Authors: Stefano Ceri, Anna Bernasconi, Alessia Gagliardi

Funding: This paper was supported by the PNRR-PE-AI FAIR project, funded by the NextGenerationEU
program.

Preprint: here

Abstract: Today’s large knowledge graphs are conceived mainly for supporting search and e-commerce within large companies such as Google or Amazon, with well-crafted knowledge creation rules.
Our recent experience of the COVID-19 pandemic, when knowledge has grown at unprecedented rates and has been often contradictory, inspired us to capture a huge gap in existing concepts and technology:
today’s knowledge management does not adequately support such a disruptive process.
In this article, we propose the design and prototyping of the next generation of knowledge management concepts and systems, which will support domain diversity and scientific evolution as foundational ingredients.
Change management is based on a reactive approach, well-established in database systems, but so far lacking in knowledge systems. We propose the reactive interaction of several knowledge hubs, each developed within a scientific domain and “owner” of a portion of a common knowledge representation. Knowledge is represented as graphs, with nodes and edges; edges may interconnect nodes from different hubs. Most importantly, reactive rules cross the hub’s borders and create the premises for a disciplined knowledge evolution, even under the pressure of crises.
Similar challenges are not restricted to the recent pandemic and can address other crisis scenarios, including the catastrophic consequences of climate change or the recent (r)-evolution in artificial intelligence, studied by several scientific communities, whose management requires complex and controversial choices.