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Data science for social good = phila...

Lapucci, Massimo.

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Data science for social good = philanthropy and social impact in a complex world /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science for social good/ edited by Massimo Lapucci, Ciro Cattuto.
Reminder of title:	philanthropy and social impact in a complex world /
other author:	Lapucci, Massimo.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xii, 99 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- The Value of Data and Data Collaboratives for Good: A Roadmap for Philanthropies to Facilitate Systems Change through Data -- UN Global Pulse: A UN Innovation Initiative with a Multiplier Effect -- Building the Field of Data for Good -- When Philanthropy Meets Data Science: A Framework for Governance to Achieve Data-Driven Decision-Making for Public Good -- Data for Good: Unlocking Privately-Held Data to the Benefit of the Many -- Building a Funding Data Ecosystem: Grantmaking in the UK -- A Reflection on the Role of Data for Health: COVID-19 and Beyond.
Contained By:	Springer Nature eBook
Subject:	Decision making - Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-030-78985-5
ISBN:	9783030789855

Data science for social good = philanthropy and social impact in a complex world /
Data science for social goodphilanthropy and social impact in a complex world /[electronic resource] :edited by Massimo Lapucci, Ciro Cattuto. - Cham :Springer International Publishing :2021. - xii, 99 p. :ill., digital ;24 cm. - SpringerBriefs in complexity,2191-5334. - SpringerBriefs in complexity..

Introduction -- The Value of Data and Data Collaboratives for Good: A Roadmap for Philanthropies to Facilitate Systems Change through Data -- UN Global Pulse: A UN Innovation Initiative with a Multiplier Effect -- Building the Field of Data for Good -- When Philanthropy Meets Data Science: A Framework for Governance to Achieve Data-Driven Decision-Making for Public Good -- Data for Good: Unlocking Privately-Held Data to the Benefit of the Many -- Building a Funding Data Ecosystem: Grantmaking in the UK -- A Reflection on the Role of Data for Health: COVID-19 and Beyond.

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact - identifying a social need, targeting an intervention, measuring impact - and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

ISBN: 9783030789855

Standard No.: 10.1007/978-3-030-78985-5doiSubjects--Topical Terms:

750247
Decision making
--Statistical methods.

LC Class. No.: HD30.23 / .D37 2021

Dewey Class. No.: 658.403

Data science for social good = philanthropy and social impact in a complex world /
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505 0 $a Introduction -- The Value of Data and Data Collaboratives for Good: A Roadmap for Philanthropies to Facilitate Systems Change through Data -- UN Global Pulse: A UN Innovation Initiative with a Multiplier Effect -- Building the Field of Data for Good -- When Philanthropy Meets Data Science: A Framework for Governance to Achieve Data-Driven Decision-Making for Public Good -- Data for Good: Unlocking Privately-Held Data to the Benefit of the Many -- Building a Funding Data Ecosystem: Grantmaking in the UK -- A Reflection on the Role of Data for Health: COVID-19 and Beyond.
520 $a This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact - identifying a social need, targeting an intervention, measuring impact - and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.
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