Research and application of data management based on Data Management Maturity Model (DMM)
Open accessAbstract
Through the analysis and contrast of the different Data Management Maturity Model, such as DCAM, DMM, DCMM and the model of IBM, we try to make empirical research under the framework of data management maturity model. This article take a project whose main research object is about the academic career of scientists and with massive unstructured data for example, through analysis of the goal, management processes and influence factors of this project in detail, we built up an evaluation system for data management for such projects under the framework of DCMM. It is expected to have a positive significance to the evaluation of similar data management capability.
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Despite recent regulations on explainable AI, traceability is not yet shortlisted in the data quality framework used by the UK government.
“despite recent regulations on explainable AI (XAI) 6 , traceability is not yet shortlisted in the data quality framework used by the UK government 7”
From A Survey of Data Quality Requirements That Matter in ML Development Pipelines (2023) · cites this paper as [7]
Section 2.2 discusses China's Data Capability Maturity Model, and the Conclusion describes a model for data about Chinese scientists. Searches for traceability and a UK-government data quality framework found no passage addressing whether traceability is included in such a framework. (LLM, conf=0.76)
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Cites
The Fourth Paradigm – Data-Intensive Scientific Discovery
Hey, T. (2012) · Communications in computer and information science · doi:10.1007/978-3-642-33299-9_1 · Cited by 1,598 · see citing works
The Fourth Paradigm: Data-Intensive Scientific Discovery
Buchan, I. E., Winn, J. M., & Bishop, C. (2009) · Cited by 1,428 · see citing works
A Hybrid Data Center Architecture for Big Data
Rahman, M. N., & Esmailpour, A. (2016) · Big Data Research · doi:10.1016/j.bdr.2016.02.001 · Cited by 28 · see citing works
The IBM Data Governance Unified Process: Driving Business Value with IBM Software and Best Practices
Soares, S. (2010) · Cited by 20 · see citing works
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Research works printed but not linked: 1
- [3]3. LI B, BIN J Z. Data management capability maturity model[J]. Big Data Research, 2017, 3(4): 29-36.
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A Survey of Data Quality Requirements That Matter in ML Development Pipelines
Priestley, M., O’donnell, F., & Simperl, E. (2023) · Journal of Data and Information Quality · doi:10.1145/3592616 · Cited by 86 · see citing works
- Authors
- Baolong, Y., Hong, W., & Haodong, Z.
- Affiliations
- China Association for Science and Technology (CN)
- National Academy of Innovation Strategy, CAST, Beijing
- Venue
- Proceedings of the 2018 10th International Conference on Machine Learning and Computing
- Publisher
- ACM
- Published
- 2018-02-26
- Pages
- 157-160
- OpenAlex
- W2805438023
- Cited by
- 13
- References
- 4
- Citations by year
- 2025: 5 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 2
- FWCI
- 0.39
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Machine Learning and Computing (ICMLC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Keywords
- data management maturity model, unstructured data, data management processes
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