| data quality assessment checklist: Data quality assurance. Module 3. Site assessment of data quality World Health Organization, 2023-01-17 This publication is one of the three module toolkit and provide technical guidance and tools to support the work on strengthening data quality in countries. This is part of the Division of Data, Analytics and Delivery for Impact’s scope of work providing normative guidance for health information system strengthening. |
| data quality assessment checklist: Data quality assurance. Module 1. Framework and metrics World Health Organization, 2023-02-14 |
| data quality assessment checklist: The Practitioner's Guide to Data Quality Improvement David Loshin, 2010-11-22 The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. - Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. - Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. - Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. |
| data quality assessment checklist: WHO Data quality assessment of national and partner monitoring data and system implementation tool Second edition. World Health Organization, 2024-04-17 This technical brief summarizes key updates to the 2018 Data quality assessment of national and partner HIV treatment and patient monitoring data and systems implementation tool focusing on implementing and following up remedial activities after such assessments and guidance on developing data quality improvement strategies. It is intended that this technical update is used alongside the 2018 implementation tool to support country implementation of data quality assessments. This technical brief provides further guidance and recommendations on the following: - developing a follow-up action plan after conducting data quality assessment to support the implementation of remedial actions; - disseminating, notifying and reporting data quality assessment results; - using data quality assessment results to adjust national HIV estimates; and - implementing data quality improvement activities at the site level that link data quality assessment to broader data quality improvement activities to address data quality issues and strengthen data use. |
| data quality assessment checklist: Exploratory Data Mining and Data Cleaning Tamraparni Dasu, Theodore Johnson, 2003-08-01 Written for practitioners of data mining, data cleaning and database management. Presents a technical treatment of data quality including process, metrics, tools and algorithms. Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge. Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches. Uses case studies to illustrate applications in real life scenarios. Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques. Exploratory Data Mining and Data Cleaning will serve as an important reference for serious data analysts who need to analyze large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large scale data analys is and data mining. |
| data quality assessment checklist: Data Science Thinking Longbing Cao, 2018-08-17 This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. |
| data quality assessment checklist: Module for assessing and strengthening the quality of viral load testing data within HIV programmes and patient monitoring systems: implementation tool, Second edition World Health Organization, 2024-03-26 This technical update of the 2020 viral load data quality module provides further guidance on the recommended data quality assurance activities, updated web annexes to support country implementation, and generic budgets for viral load testing data quality monitoring activities. These are part of ongoing efforts to standardize approaches to ensure that accurate and timely HIV viral load testing data and results are available for both clinical use and to strengthen programme monitoring. This aligns with recommendations outlined in the 2022 WHO Consolidated guidelines on person-centred HIV strategic information on data quality assessment and improvement. The updated guidance on the priority indicators and the key elements of data quality include: - Key indicators to be included in data quality monitoring activities; - Main activities to be included in the viral load testing data quality assessment process; - The calculation of viral load test turnaround times; - Considerations for data quality assessments for sites with electronic data systems; - Sampling for national data quality assessments of sites and clinical records; - Data quality monitoring via lot-quality assurance sampling; - Considerations for facilities with point-of-care or near point-of-care viral load testing; - Considerations for data quality assessments of viral load testing data for pregnant and breastfeeding women; and - Recording the limitations and challenges of data quality monitoring assurance activities. |
| data quality assessment checklist: Guidance for quality assurance project plans , |
| data quality assessment checklist: Quality and Safety in Radiation Oncology Adam P. Dicker, MD, PhD, Eric C. Ford, PhD, Tim R. Williams, MD, 2016-08-17 Quality and Safety in Radiation Oncology is the first book to provide an authoritative and evidence-based guide to the understanding and implementation of quality and safety procedures in radiation oncology practice. Alongside the rapid growth of technology and radiotherapy treatment options for cancer in recent years, quality and safety standards are not only of the utmost importance but best practices ensuring quality and safety are crucial aspect of modern radiation oncology training. A detailed exploration and review of these standards is a necessary part of radiation oncologist’s professional competency, both in the clinical setting and at the study table while preparing for board review and MOC exams. Chapter topics range from fundamental concepts of value and quality to commissioning technology and the use of metrics. They include perspectives on quality and safety from the patient, third-party payers, as well as from the federal government. Other chapters cover prospective testing of quality, training and education, error identification and analysis, incidence reporting, as well as special technology and procedures, including MRI-guided radiation therapy, proton therapy and stereotactic body radiation therapy (SBRT), quality and safety procedures in resource-limited environments, and more. State-of-the-art quality assurance procedures and safety guidelines are the backbone of this unique and essential volume. Physicians, medical physicists, dosimetrists, radiotherapists, hospital administrators, and other healthcare professionals will find this resource an invaluable compendium of best practices in radiation oncology. Key Features: Case examples illustrate best practices and pitfalls Several dozen graphs, tables and figures help quantify the discussion of quality and safety throughout the text Section II covers all aspects of quality assurance procedures for the physicist |
| data quality assessment checklist: How to be FAIR with Your Data Claudia Engelhardt, Raisa Barthauer, Katarzyna Biernacka, Aoife Coffey, Ronald Cornet, Alina Danciu, Yuri Demchenko, Stephen Downes, Christopher Erdmann, Federica Garbuglia, Kerstin Germer, Kerstin Helbig, Margareta Hellström, Kristina Hettne, Dawn Hibbert, Mijke Jetten, Yulia Karimova, Karsten Kryger Hansen, Mari Elisa Kuusniemi, Viviana Letizia, Valerie McCutcheon, Barbara McGillivray, Jenny Ostrop, Britta Petersen, Ana Petrus, Stefan Reichmann, Najla Rettberg, Carmen Reverté, Nick Rochlin, Bregt Saenen, Birgit Schmidt, Jolien Scholten, Hugh Shanahan, Armin Straube, Veerle Van den Eynden, Justine Vandendorpe, Shanmugasundaram Venkataram, André Vieira, Cord Wiljes, Ulrike Wuttke, Joanne Yeomans, Biru Zhou, 2022 This handbook was written and edited by a group of about 40 collaborators in a series of six book sprints that took place between 1 and 10 June 2021. It aims to support higher education institutions with the practical implementation of content relating to the FAIR principles in their curricula, while also aiding teaching by providing practical material, such as competence profiles, learning outcomes, lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021. |
| data quality assessment checklist: Principles of Data Quality Arthur D. Chapman, 2005 |
| data quality assessment checklist: Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields Leanne Marie Kmet, Robert C. Lee (M.Sc.), Alberta Heritage Foundation for Medical Research, 2004 This paper arose in response to a gap in the literature and a need on the part of health science researchers for a standard reproducible criteria for simultaneously critically appraising the quality of a wide range of studies. The paper is meant to stimulate discussion about how to further advance the capacity of researchers to effectively conduct the critical appraisals. It is hoped that researchers will continue to test the validity of and refine the Qualsyst tool which is described in this paper. |
| data quality assessment checklist: Quality assurance project plan for analytical control and assessment activities in the national study of chemical residues in lake fish tissue , |
| data quality assessment checklist: Situational assessment checklist to guide implementation of the global strategy for tuberculosis research and innovation , 2021-03-23 Research along its full spectrum is critical for developing new tools and strategies for better tuberculosis (TB) prevention, diagnosis, treatment and care and to provide scientific evidence for programmes, practitioners and policy-makers working to alleviate morbidity and mortality from TB. Under the leadership of WHO, a global strategy for TB research and innovation was developed and adopted by Member States in 2020 to advance research and innovation, by translating political commitments made in the Moscow Declaration to End TB (2017) and the political declaration at the United Nations high-level meeting on TB (2018) into concrete actions. The present document is a checklist that allows for a robust analysis of the current situation at country level, to build an evidence base for prioritizing the implementations of the recommendations made in the global strategy through changes in policies, programmes and interventions. It is designed as a reference for ministries of health and other entities responsible for overseeing the implementation of the global strategy. |
| data quality assessment checklist: Executing Data Quality Projects Danette McGilvray, 2021-05-27 Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. - Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach - Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book - Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices - A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online |
| data quality assessment checklist: RealWorld Evaluation Michael Bamberger, Jim Rugh, Linda Mabry, 2011-11-29 This book addresses the challenges of conducting program evaluations in real-world contexts where evaluators and the agencies face budget and time constraints and where critical data is missing. The book is organized around a seven-step model developed by the authors, which has been tested and refined in workshops. Vignettes and case studies—representing evaluations from a variety of geographic regions and sectors—demonstrate adaptive possibilities for small projects with budgets of a few thousand dollars to large-scale, long-term evaluations. The text incorporates quantitative, qualitative, and mixed-method designs and this Second Edition reflects important developments in the field over the last five years. |
| data quality assessment checklist: Global guidance on criteria and processes for validation , 2021-11-26 The global community has committed to elimination of mother-to-child transmission, or vertical transmission, of HIV, syphilis and hepatitis B virus (HBV) as a public health priority and reducing global disease burden, quality reproductive, maternal and child health services to a level no longer a public health concern. Achieving and maintaining elimination requires strong political and public health commitment. Strengthened, resilient health systems improve a broad range of services and outcomes while similarities in prevention interventions add to the benefit of an integrated approach. Validation is an attestation that a country has successfully met standard criteria for elimination, or for being at one of the 3 levels of achievement on the ‘Path to Elimination’ while delivering quality services for women, girls and their children, through the life-course, respecting human rights and ensuring gender equality and community engagement. It requires systems that comprehensively identify and monitor new infections and infant outcomes. Establishment of criteria for validation began in 2007 with global consultations while lessons learnt advised publication of 2 editions of global guidance on criteria and processes for validation: elimination of mother-to-child transmission of HIV and syphilis (the ‘Orange Book’). This document, the third version, adds on EMTCT of HBV, bringing together a package of interventions and metrics to support integrated management and monitoring of vertical transmission across a wide range of epidemiological and programmatic contexts. |
| data quality assessment checklist: Artificial Intelligence in Medical Imaging Erik R. Ranschaert, Sergey Morozov, Paul R. Algra, 2019-01-29 This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals. |
| data quality assessment checklist: Data Quality Jack E. Olson, 2003-01-09 Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets. |
| data quality assessment checklist: Assessment of Treatment Plant Performance and Water Quality Data: A Guide for Students, Researchers and Practitioners Marcos von Sperling , Matthew E. Verbyla , Silvia M.A.C Oliveira, 2020-01-15 This book presents the basic principles for evaluating water quality and treatment plant performance in a clear, innovative and didactic way, using a combined approach that involves the interpretation of monitoring data associated with (i) the basic processes that take place in water bodies and in water and wastewater treatment plants and (ii) data management and statistical calculations to allow a deep interpretation of the data. This book is problem-oriented and works from practice to theory, covering most of the information you will need, such as (a) obtaining flow data and working with the concept of loading, (b) organizing sampling programmes and measurements, (c) connecting laboratory analysis to data management, (e) using numerical and graphical methods for describing monitoring data (descriptive statistics), (f) understanding and reporting removal efficiencies, (g) recognizing symmetry and asymmetry in monitoring data (normal and log-normal distributions), (h) evaluating compliance with targets and regulatory standards for effluents and water bodies, (i) making comparisons with the monitoring data (tests of hypothesis), (j) understanding the relationship between monitoring variables (correlation and regression analysis), (k) making water and mass balances, (l) understanding the different loading rates applied to treatment units, (m) learning the principles of reaction kinetics and reactor hydraulics and (n) performing calibration and verification of models. The major concepts are illustrated by 92 fully worked-out examples, which are supported by 75 freely-downloadable Excel spreadsheets. Each chapter concludes with a checklist for your report. If you are a student, researcher or practitioner planning to use or already using treatment plant and water quality monitoring data, then this book is for you! 75 Excel spreadsheets are available to download. |
| data quality assessment checklist: Assessing the National Health Information System Health Metrics Network, World Health Organization, 2008 The Health Metrics Network (HMN) was launched in 2005 to help countries ... improve global health by strengthening the systems that generate health-related information for evidence-based decision-making.--Introd. |
| data quality assessment checklist: Consolidated guidance on tuberculosis data generation and use. Module 1. Tuberculosis surveillance World Health Organization, 2024-04-29 Since 1995, WHO has ensured a consistent approach to national, regional and global TB surveillance by providing standardized definitions, forms and registers for the recording and reporting of individual-level and aggregated data about people diagnosed with and treated for TB, which are used worldwide. This standardization has facilitated the regular reporting of TB data to WHO from 215 countries and areas in annual rounds of global TB data collection, with findings published in an annual WHO global TB report since 1997 and data made publicly available via the online WHO global TB database. The goal of this 2024 edition of WHO guidance on TB surveillance (following the last major update published in 2013) is to ensure the continued worldwide standardization of TB surveillance, in the context of the WHO End TB Strategy, the latest WHO guidelines on TB screening, prevention, diagnosis and treatment, and commitments made at the 2023 UN high-level meeting on TB, while also promoting the establishment or strengthening of digital, case-based TB surveillance that is integrated within the overall public health architecture. This 2024 edition provides a comprehensive and consolidated package, bringing together both updated guidance as well as (within web annexes) closely related WHO products, tools and documentation related to TB surveillance. The web annexes (and associated links to them) are listed below. The package was informed by (and includes a summary of) lessons learned about TB surveillance during more than 100 national TB epidemiological reviews conducted since 2013. |
| data quality assessment checklist: Utilization-Focused Evaluation Michael Quinn Patton, 1986 The second edition of Patton's classic text retains the practical advice, based on empirical observation and evaluation theory, of the original. It shows how to conduct an evaluation, from beginning to end, in a way that will be useful -- and actually used. Patton believes that evaluation epitomizes the challenges of producing and using information in the information age. His latest book includes new stories, new examples, new research findings, and more of Patton's evaluation humour. He adds to the original book's insights and analyses of the changes in evaluation during the past decade, including: the emergence of evaluation as a field of professional practice; articulation of standards for evaluation; a methodological synthesis of the qualitative versus quantitative debate; the tremendous growth of 'in-house' evaluations; and the cross-cultural development of evaluation as a profession. This edition also incorporates the considerable research done on utilization during the last ten years. Patton integrates diverse findings into a coherent framework which includes: articulation of utilization-focused evaluation premises; examination of the stakeholder assumption; and clarification of the meaning of utilization. --Publisher description. |
| data quality assessment checklist: Handbook of Climate Services Walter Leal Filho, Daniela Jacob, 2020-01-17 This book explores climate services, including projections, descriptive information, analyses, assessments, and an overview of current trends. Due to the pressures now being put on the world’s climate, it is vital to gather and share reliable climate observation and projection data, which may be tailored for use by different groups. In other words, it is essential to offer climate services. But despite the growth in the use of these services, there are very few specialist publications on this topic. This book addresses that need. Apart from presenting studies and the results of research projects, the book also offers an overview of the wide range of means available for providing and using climate services. In addition, it features case studies that provide illustrative and inspiring examples of how climate services can be optimally deployed. |
| data quality assessment checklist: 2008 UNAIDS Annual Report Unaids, 2010-03 In November 2007, the Joint United Nations Program on HIV/AIDS (UNAIDS) and the World Health Organization (WHO) published data showing that HIV prevalence has stabilized, even though the number of people living with HIV continues to rise. The following year, a joint UNAIDS, United Nations Children's Fund (UNICEF) and WHO report announced that 3 million people living with HIV were accessing antiretroviral therapy, an unprecedented increase of 1 million from the previous year and a 10-fold increase from five years earlier. |
| data quality assessment checklist: Malaria surveillance assessment toolkit World Health Organization, 2022-08-02 |
| data quality assessment checklist: Finding What Works in Health Care Institute of Medicine, Board on Health Care Services, Committee on Standards for Systematic Reviews of Comparative Effectiveness Research, 2011-07-20 Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research. |
| data quality assessment checklist: Quality Assurance Implementation in Research Labs Akshay Anand, 2021-08-17 This book is a comprehensive and timely compilation of strategy, methods, and implementation of a proof of concept modified quality module of Good Laboratory Practices (GLP). This text provides a historical overview of GLP and related standards of quality assurance practices in clinical testing laboratories as well as basic research settings. It specifically discusses the need and challenges in audit, documentation, and strategies for its implications in system-dependent productivity striving research laboratories. It also describes the importance of periodic training of study directors as well as the scholars for standardization in research processes. This book describes different documents required at various time points of a successful Ph.D and post-doc tenure along with faculty training besides entire lab establishments. Various other areas including academic social responsibility and quality assurance in the developing world, lab orientations, and communication, digitization in data accuracy, auditability and back traceability have also been discussed. This book will be a preferred source for principal investigators, research scholars, and industrial research centers globally. From the foreword by Ratan Tata, India “This book will be a guide for students and professionals alike in quality assurance practices related to clinical research labs. The historical research and fundamental principles make it a good tool in clinical research environments. The country has a great need for such a compilation in order to increase the application of domestic capabilities and technology” |
| data quality assessment checklist: School-Based Observation Amy M. Briesch, Robert J. Volpe, Randy G. Floyd, 2018-01-16 Widely used to assess social–emotional and behavioral referral concerns in grades PreK–12, systematic direct observation is an essential skill for school psychologists and other educators. This accessible book helps practitioners conduct reliable, accurate observations using the best available tools. Chapters present effective coding systems for assessing student classroom behavior, the classroom environment, behavior in non-classroom settings, and behavior in a functional assessment context; also provided are guidelines for developing new codes when an appropriate one does not already exist. Procedures for summarizing, graphing, and interpreting data for different assessment purposes are detailed. In a large-size format for easy photocopying, the book includes 13 reproducible coding forms. Purchasers get access to a Web page where they can download and print the reproducible materials. This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas. |
| data quality assessment checklist: In Silico Toxicology Mark T. D. Cronin, Judith C. Madden, 2010 This book defines the use of computational approaches to predict the environmental toxicity and human health effects of organic chemicals. |
| data quality assessment checklist: Big Data and Innovation in Tourism, Travel, and Hospitality Marianna Sigala, Roya Rahimi, Mike Thelwall, 2019-02-26 This book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism. It also provides a consolidated framework and roadmap summarising the major issues that both researchers and practitioners have to address for effective big data innovation. The book proposes a process-based model to identify and implement big data innovation strategies in tourism. This process framework consists of four major parts: 1) inputs required for big data innovation; 2) processes required to implement big data innovation; 3) outcomes of big data innovation; and 4) contextual factors influencing big data exploitation and advances in big data exploitation for business innovation. |
| data quality assessment checklist: Multidisciplinary Social Networks Research Leon Shyue-Liang Wang, Jason J. June, Chung-Hong Lee, Koji Okuhara, Hsin-Chang Yang, 2014-09-11 This book constitutes the refereed proceedings of the 2014 Multidisciplinary International Social Networks Research, MISNC 2014, held in Kaohsiung, Taiwan, in September 2014. The 37 full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on electronic commerce, e-business management, and social networks; social networks issues on sociology, politics and statistics; information technology for social networks analysis and mining; social networks for global eHealth and bio-medics; security, open data, e-learning and other related topics; intelligent data analysis and its applications. |
| data quality assessment checklist: The Operational Audit Blueprint - Definitions, Internal Audit Programs and Checklists for Success SALIH AHMED ISLAM, 2023-04-09 The Operational Audit Blueprint: Definitions, Internal Audit Programs, and Checklists for Success is an indispensable guide for anyone seeking to improve their organisation's operational processes through operational auditing. This book provides a comprehensive overview of operational auditing, including the tools and techniques used by internal auditors to evaluate operational processes. It also emphasises the importance of audit programs and checklists in achieving success. Contents of the book: FINANCE • Financial reporting • Investments • Accounts payable and receivable • Budgeting & Monitoring • Fixed assets • Tax compliance HR · Human resources · Payroll · Payroll cycle data analytics MANUFACTURING · Planning and production control · Quality control · Maintenance · Safety · ESG SUPPLY CHAIN · Demand Planning · Purchasing · Tendering · Import · Inventory · Third-Party Labour Contractor · Warehouse Management · Purchase-to-Pay Cycle Data Analytics SALES & MARKETING · Sales Management · Sales Performance And Monitoring · Product Development · Pricing And Discount · Promotion And Advertising · Marketing Campaigns · Credit Limits · Export · Order Processing · Customer Relationship Management · Retail · Customer Credit Data Analytics INFORMATION TECHNOLOGY · Business Continuity Management · Data Privacy · Database · It General Controls · It Security Management · It Backup & Recovery · It Vendor Management · It Access Controls · It Asset Management · It Change Management · It Data Management · It Help Desk GENERAL PROCESSES · Contract Management · Project Management · Ethics · Ethical Business Conduct Guidelines · Fraud Prevention Whether you're a business owner, manager, or internal auditor, The Operational Audit Blueprint: Definitions, Internal Audit Programs, and Checklists for Success is an essential resource for achieving operational and financial success through improved operational auditing. With this book, you will be able to identify and address potential issues before they become significant problems, ensuring that your organization's are operating at peak efficiency. |
| data quality assessment checklist: Quality Assurance Handbook for Air Pollution Measurement Systems: Stationary sources specific methods (2 v.) , 1984 |
| data quality assessment checklist: Investing in E-Health: People, Knowledge and Technology for a Healthy Future H. Grain, F. Martin-Sanchez, L.K. Schaper, 2014-08-14 As healthcare organisations and governments look to information technology to capitalise and enhance healthcare, the need for effective investment to update existing technology and provide cost-effective infrastructure for the future becomes clear. The issues of defining success and understanding opportunities are crucial to planning optimum investment and the best use of scarce resources. This book presents papers from the Australian Health Informatics Conference (HIC 2014), held in Melbourne, Australia, in August 2014. With the theme of investing in e-health: people, knowledge and technology for a healthy future, the papers delivered at the conference and included here address the issues of building a future-focused, scalable and adaptable infrastructure and of training the healthcare workforce necessary to support it. Subjects covered include: user participation in ICT development for older adults; interactive patient websites; application areas of multi-user virtual environments in the healthcare context; as well as governance, training and assessing the quality of data in public health information systems. The book will be of interest to all those policy makers and practitioners involved in the planning and implementation of information technology projects as part of the healthcare system. |
| data quality assessment checklist: Practical Techniques for Laboratory Analysis James A. Poppiti, Charles Sellers, 1994-07-27 This book presents a detailed overview of day-to-day operations of laboratories. Commercial laboratories that cater to the environmental community are emphasized. The book is divided into three parts: laboratory management, practical solutions to common laboratory problems, and suggestions for increasing laboratory productivity. |
| data quality assessment checklist: 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 quality assessment checklist: EPA Publications Bibliography United States. Environmental Protection Agency, 1991 |
| data quality assessment checklist: "Oh!" "Ah!" "Wow!" KSN Murthy, Dimple K Sanghvi, 2024-04-22 This book is a comprehensive guide that distills the essence of successful business practices into easily understandable language, reminiscent of wisdom passed down through generations. It aims to equip readers with practical knowledge, offering insights into challenges, perspectives, and solutions without delving into complex statistics, analyses, or intricate management techniques. The focus is on simplifying the understanding of key elements essential for business success. In summary, this book aspires to guide readers in setting up a culture, understanding problems, and preparing for future generations. It emphasizes simple tools that can solve problems without the need for extensive mathematics or statistics. By offering practical and commonsense approaches, the book aims to empower organizations to excel in diverse industries, irrespective of their size or technological prowess. |
| data quality assessment checklist: Improving Healthcare Quality in Europe Characteristics, Effectiveness and Implementation of Different Strategies OECD, World Health Organization, 2019-10-17 This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
