DataHub: Knowledge-based data management for data discovery

1993 ◽  
Author(s):  
Thomas H. Handley ◽  
Y. Philip Li
VINE ◽  
2015 ◽  
Vol 45 (3) ◽  
pp. 344-359 ◽  
Author(s):  
Joyline Makani

Purpose – The purpose of this paper is to synthesize existing research on research data management (RDM), academic scholarship and knowledge management and provide a conceptual framework for an institutional research data management support-system (RDMSS) for systems development, managerial and academic use. Design/methodology/approach – Viewing RDMSS from multiple theoretical perspectives, including data management, knowledge management, academic scholarship and the practice-based perspectives of knowledge and knowing, this paper conceptually explores the systems’ elements needed in the development of an institutional RDM service by considering the underlying data discovery and application issues, as well as the nature of academic scholarship and knowledge creation, discovery, application and sharing motivations in a university environment. Findings – The paper provides general criteria for an institutional RDMSS framework. It suggests that RDM in universities is at the very heart of the knowledge life cycle and is a central ingredient to the academic scholarships of discovery, integration, teaching, engagement and application. Research limitations/implications – This is a conceptual exploration and as a result, the research findings may lack generalisability. Researchers are therefore encouraged to further empirically examine the proposed propositions. Originality/value – The broad RDMSS framework presented in this paper can be compared with the actual situation at universities and eventually guide recommendations for adaptations and (re)design of the institutional RDM infrastructure and knowledge discovery services environment. Moreover, this paper will help to address some of the identified underlying scholarship and RDM disciplinary divides and confusion constraining the effective functioning of the modern day university’s RDM and data discovery environment.


Author(s):  
Joanna Palonka

Nowadays, information has been recognized as a strategic asset of an organization. There are numerous best practices for ensuring good quality data and establishing data management frameworks that are required to provide quality information for the management decision-making process. Unlike most data management studies, which focus on large enterprises and SMEs, this study deals with organizations from the third sector in Poland, comprising e.g. associations, foundations, faith-based organizations, etc. The aim of the chapter is to determine the organizations' maturity level of data management for decision-making processes in management. A survey was conducted to gather data from the organizations. The chapter utilizes samples that were collected from Slaskie Voivodship. The conclusions of the present research can help in creating and implementing a model of the data-driven decision-making process so that the operations of these organizations can be enhanced and improved.


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