dc.contributor.author |
Marivate, Vukosi N
|
|
dc.contributor.author |
Moorosi, Nyalleng
|
|
dc.date.accessioned |
2019-03-11T06:37:04Z |
|
dc.date.available |
2019-03-11T06:37:04Z |
|
dc.date.issued |
2018-05 |
|
dc.identifier.citation |
Marivate, V.N., Moorosi, N. 2018. Exploring data science for public good in South Africa: evaluating factors that lead to success. Proceedings of 19th Annual International Conference on Digital Government Research: Governance in the Data Age (dg.o’18), 30 May 2018 - 1 June 2018, Delft, Netherlands, 6pp. |
en_US |
dc.identifier.isbn |
978-1-4503-6526-0 |
|
dc.identifier.uri |
http://dgsoc.org/wp-content/uploads/2017/04/DGO2018_Conference-Program.pdf
|
|
dc.identifier.uri |
http://hdl.handle.net/10204/10773
|
|
dc.description |
Copyright: 2018 publication rights licensed to Association for Computing Machinery. |
en_US |
dc.description.abstract |
In the pursuit of public service, governments have to oversee many complex systems. In recent years, data-driven methodologies have been adopted as tools to oversee and enhance service delivery. In this paper we discuss some of the ways that the government of South Africa, and its agencies, has utilised data tools, how it can improve other services by developing products that address those specific needs as well as how it can begin to develop a more enabling ecosystem for the development of these tools and processes. We discuss the current data landscape from the lens of data policy readiness, human capital development and ethics. The paper is a summary of our observations, our successes, aspirations and challenges as we endeavour to contribute to a more data-driven governance. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Association for Computing Machinery |
en_US |
dc.relation.ispartofseries |
Workflow;21373 |
|
dc.subject |
e-Government |
en_US |
dc.subject |
Data science for social good |
en_US |
dc.subject |
Data readiness |
en_US |
dc.subject |
Open data |
en_US |
dc.subject |
Government data |
en_US |
dc.title |
Exploring data science for public good in South Africa: evaluating factors that lead to success |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Marivate, V. N., & Moorosi, N. (2018). Exploring data science for public good in South Africa: evaluating factors that lead to success. Association for Computing Machinery. http://hdl.handle.net/10204/10773 |
en_ZA |
dc.identifier.chicagocitation |
Marivate, Vukosi N, and Nyalleng Moorosi. "Exploring data science for public good in South Africa: evaluating factors that lead to success." (2018): http://hdl.handle.net/10204/10773 |
en_ZA |
dc.identifier.vancouvercitation |
Marivate VN, Moorosi N, Exploring data science for public good in South Africa: evaluating factors that lead to success; Association for Computing Machinery; 2018. http://hdl.handle.net/10204/10773 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Marivate, Vukosi N
AU - Moorosi, Nyalleng
AB - In the pursuit of public service, governments have to oversee many complex systems. In recent years, data-driven methodologies have been adopted as tools to oversee and enhance service delivery. In this paper we discuss some of the ways that the government of South Africa, and its agencies, has utilised data tools, how it can improve other services by developing products that address those specific needs as well as how it can begin to develop a more enabling ecosystem for the development of these tools and processes. We discuss the current data landscape from the lens of data policy readiness, human capital development and ethics. The paper is a summary of our observations, our successes, aspirations and challenges as we endeavour to contribute to a more data-driven governance.
DA - 2018-05
DB - ResearchSpace
DP - CSIR
KW - e-Government
KW - Data science for social good
KW - Data readiness
KW - Open data
KW - Government data
LK - https://researchspace.csir.co.za
PY - 2018
SM - 978-1-4503-6526-0
T1 - Exploring data science for public good in South Africa: evaluating factors that lead to success
TI - Exploring data science for public good in South Africa: evaluating factors that lead to success
UR - http://hdl.handle.net/10204/10773
ER -
|
en_ZA |