Data science for social good : philanthropy and social impact in a complex / Massimo Lapucci, Ciro Cattuto, editors.

Format:

Book

Contributor:

Lapucci, Massimo, editor.

Cattuto, Ciro, editor.

Series:

SpringerBriefs in complexity 2191-5334

SpringerBriefs in complexity, 2191-5334

Language:

English

Subjects (All):

Decision making--Statistical methods.

Decision making.

Social service--Statistical methods.

Social service.

Social service--Data processing.

Genre:

Electronic books.

Physical Description:

1 online resource.

Place of Publication:

Cham, Switzerland : Springer, 2021.

System Details:

text file

Summary:

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.

Contents:

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.

Notes:

Online resource; title from PDF title page (SpringerLink, viewed October 22, 2021).

ISBN:

9783030789855

3030789853

OCLC:

1276850060

Access Restriction:

Restricted for use by site license.