papers presented at International Conference on Intelligent and Smart Computing in Data Analytics (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, pattern recognition and analysis, computational intelligence, signal and image processing, bioinformatics, ubiquitous computing, genetic fuzzy systems, hybrid evolutionary algorithms, nature-inspired smart hybrid systems, Internet of things, industrial IoT, health informatics, human–computer interaction and social network analysis. The book presents innovative work by leading academics, researchers and experts from industry. |
| data management conference 2023: Blockchain, Internet of Things, and Artificial Intelligence Naveen Chilamkurti, T. Poongodi, Balamurugan Balusamy, 2021-04-02 Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book's accessibility more extensively. Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions. The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed. FEATURES Discusses the potential of blockchain to significantly increase data while boosting accuracy and integrity in IoT-generated data and AI-processed information Elucidates definitions, concepts, theories, and assumptions involved in smart contracts and distributed ledgers related to IoT systems and AI approaches Offers real-world uses of blockchain technologies in different IoT systems and further studies its influence in supply chains and logistics, the automotive industry, smart homes, the pharmaceutical industry, agriculture, and other areas Presents readers with ways of employing blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain Provides readers with an awareness of how industry can avoid some of the pitfalls of traditional data-sharing strategies This book is suitable for graduates, academics, researchers, IT professionals, and industry experts. |
| data management conference 2023: 16th European Conference on Management, Leadership and Governance Dr Paul Griffiths, 2020-10-26 These proceedings represent the work of contributors to the 16th European Conference on Management Leadership and Governance (ECMLG 2020) hosted by ACI and EM-Normandie Business School, Oxford, UK, UK on 26 – 27th October 2020. The Conference Chair Dr Paul Griffiths, EM-Normandie Business School, Metis Lab. Oxford, UK |
| data management conference 2023: Big Data Management And Analytics Brij B Gupta, Mamta, 2023-12-05 With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance. |
| data management conference 2023: Proceedings of the Rocscience International Conference 2023 (RIC2023) Reginald E. Hammah, Sina Javankhoshdel, Thamer Yacoub, Alireza Azami, Alison McQuillan, 2023-12-08 This is an open access book. Rocscience is delighted to announce the Rocscience International Conference 2023 (RIC2023), an in-person gathering to be held from April 24–26, 2023, in Toronto, Canada. RIC2023's primary objective is to bring geotechnical professionals together to meet and exchange ideas on important issues and developments in geotechnical engineering, particularly combinations of emerging and mature technologies. The geotechnical industry is rapidly evolving. Engineers are more connected through technology, technology is becoming more integrated than ever, and methods combining these technologies are becoming more prevalent. This movement towards combining technologies led us to the conference theme, “Synergy in Geotechnical Engineering – Success Beyond Individual Technologies.” We believe the time is right to highlight how far the industry has come with various technologies and continues to develop. The conference aims to create an environment that fosters new perspectives and helps attendees delve deeper into innovative approaches. During RIC2023, Rocscience will award the 2023 Lifetime Achievement Medal to Dr. Norbert Morgenstern, an internationally recognized authority in the engineering community. As both a practitioner and educator, Dr. Morgenstern’s contributions to the geotechnical community continue to benefit engineers worldwide, and he will give an address on his career. In addition to keynotes by Dr. Morgernstern and four other distinguished speakers, there will be several technical and networking sessions. |
| data management conference 2023: The IBM Data Governance Unified Process Sunil Soares, 2010-10 Anyone considering a data governance program within their organization will find an invaluable step-by-step methodology using IBM tools and best practices in this structured how-to. While many in the IT industry hold separate definitions in their minds, this authoritative manual defines data governance as the discipline of treating data as an enterprise asset. The intricate process of data governance involves the exercise of decision rights to optimize, secure, and leverage data. Providing a rigorous explanation of the 14 steps and almost 100 substeps to enact unified data governance, this extensive handbook also shows that the core issues to be tackled are not about technology but rather about people and process. |
| data management conference 2023: Enterprise Master Data Management Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run, Dan Wolfson, 2008-06-05 The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration |
| data management conference 2023: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it! |
| data management conference 2023: The "Orange" Model of Data Management Irina Steenbeek, 2019-10-21 *This book is a brief overview of the model and has only 24 pages.*Almost every data management professional, at some point in their career, has come across the following crucial questions:1. Which industry reference model should I use for the implementation of data managementfunctions?2. What are the key data management capabilities that are feasible and applicable to my company?3. How do I measure the maturity of the data management functions and compare that withthose of my peers in the industry4. What are the critical, logical steps in the implementation of data management?The Orange (meta)model of data management provides a collection of techniques and templates for the practical set up of data management through the design and implementation of the data and information value chain, enabled by a set of data management capabilities.This book is a toolkit for advanced data management professionals and consultants thatare involved in the data management function implementation.This book works together with the earlier published The Data Management Toolkit. The Orange model assists in specifying the feasible scope of data management capabilities, that fits company's business goals and resources. The Data Management Toolkit is a practical implementation guide of the chosen data management capabilities. |
| data management conference 2023: New Trends in Database and Information Systems Alberto Abelló, Panos Vassiliadis, Oscar Romero, Robert Wrembel, Francesca Bugiotti, Johann Gamper, Genoveva Vargas Solar, Ester Zumpano, 2023-08-30 This book constitutes the refereed proceedings of the Doctoral Consortium and Workshops on New Trends in Database and Information Systems, ADBIS 2023, held in Barcelona, Spain, during September 4–7, 2023. The 29 full papers, 25 short papers and 7 doctoral consortium included in this book were carefully reviewed and selected from 148. They were organized in topical sections as follows: ADBIS Short Papers: Index Management & Data Reconstruction, ADBIS Short Papers: Query Processing, ADBIS Short Papers: Advanced Querying Techniques, ADBIS Short Papers: Fairness in Data Management, ADBIS Short Papers: Data Science, ADBIS Short Papers: Temporal Graph Management, ADBIS Short Papers: Consistent Data Management, ADBIS Short Papers: Data Integration, ADBIS Short Papers: Data Quality, ADBIS Short Papers: Metadata Management, Contributions from ADBIS 2023 Workshops and Doctoral Consortium, AIDMA: 1st Workshop on Advanced AI Techniques for Data Management, Analytics, DOING: 4th Workshop on Intelligent Data - From Data to Knowledge, K-Gals: 2nd Workshop on Knowledge Graphs Analysis on a Large Scale, MADEISD: 5th Workshop on Modern Approaches in Data Engineering, Information System Design, PeRS: 2nd Workshop on Personalization, Recommender Systems, Doctoral Consortium. |
| data management conference 2023: Crowdsourced Data Management Guoliang Li, Jiannan Wang, Yudian Zheng, 2019-11-08 This book provides an overview of crowdsourced data management. Covering all aspects including the workflow, algorithms and research potential, it particularly focuses on the latest techniques and recent advances. The authors identify three key aspects in determining the performance of crowdsourced data management: quality control, cost control and latency control. By surveying and synthesizing a wide spectrum of studies on crowdsourced data management, the book outlines important factors that need to be considered to improve crowdsourced data management. It also introduces a practical crowdsourced-database-system design and presents a number of crowdsourced operators. Self-contained and covering theory, algorithms, techniques and applications, it is a valuable reference resource for researchers and students new to crowdsourced data management with a basic knowledge of data structures and databases. |
| data management conference 2023: Responsible Artificial Intelligence Virginia Dignum, 2019-11-04 In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens. |
| data management conference 2023: Transactions on Large-Scale Data- and Knowledge-Centered Systems LVII Abdelkader Hameurlain, |
| data management conference 2023: Collaborative Computing: Networking, Applications and Worksharing Honghao Gao, Xinheng Wang, 2022-01-01 This two-volume set constitutes the refereed proceedings of the 17th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 62 full papers and 7 short papers presented were carefully reviewed and selected from 206 submissions. The papers reflect the conference sessions as follows: Optimization for Collaborate System; Optimization based on Collaborative Computing; UVA and Traffic system; Recommendation System; Recommendation System & Network and Security; Network and Security; Network and Security & IoT and Social Networks; IoT and Social Networks & Images handling and human recognition; Images handling and human recognition & Edge Computing; Edge Computing; Edge Computing & Collaborative working; Collaborative working & Deep Learning and application; Deep Learning and application; Deep Learning and application; Deep Learning and application & UVA. |
| data management conference 2023: Human-Centered Artificial Intelligence Chang S. Nam, Jae-Yoon Jung, Sangwon Lee, 2022-05-18 Human-Centered Artificial Intelligence: Research and Applications presents current theories, fundamentals, techniques and diverse applications of human-centered AI. Sections address the question, are AI models explainable, interpretable and understandable?, introduce readers to the design and development process, including mind perception and human interfaces, explore various applications of human-centered AI, including human-robot interaction, healthcare and decision-making, and more. As human-centered AI aims to push the boundaries of previously limited AI solutions to bridge the gap between machine and human, this book is an ideal update on the latest advances. Presents extensive research on human-centered AI technology Provides different methods and techniques used to investigate human-AI interaction Discusses open questions and challenges in trust within human-centered AI Explores how human-centered AI changes and operates in human-machine interactions |
| data management conference 2023: Proceedings of 2023 China Science and Technology Information Resource Management and Service Annual Conference , 2024 |
| data management conference 2023: Artificial Intelligence-Based System Models in Healthcare A. Jose Anand, K. Kalaiselvi, Jyotir Moy Chatterjee, 2024-10-01 Artificial Intelligence-Based System Models in Healthcare provides a comprehensive and insightful guide to the transformative applications of AI in the healthcare system. This book is a groundbreaking exploration of the synergies between artificial intelligence and healthcare innovation. In an era where technological advancements are reshaping the landscape of medical practices, this book provides a comprehensive and insightful guide to the transformative applications of AI in healthcare systems. From conceptual foundations to practical implementations, the book serves as a roadmap for understanding the intricate relationships between AI-based system models and the evolution of healthcare delivery. The first section delves into the fundamental role of technology in reshaping the healthcare landscape. With a focus on daily life activities, decision support systems, vision-based management, and semantic frameworks, this section lays the groundwork for understanding the pivotal role of AI in revolutionizing traditional healthcare approaches. Each chapter offers a unique perspective, emphasizing the intricate integration of technology into healthcare ecosystems. The second section takes a deep dive into specific applications of AI, ranging from predictive analysis and machine learning to deep learning, image analysis, and biomedical text processing. With a focus on decision-making support systems, this section aims to demystify the complex world of AI algorithms in healthcare, offering valuable insights into their practical implications and potential impact on patient outcomes. The final section addresses the modernization of healthcare practices and envisions the future landscape of AI applications. From medical imaging and diagnostics to predicting ventilation needs in intensive care units, modernizing health record maintenance, natural language processing, chatbots for medical inquiries, secured health insurance management, and glimpses into the future, the book concludes by exploring the frontiers of AI-driven healthcare innovations. Audience This book is intended for researchers and postgraduate students in artificial intelligence and the biomedical and healthcare sectors. Medical administrators, policymakers and regulatory specialists will also have an interest. |
| data management conference 2023: Sigmod/pods '18 Christopher Jermaine, 2018-06-03 SIGMOD/PODS '18: International Conference on Management of Data Jun 03, 2018-Jun 08, 2018 Houston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl. |
| data management conference 2023: Data Management for Researchers Kristin Briney, 2015-09-01 A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline. —Robert Buntrock, Chemical Information Bulletin |
| data management conference 2023: Advancements in Business for Integrating Diversity, and Sustainability Dimitrios A Karras, Srinesh Thakur, Sai Kiran Oruganti, 2024-03-01 This book is the collection of selected articles that appeared at the First International Analytics Conference 2023 held in Hyderabad in virtual mode on February 2nd the 3rd 2023. In the fast-paced, ever-changing world of business, the pursuit of diversity and sustainability has emerged as a dynamic catalyst for progress. This illuminating volume takes you on a journey through the evolving realm of business, where innovative approaches are redefining corporate strategies and values. |
| data management conference 2023: Computational Intelligence T. Ananth Kumar, E. Golden Julie, Venkata Raghuveer Burugadda, Abhishek Kumar, Puneet Kumar, 2024-11-27 This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system’s physiological characteristics and has been implemented numerically for non-linear mapping. Fuzzy Logic Systems simulate the human brain’s psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into computational intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems. |
| data management conference 2023: Information Management and Big Data Juan Antonio Lossio-Ventura, Denisse Muñante, Hugo Alatrista-Salas, 2019 This book constitutes the refereed proceedings of the 5th International Conference on Information Management and Big Data, SIMBig 2018, held in Lima, Peru, in September 2018. The 34 papers presented were carefully reviewed and selected from 101 submissions. The papers address issues such as data mining, artificial intelligence, Natural Language Processing, information retrieval, machine learning, web mining. |
| data management conference 2023: Text Data Management and Analysis ChengXiang Zhai, Sean Massung, 2016-06-30 Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data. |
| data management conference 2023: In-Memory Data Management Hasso Plattner, Alexander Zeier, 2012-04-17 In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes. |
| data management conference 2023: 18th European Conference on Management, Leadership and Governance Martin Rich, 2023-11-23 These proceedings represent the work of contributors to the 19th European Conference on Management Leadership and Governance (ECMLG 2023) hosted by ACI and Bayes Business School, City, University of London, UK on 23 - 24 November 2023. The Conference Chair is Dr Martin Rich from Bayes Business School, City, University of London, UK. ECMLG is now a well-established event on the academic research calendar and now in its 19th year. The key aim remains the opportunity for participants to share ideas and meet the people who hold them. The scope of papers will ensure an interesting two days. The subjects covered illustrate the wide range of topics that fall into this important and ever-growing area of research. The opening keynote presentation is given by Dr Jeffrey Ridley, PhD, FCG, FIIA, CIA, on the topic of A lifetime of Management and Governance Learning: A wish for you all. The second day of the conference Keynote presentation is given by Professor Pumela Msweli, University of South Africa, on the topic of The Leadership Dance on a geopolitically entangled dance floor: Towards Unitive Consciousness. With an initial submission of 164 abstracts, after the double blind, peer review process there are 54 Academic Research papers, 11 PhD Research papers, 2 Masters Research papers and 2 work-in-progress papers published in these Conference Proceedings. These papers represent research from China, Czech Republic, Czechia, Egypt, Finland, France, Germany, Ghana, Greece, Hungary, India, Italy, Kenya, Macau, Mexico, Morocco, Netherlands, Norway, Pakistan, Peru, Poland, Portugal, Romania, Saudi Arabia, Scotland, Slovakia, South Africa, Spain, Switzerland, The Netherlands, United Arab Emirates, the UK and the USA. |
| data management conference 2023: Sustainable Production Through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning J. Andersson, S. Joshi, L. Malmsköld, 2024-05-07 Collaboration between those working in product development and production is essential for successful product realization. The Swedish Production Academy (SPA) was founded in 2006 with the aim of driving and developing production research and higher education in Sweden, and increasing national cooperation in research and education within the area of production. This book presents the proceedings of SPS2024, the 11th Swedish Production Symposium, held from 23 to 26 April 2024 in Trollhättan, Sweden. The conference provided a platform for SPA members, as well as for professionals from industry and academia interested in production research and education from around the world, to share insights and ideas. The title and overarching theme of SPS2024 was Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning, and the conference emphasized stakeholder value, the societal role of industry, worker wellbeing, and environmental sustainability, in alignment with the European Commission's vision for the future of manufacturing. The 59 papers included here were accepted for publication and presentation at the symposium after a thorough review process. They are divided into 6 sections reflecting the thematic areas of the conference, which were: sustainable manufacturing, smart production and automation, digitalization for efficient product realization, circular production, industrial transformation for sustainability, and the integration of education and research. Highlighting the latest developments and advances in automation and sustainable production, the book will be of interest to all those working in the field. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
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Belmont Forum
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