scholarly journals Perspective: Data Governance—Making Data Great

ACI Open ◽  
2021 ◽  
Vol 05 (02) ◽  
pp. e80-e83
Author(s):  
Keith F. Woeltje
Keyword(s):  
2019 ◽  
Vol 41 (2) ◽  
pp. 75-106
Author(s):  
Sunyoung Kim ◽  
Byungwoong Kwon

2020 ◽  
pp. I-VIII
Author(s):  
Kristin Weber ◽  
Christiana Klingenberg
Keyword(s):  

2020 ◽  
Author(s):  
Zahra Zandesh

BACKGROUND The complicated nature of cloud computing encompassing internet-based technologies and service models for delivering IT applications, processing capability, storage, and memory space and some notable features motivate organizations to migrate their core businesses to the cloud. Consequently, healthcare organizations are much interested to migrate to this new paradigm despite challenges about security, privacy and compliances issues. OBJECTIVE The present study was conducted to investigate all related cloud compliances in health domain in order to find gaps in this context. METHODS All works on cloud compliance issues were surveyed after 2013 in health domain in PubMed, Scopus, Web of Science, and IEEE Digital Library databases. RESULTS Totally, 36 compliances had been found in this domain used in different countries for a variety of purposes. Initially, all founded compliances were divided into three parts as well as five standards, twenty-eight legislations and three policies and guidelines each of which is presented here by in detail. CONCLUSIONS Then, some main headlines like compliance management, data management, data governance, information security services, medical ethics, and patients' rights were recommended in terms of any compliance or frameworks and their corresponding patterns which should be involved in this domain.


2020 ◽  
Vol 4 (1) ◽  
pp. 122-142
Author(s):  
Inna Kouper ◽  
Anjanette H Raymond ◽  
Stacey Giroux

AbstractMaking decisions regarding data and the overall credibility of research constitutes research data governance. In this paper, we present results of an exploratory study of the stakeholders of research data governance. The study was conducted among individuals who work in academic and research institutions in the US, with the goal of understanding what entities are perceived as making decisions regarding data and who researchers believe should be responsible for governing research data. Our results show that there is considerable diversity and complexity across stakeholders, both in terms of who they are and their ideas about data governance. To account for this diversity, we propose to frame research data governance in the context of polycentric governance of a knowledge commons. We argue that approaching research data from the commons perspective will allow for a governance framework that can balance the goals of science and society, allow us to shift the discussion toward protection from enclosure and knowledge resilience, and help to ensure that multiple voices are included in all levels of decision-making.


Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 91
Author(s):  
Jaime Manning ◽  
Deborah Power ◽  
Amy Cosby

The five freedoms and, more recently, the five domains of animal welfare provide internationally recognised frameworks to evaluate animal welfare practices which recognise both the physical and mental wellbeing needs of animals, providing a balanced view of their ability to cope in their environment. Whilst there are many techniques to measure animal welfare, the challenge lies with how best to align these with future changes in definitions and expectations, advances in science, legislative requirements, and technology improvements. Furthermore, enforcement of current animal welfare legislation in relation to livestock in Australia and the reliance on self-audits for accreditation schemes, challenges our ability to objectively measure animal welfare. On-animal sensors have enormous potential to address animal welfare concerns and assist with legislative compliance, through continuous measurement and monitoring of an animal’s behavioural state and location being reflective of their wellbeing. As reliable animal welfare measures evolve and the cost of on-animal sensors reduce, technology adoption will increase as the benefits across the supply chain are realised. Future adoption of on-animal sensors by producers will primarily depend on a value proposition for their business being clear; algorithm development to ensure measures are valid and reliable; increases in producer knowledge, willingness, and trust in data governance; and improvements in data transmission and connectivity.


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