Moving away from the strong body of critique of pervasive ?bad data? practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ?good data? practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted conversation on the kinds of futures we want to see, and presents concrete steps on how we can start realizing good data in practice.
But whatever the news has told you about data and technology, think again. Data expert and tech insider Sam Gilbert shows that, actually, this data revolution could be the best thing that ever happened to us.
This book discusses the principles and best practices of dataset creation, and covers basic data types and their related appropriate statistics and visualizations.
In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Too often data has been used--and manipulated--to make policy decisions without much stakeholder input.
Jacobs & Vandendaele indicate that their data are exclusively related to white-collar settings: as the interviews that their students conducted are with managers or senior office staff only, they realize they may well have missed out on ...
We must find a balance between our ability to make and produce identifiable data, the known failure rates of de-identification systems, and our need for policy and technology supported by 'good' data. If we cannot find this balance we ...
This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.
Data quality in the context of this book is the degree of excellence of data to precisely and comprehensively describe the practical situation of interest in an unbiased and complete way. The data must be appropriate to answer the ...
Data is always messy and rarely perfect. You'll get more done if you prioritize having an end-to-end view of data health and accuracy over more granular control. Greg's final piece of advice for data leaders? “Hire good people with ...
The best books occupy precious desk space, dog-eared and highlighted. By this standard, Danette McGilvray's book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted InformationTM, will be absolutely ravaged, ...
Numbers in each cell represent the strength of that relationship, often as a Pearson's correlation coefficient (see Box on page 254). The correlation matrix graph uses the same layout but instead of numbers it uses shapes—often ...