Data governance: Organizing data for trustworthy Artificial Intelligence

The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements. However, they all rely on data which is not only big, open and linked but varied, dynamic and streamed at high speeds in real-time. Managing such data is challenging. To overcome such challenges and utilize opportunities for BDAS, organizations are increasingly developing advanced data governance capabilities. This paper reviews challenges and approaches to data governance for such systems, and proposes a framework for data governance for trustworthy BDAS. The framework promotes the stewardship of data, processes and algorithms, the controlled opening of data and algorithms to enable external scrutiny, trusted information sharing within and between organizations, risk-based governance, system-level controls, and data control through shared ownership and self-sovereign identities. The framework is based on 13 design principles and is proposed incrementally, for a single organization and multiple networked organizations.NORTE-01-0145- FEDER-000037

Police performance measurement: an annotated bibliography

This study provides information to assist those involved in performance measurement in police organisations. The strategies used to identify the literature are described. Thematic sections cover; general overviews; methodological issues; performance management in other industries; national, international and cross-national studies; frameworks (e.g. Compstat; the Balanced Scorecard); criticisms (particularly unintended consequences); crime-specific measures; practitioner guides; performance evaluation of individual staff; police department plans and evaluations; annotated bibliographies in related areas, and; other literature. Our discussion offers two conclusions: the measures best aligned with performance are typically more expensive, while most operational data should only provide contextual information; the philosophy of open governance should be pursued to promote transparency, accountability and communication to improve police performance

Performance measurement in the public sector: evaluating performance measurement and reporting in health

Abstract not available

Examining CSR Disclosure Strategies Within the Australian Food and Beverage Industry

This study examines intra-industry variation in CSR disclosure practice. Specifically, it investigates whether companies from industry sub-sectors with different CSR profiles have varying patterns of CSR disclosure. The industry analysed is the Australian food and beverage industry. The paper finds that companies from industry sub-sectors with higher CSR profiles engage in greater ‘symbolic’ disclosures. Further, the relationship between CSR profile and disclosure strategy was found to be influenced also by the centrality of the CSR issue under examination to the company’s business. While the small sample size limits generalisability, these findings have implications for both CSR research and practice