Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Research Article: 2021 Vol: 24 Issue: 3

Data governance and its scientific outlook in Indonesia: A literature review

Adi Firman Ramadhan, University of Malaya and Universitas Diponegoro

Noor Ismawati Jaafar, University of Malaya

Farzana Parveen Tajudeen, University of Malaya

Citation Information: Ramadhan, A. F., Jaafar, N. I., & Tajudeen, F. P. (2021). Data governance and its scientific outlook in Indonesia: A literature review. Journal of Management Information and Decision Sciences, 24(3), 1-10.

Abstract

Data is a crucial asset in every organization nowadays. Data governance is needed to manage and control data. The development and implementation of data governance in Indonesia are fascinating. This paper aims to find the trending topic of data governance study in Indonesia. This paper used a literature review method to find trending topics.

In Indonesia, data governance has been discussed in topics: the data governance design/model, data governance maturity, and data governance's relationship with other variables. Most of the study was looking at data governance in government institutions. For future research in data governance in Indonesia, more research on the impact of data governance is challenging. Furthermore, identify the relationship of data governance with other variables such as data quality, data security, and the performance also engaging to be studied. Besides, the study on data governance in other institutions such as higher education, hospital, the financial industry, and other service organization also has an opportunity.

Keywords

Data governance; Indonesia; Literature review.

Introduction

Data becomes an essential asset in the organization. Organizations should appropriately manage their data since data is an asset (Khatri & Brown, 2010; Ladley, 2020). Effective data governance can solve data problems (Al-Ruithe et al., 2018). Data governance can be defined as "the policies and processes that continually work to improve and ensure the availability, accessibility, quality, consistency, auditability, and security of data in a company or institution" (Schmidt & Lyle, 2010). Many studies have discussed data governance for more than a decade.

"Data Governance always has been a complicated issue for most organizations" (Zaino, 2020). Better data governance practices could help the government handle complex rapid change faces (Findie et al., 2016). Indonesia faces complex development challenges as a developing country, which means the government needs better data governance. Identifying research topics on data governance in Indonesia is essential since data governance becoming word wide issue. Moreover, based on the Scopus database, scholars from many countries such as the United States, the United Kingdom, and some countries in Asia, including Indonesia, have studied data governance. Figure 1 shows the countries' network analysis by VOS Viewer software.

Figure 1 Country Network Analysis by VOS Viewer

Hence, this paper will describe data governance research topics in Indonesia and potential further research on data governance. This study aims to find data governance research topics in Indonesia. This study is a literature review study using Scopus and Web of Science (WoS) as database resources and Google Scholar as another resource.

Data Sources and Methodology

This comprehensive literature review has involved extensive note-taking highlighting any possible references to data governance and Indonesia. Articles containing references to data governance are then analyzed in more depth for finding the research topics. Part of this analysis involves differentiating and combining the collected data (Miles & Huberman, 1994). Emphasis is placed not on the words themselves but on the meaning of the words. Therefore, regardless of the description, all data governance is recorded to understand that the sorting stage will begin to place data governance in a similar category.

The analysis level can be a signal word, a set of words, phrases, or an entire document (Finney & Corbett, 2007). In this study, data governance and Indonesia are a set of words that become a keyword for sorting the articles from the database resource. After papers were sorted, the articles were reviewed based on the abstract and author keywords before analyzing them. Figure 2 shows the research procedure in this study.

Figure 2 Research Procedures

Result and Discussion

This study aims to identify and categorize the literature that explicitly mentions data governance researched in Indonesia. To identify and classify data governance topics, this study following some procedures as shown on the PRISMA diagrams (Figure 3) and is explained below.

Figure 3 Prisma Diagram

First, this study decided to use data governance and Indonesia to identify articles from the databases. Scopus and WoS were used as database resources and Google Scholar as another resource.Second, finding articles on Scopus, Wos, and Google Scholar using keywords data governance and Indonesia. Twenty-one articles were found in this step, consisting of nine papers found in Scopus, four papers also found in WoS, and twelve articles found in Google Scholar. Table 1 gives detail information about each founded article. These articles were published from 2010 until 2020 in various conference proceedings and journals. Most of the articles published in the conference proceedings, such as:

Table 1 Papers Resulting from each Database on the 10th September 2020
No Authors Title Year Publish in Sources
1 Aisyah M., Ruldeviyani Y. Designing data governance structure based on data management body of knowledge (DMBOK) Framework: A case study on Indonesia deposit insurance corporation (IDIC) 2019 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 Scopus and WoS
2 Saputra D.A., Handika D., Ruldeviyani Y. Data Governance Maturity Model (DGM2) Assessment in organization transformation of digital telecommunication company: Case study of PT Telekomunikasi Indonesia 2019 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 Scopus and WoS
3 Putro B.L., Surendro K., Herbert H. Leadership and culture of data governance for the achievement of higher education goals (Case study: Indonesia University of Education) 2016 AIP Conference Proceedings Scopus and WoS
4 Tallis H., Levin P.S., Ruckelshaus M., Lester S.E., McLeod K.L., Fluharty D.L., Halpern B.S. The many faces of ecosystem-based management: Making the process work today in real places 2010 Marine Policy Vol. 34, Issue 2, 2010 Scopus and WoS
5 Wibowo S., Sandikapura T. Improving Data Security, Interoperability, and Veracity using Blockchain for One Data Governance, Case Study of Local Tax Big Data 2019 Proceeding - 2019 International Conference on ICT for Smart Society: Innovation and Transformation Toward Smart Region, ICISS 2019 Scopus
6 Utama R.P., Purwandari B., Satria R., Kumaralalita L. Open government maturity measurement on social media usage: The ministry of foreign affairs in Indonesia case study 2019 ACM International Conference Proceeding Series Scopus
7 Maulina J., Ruldeviyani Y. Data Governance and Data Architecture for the Ministry of Foreign Affairs of the Republic of Indonesia 2019 Proceedings of 2019 International Conference on Information Management and Technology, ICIMTech 2019 Scopus
8 Sekarhati D.K.S., Nefiratika A., Hidayanto A.N., Budi N.F.A., Solikin Online Travel Agency (OTA) Data Maturity Assessment: Case Study PT Solusi Awan Indonesia -'Flylist' 2019 Proceedings of 2019 International Conference on Information Management and Technology, ICIMTech 2019 Scopus
9 Arman A.A., Sembiring J., Suhardi The importance of data management to support open data - Case study in Indonesia 2014 ACM International Conference Proceeding Series Scopus
10 Remi Indra Permana, Jarot S. Suroso Data Governance Maturity Assessment at PT. XYZ. Case Study: Data Management Division 2018 2018 International Conference on Information Management and Technology (ICIMTech) Google Scholar
11 Dwitama Heryadi Kurniawan; Yova Ruldeviyani; Mohammad Rizky Adrian; Sutia Handayani; M. Rizki Pohan; Rani Khairunnisa T Data Governance Maturity Assessment: A Case Study in IT Bureau of Audit Board 2019 2019 International Conference on Information Management and Technology (ICIMTech) Google Scholar
12 Dody Setiyawan A Proposed Model of IT Governance within Cloud Computing and Data Management in Higher Education 2019 International Journal of Advanced Engineering Research and Science (IJAERS), Vol-6, Issue-10, Oct- 2019 Google Scholar
13 Alivia Yulfitri Modeling operational model of data governance in government: Case study: Government agency X in Jakarta 2016 2016 International Conference on Information Technology Systems and Innovation (ICITSI) Google Scholar
14 Hanung Nindito Prasetyo A Review of Data Governance Maturity Level In Higher Education 2016 Jurnal Ilmiah Teknologi Informasi Terapan, Vol. 3, No. 1, 2016 Google Scholar
15 Alivia Yulfitri Analysis of Governance Maturity Data Using Stanford Data Governance Maturity 2020 BRITech (Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan) Volume 1, No 2 Januari 2020 Google Scholar
16 Hanung Nindito Prasetyo, Soni Fajar Surya Gumilang Data Governance Strategy for E-Government in Bandung District Governments 2019 International Journal of Engineering & Technology, Google Scholar
17 Hanung Nindito Prasetyo, Regina Nathania Djepapu, Ferra Arik Tridalestari, Ironman Hariman Development of Project Document Management System Based on Data Governance with DAMA International Framework 2018 Proceedings of the 2018 International Conference on Industrial Enterprise and System Engineering (IcoIESE 2018) Google Scholar
18 Rela Sabtiana; Satrio Baskoro Yudhoatmojo; Achmad Nizar Hidayanto Data Quality Management Maturity Model: A Case Study in BPS-Statistics of Kaur Regency, Bengkulu Province, 2017 2018 2018 6th International Conference on Cyber and IT Service Management (CITSM) Google Scholar
19 Amri Hanif; Tien Fabrianti Kusumasari; Rachmadita Andreswari Analysis and Design of Data Synchronization Algorithm for Master Data Management Tools Based on Open Source Platform at PT. XYZ 2019 2019 International Conference on Electrical Engineering and Informatics (ICEEI) Google Scholar
20 R. Tenie Pennata Kusumah; Suhardi Designing information governance in statistical organization 2014 2014 International Conference on Information Technology Systems and Innovation (ICITSI) Google Scholar
21 Budi Yuwono dan Aditya Arinanda Metode Perancangan Struktur Fungsi Danperan Tata Kelola Data Berbasis COBIT 2010 Journal of Information Systems, Volume 6, Issues 2, October 2010 Google Scholar

1. the International Conference on Advanced Computer Science and Information Systems (ICACSIS),

2. the International Conference on Information Technology Systems and Innovation (ICITSI),

3. AIP Conference,

4. International Conference on ICT for Smart Society (ICISS),

5. ACM International Conference,

6. International Conference on Information Management and Technology (ICIMTech),

7. International Conference on Industrial Enterprise and System Engineering (IcoIESE),

8. International Conference on Cyber and IT Service Management (CITSM), and

9. International Conference on Electrical Engineering and Informatics (ICEEI).

Whereas only six journals, two national journals and four international journals, published the articles, such as

1. Marine Policy Journal,

2. International Journal of Advanced Engineering Research and Science (IJAERS),

3. Jurnal Ilmiah Teknologi Informasi Terapan,

4. BRITech (Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan),

5. International Journal of Engineering & Technology, and

6. Journal of Information Systems

Third, after finding the articles from the databases, the articles were reviewed to determine the topics trend on data governance in Indonesia. From twenty-one founded articles, it becomes 14 articles after reviewed. Based on these articles, the study analyzes the topic in each article.

Fourth, 14 articles are eligible to be analyzed. These articles have been analyzed to identify and classify research topics. Based on these articles, three research topics are data governance design/model, the maturity of data governance, and the relationship of data governance with other variables (open data, leadership, and culture). Detailed information shows in Table 2.

Table 2 Research Topics from Sorted Articles Based on Abstract and Author's Keywords
No Research Topics Authors Title Year
1 Data governance design/model Aisyah M., Ruldeviyani Y. Designing data governance structure based on data management body of knowledge (DMBOK) Framework: A case study on Indonesia deposit insurance corporation (IDIC) 2019
Maulina J., Ruldeviyani Y. Data Governance and Data Architecture for the Ministry of Foreign Affairs of the Republic of Indonesia 2019
Alivia Yulfitri Modelling operational model of data governance in government: Case study: Government agency X in Jakarta 2016
Hanung Nindito Prasetyo, Soni Fajar Surya Gumilang Data Governance Strategy for E-Government in Bandung District Governments 2019
Amri Hanif ; Tien Fabrianti Kusumasari ; Rachmadita Andreswari Analysis and Design of Data Synchronization Algorithm for Master Data Management Tools Based on Open Source Platform at PT. XYZ 2019
R. Tenie Pennata Kusumah ; Suhardi Designing information governance in statistical organization 2014
Budi Yuwono dan Aditya Arinanda Metode Perancangan Struktur Fungsi dan Peran Tata Kelola Data Berbasis COBIT 2010
2 Maturity of data governance Saputra D.A., Handika D., Ruldeviyani Y. Data Governance Maturity Model (DGM2) Assessment in organization transformation of digital telecommunication company: Case study of PT Telekomunikasi Indonesia 2019
Remi Indra Permana, Jarot S. Suroso Data Governance Maturity Assessment at PT. XYZ. Case Study: Data Management Division 2018
Dwitama Heryadi Kurniawan Yova Ruldeviyani ; Mohammad Rizky Adrian ; Sutia Handayani ; M. Rizki Pohan ; Rani Khairunnisa T Data Governance Maturity Assessment: A Case Study in IT Bureau of Audit Board 2019
Hanung Nindito Prasetyo A Review Of Data Governance Maturity Level In Higher Education 2016
Alivia Yulfitri Analysis of Governance Maturity Data Using Stanford Data Governance Maturity 2020
3 Relationship of data governance with other variables (open data, leadership, and culture) Arman A.A., Sembiring J., Suhardi The importance of data management to support open data - Case study in Indonesia 2014
Putro B.L., Surendro K., Herbert H. Leadership and culture of data governance for the achievement of higher education goals (Case study: Indonesia University of Education) 2016

Most of the researchers in Indonesia study on data governance design/model topics from 2010-2020. Seven articles discussed modeling, design, or architecture of data governance in the organizations/institutions. Data Management and Body of Knowledge (DMBOK) and Control Objective for Information and related Technology (COBIT) were used to design data governance. The ideas and concepts presented in the DMBOK2 will be applied differently across organizations (DAMA International, 2014). Applying data governance activities based on DMBOK can be an initial solution for data problems (Aisyah & Ruldeviyani, 2019). Moreover, almost all research studied in government institutions: Indonesia deposit insurance corporation (IDIC), the Ministry of Foreign Affairs of the Republic of Indonesia, Government agency X in Jakarta, and Bandung District Governments. Government institutions need data governance to solve data problems (Aisyah & Ruldeviyani, 2019), meet the accuracy and availability of public information (Yulfitri, 2017), and provide transparency for helping decision-making (Prasetyo & Gumilang, 2019).

The maturity of data governance is another topic of data governance research in Indonesia. Data Governance Maturity Model (DGM2) and Stanford Data Governance Maturity usually use this model to measure data governance's maturity in the organization. Measuring data governance maturity is to identify the organization’s problems and give recommendations to the organizations (Permana & Suroso, 2018; Saputra et al., 2019; Yulfitri, 2020) so that organizations can improve data governance implementations (Prasetyo, 2016; Kurniawan et al., 2019).

Research on data governance's relationship with other variables was rarely studied - only two articles found in Indonesia. Open data, leadership, and culture are the variables that were used in previous researches. Data governance is essential to support all open data principles (Arman et al., 2014). Cultural factors, including leadership, are essential in data governance studies (Putro et al., 2016).

Conclusion

Research in data governance is growing in IS, as is the need for research in this area as an increasing number of organizations view data as a valuable asset. A review of the data governance literature suggests a lack of research that explicitly examines data governance activities. Nevertheless, several studies contribute to our understanding of data governance through modeling (Khatri & Brown, 2010; Otto, 2011; Tallon, 2013). This study reveals some progress in exploring data governance research topics in Indonesia.

The selection process yielded 21 articles subject to selection and exclusion criteria, which use data governance and Indonesia as the keywords. Following a more in-depth review, 14 were found to serve the research aim explicitly. These 14 papers were analyzed based on the articles' abstract and author keywords. This technique was selected to conduct an in-depth analysis of the data governance topics mentioned in these papers. There are three main research topics identified: data governance model/design, data governance maturity, and the relationship between data governance and other variables (open data, leadership, and culture).

This research has two limitations. Firstly, the research focused only on academic literature in the data governance area, ignoring practitioners' publications specifically. Institutions such as DAMA and The Data Warehousing Institute (TDWI) may provide further insight into data governance programs from a practitioner perspective. Future research may highlight differences in theory and practice (DAMA International, 2014). Secondly, the research presented in this paper only comes from Scopus, WoS, and Google Scholar. Other database sources did not include in this research, like as Ebsco online, Science Direct, Emerald Insight, AIS electronic library, and ACM Digital library.

For future research in data governance in Indonesia, more research on the impact of data governance is challenging. Furthermore, identify the relationship of data governance with other variables such as data quality, data security, and the performance also engaging to be studied. Besides, the study on data governance in other institutions such as higher education, hospitals, the financial industry, and other service organizations also has an opportunity.

References

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Al-Ruithe, M., Benkhelifa, E., & Hameed, K. (2018). Data governance taxonomy: Cloud versus non-cloud. Sustainability, 10(1), 95.

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