Development Research in Practice

Development Research in Practice

Author: Kristoffer Bjärkefur

Publisher: World Bank Publications

Published: 2021-07-16

Total Pages: 388

ISBN-13: 1464816956

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Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University


Information Systems for Business and Beyond

Information Systems for Business and Beyond

Author: David T. Bourgeois

Publisher:

Published: 2014

Total Pages: 167

ISBN-13:

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"Information Systems for Business and Beyond introduces the concept of information systems, their use in business, and the larger impact they are having on our world."--BC Campus website.


Automatic Design of Data Processing Systems

Automatic Design of Data Processing Systems

Author: Gregory R. Ruth

Publisher:

Published: 1976

Total Pages: 25

ISBN-13:

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The design of data organization and data accessing procedures for data processing systems operating on large keyed files of data is a common and recurrent activity in modern data processing applications. A considerable amount of understanding and expertise in this area has been developed and it is time to begin codifying and automating this process. It should be possible to develop a system where the user has merely to specify the characteristics of his data objects and their interrelations and the system will automatically determine the data organizations and accessing procedures that are optimal for his application. The optimizer for Protosystem I (an automatic programming system prototype at MIT) provides an example of how such automation can be accomplished.