PolicyCLOUD: A prototype of a cloud serverless ecosystem for policy analytics

Abstract

We present PolicyCLOUD: a prototype for an extensible serverless cloud-based system that supports evidence-based elaboration and analysis of policies. PolicyCLOUD allows flexible exploitation and management of policy-relevant dataflows, by enabling the practitioner to register datasets and specify a sequence of transformations and/or information extraction through registered ingest functions. Once a possibly transformed dataset has been ingested, additional insights can be retrieved by further applying registered analytic functions to it. PolicyCLOUD was built as an extensible framework toward the creation of an analytic ecosystem. As of now, we have developed several essential ingest and analytic functions that are built-in within the framework. They include data cleaning, enhanced interoperability, and sentiment analysis generic functions; in addition, a trend analysis function is being created as a new built-in function. PolicyCLOUD has also the ability to tap on the analytic capabilities of external tools; we demonstrate this with a social dynamics tool implemented in conjunction with PolicyCLOUD, and describe how this stand-alone tool can be integrated with the PolicyCLOUD platform to enrich it with policy modeling, design and simulation capabilities. Furthermore, PolicyCLOUD is supported by a tailor-made legal and ethical framework derived from privacy/data protection best practices and existing standards at the EU level, which regulates the usage and dissemination of datasets and analytic functions throughout its policy-relevant dataflows. The article describes and evaluates the application of PolicyCLOUD to four families of pilots that cover a wide range of policy scenarios.

Keywords

• algorithm bias
• cloud-based analytics
• evidence-based policy practice
• management of data for policies
• privacy and data protection