) during the COVID-19 pandemic, utilizing data-centric approaches and the ARMA-GARCH vine copula-based conditional value … sector-based portfolio demonstrates better diversification during the COVID-19 crisis than the other two data-centric …

Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance … Business and Information Systems Engineering (BISE) to data-centric AI. The paper defines relevant terms, provides key … characteristics to contrast the paradigm of data-centric AI with the model-centric one, and introduces a framework to illustrate the …

high-quality data. Data-centric AI is an emerging approach for solving machine learning (ML) problems. It is a collection … used in an ML pipeline. However, data-centric AI approaches are not well documented. Researchers have conducted various … experiments without a clear set of guidelines. This survey highlights six major data-centric AI aspects that researchers are …

An Introduction to Data Dominance -- The Digital Data-Centric Enterprise: Case Studies -- The Product Strategy -- The … Data Strategy -- Data: Organizing the Data Ecosystem -- Process: Building Digital Data-Centric Products -- Culture … infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions …

, coined as Legal Logistics, aims at unifying and embodying different data-centric services that exploit available and relevant … scope of data-centric services in legal systems. Such a unified view of data-centric services, enables the authors to relate … these services to each other and to their operational context, and better streamline data-centric based innovations in legal …