Design of an innovative IT platform for analytics knowledge management

Rabhi, FA; Bandara, M; Lu, K; Dewan, S

Design of an innovative IT platform for analytics knowledge management

Rabhi, FA Bandara, M Lu, K Dewan, S

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Future Generation Computer Systems, 2021, 116, pp. 209-219
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Rabhi, FA
dc.contributor.author	Bandara, M
dc.contributor.author	Lu, K
dc.contributor.author	Dewan, S
dc.date.accessioned	2022-04-12T23:07:11Z
dc.date.available	2022-04-12T23:07:11Z
dc.date.issued	2021
dc.identifier.citation	Future Generation Computer Systems, 2021, 116, pp. 209-219
dc.identifier.issn	0167-739X
dc.identifier.issn	1872-7115
dc.identifier.uri	http://hdl.handle.net/10453/156157
dc.description.abstract	An organisation wishing to conduct data analytics to support day-to-day decision making often needs a system to help analysts represent and maintain knowledge about research variables, datasets or analytical models, and effectively determine the best combination to use when solving the problem at hand. Often, such knowledge is not explicitly captured by the organisation. To address this problem, this paper presents the design of an innovative Information Technology (IT) platform which enables data sharing between different analytics models and provides the ability to extend or customise models or data sources without necessarily involving the analysts who created them. It can make analytics knowledge readily available and modifiable for future use and problem-solving by analysts and other stakeholders. In the context of our work, we organise analytics knowledge around the concept of a research variable, which analysts often use when defining and proving a hypothesis. By focusing on such a concept, this platform is particularly suited to develop empirical data analytics applications in any domain. This paper presents the architecture of this platform, including the knowledge base and the Application Programming Interface (API) layer. Capabilities of this platform are illustrated through a software prototype and a use case on property price prediction across Sydney, Australia.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Future Generation Computer Systems
dc.relation.isbasedon	10.1016/j.future.2020.10.022
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems
dc.subject.classification	Distributed Computing
dc.title	Design of an innovative IT platform for analytics knowledge management
dc.type	Journal Article
utslib.citation.volume	116
utslib.for	0803 Computer Software
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2022-04-12T23:07:09Z
pubs.publication-status	Published
pubs.volume	116

Abstract:

An organisation wishing to conduct data analytics to support day-to-day decision making often needs a system to help analysts represent and maintain knowledge about research variables, datasets or analytical models, and effectively determine the best combination to use when solving the problem at hand. Often, such knowledge is not explicitly captured by the organisation. To address this problem, this paper presents the design of an innovative Information Technology (IT) platform which enables data sharing between different analytics models and provides the ability to extend or customise models or data sources without necessarily involving the analysts who created them. It can make analytics knowledge readily available and modifiable for future use and problem-solving by analysts and other stakeholders. In the context of our work, we organise analytics knowledge around the concept of a research variable, which analysts often use when defining and proving a hypothesis. By focusing on such a concept, this platform is particularly suited to develop empirical data analytics applications in any domain. This paper presents the architecture of this platform, including the knowledge base and the Application Programming Interface (API) layer. Capabilities of this platform are illustrated through a software prototype and a use case on property price prediction across Sydney, Australia.

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http://hdl.handle.net/10453/156157