Books

Rethinking digital strategy by shifting from hoarding data to streaming insights

The Insight Economy challenges the assumptions driving how organizations collect, manage, and extract value from data. Ruben Verborgh, a Professor of Computer Science, introduces a framework where value comes not from accumulating data but from streaming insights—paralleling the shift from physical media distribution to on-demand content delivery infrastructure. The book examines mismatches between technological, legal, and economic ideals in current data and AI practices.

Through diagrams, real-world use cases, and concrete examples, the book maps the intersection of technology, law, and economics to show where current data and AI strategies fail and how to redesign them. Rather than prescribing additional tools, Verborgh offers a structural rethinking of data approaches that aligns business incentives with societal values, equipping readers with a practical framework for building data strategies that are technically and economically sound.

Readers will also find:

• A reframing of data and AI through classical economics, replacing extraction with exchange and a zero-sum game with sustainable mutual benefit
• Analysis of how Big Data assumptions create conflicts between technological capability, legal compliance, and economic sustainability
• A detailed comparison of data hoarding versus insight streaming, modeled on the Netflix postal-to-digital business transition
• An insider’s account of the open Web’s tense relationship with app stores and platforms, and what this historical pattern predicts for the AI era
• Use cases demonstrating how the Insight Economy model applies across varied business contexts

Written for business and technology leaders implementing data strategies, The Insight Economy provides a structural framework for moving beyond data accumulation toward insight-driven approaches. Decision-makers seeking to align their organizations’ data practices with the economic reality, legal requirements, and societal values will find a concrete alternative to conventional data thinking.

This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation.

Metadata experts Seth van Hooland and Ruben Verborgh introduce the key concepts of metadata standards and Linked Data and how they can be practically applied to existing metadata, giving readers the tools and understanding to achieve maximum results with limited resources. Readers will learn how to critically assess and use (semi-)automated methods of managing metadata through hands-on exercises within the book and on the accompanying website. Each chapter is built around a case study from institutions around the world, demonstrating how freely available tools are being successfully used in different metadata contexts.

Data is supposed to be the new gold, but how can you unlock the value in your data? Managing large datasets used to be a task for specialists, but you don’t have to worry about inconsistencies or errors anymore. OpenRefine lets you clean, link, and publish your dataset in a breeze. Using OpenRefine takes you on a practical tour of all the features of this well-known data transformation tool. It is a hands-on recipe book that teaches you data techniques by example. Starting from the basics, it gradually transforms you into an OpenRefine expert.

This book will teach you all the necessary skills to handle any large dataset and to turn it into high-quality data for the Web. After you learn how to analyze data and spot issues, we’ll see how we can solve them to obtain a clean dataset. Messy and inconsistent data is recovered through advanced techniques such as automated clustering. We’ll then show extract links from keyword and full-text fields using reconciliation and named-entity extraction. Using OpenRefine is more than a manual: it’s a guide stuffed with tips and tricks to get the best out of your data.