Institutional Dimensions in Open Government Data: A Deep Dive Into Indonesia’s Satu Data Initiative and Its Implications for Developing Countries

Figures & data

Table 1. Empirical insights into Open Government Data (OGD) that relate to the institutional dimensions framework.

Reference	Underlying institutional dimension(s)*					Country context**	Key findings on OGD implementation
	PS	OA	LF	RSED	PSA
						Developed
Chatfield & Reddick, 2017	✔	✔	✓	✓	✔	Australia	Policies focused on internal (e.g., government transparency) and external goals (e.g., open innovation) improve open data service capabilities. Dedicated open data portal investment improves service capabilities over time. Hackathons and idea competitions can increase user engagement with the portal.
Jetzek, 2016	✔	✔	✓	✓	✔	Denmark	Pre-existing reusable data strategies and digital governance policies benefit OGD implementation. Simplification and modernization of the IT architecture. A coherent and interoperable data model. Financial capabilities and support. Restructuring responsibility and authority between organizations and across ministries, and levels of government.
Kassen, 2019	✔	✓	✓	✓	✔	Estonia	Highly centralized administrative policy to advance technology-driven public services. Involvement of civil society and private ICT industry.
Kassen, 2018	✔	✔	✓	✔	✔	Finland	Highly centralized administrative policy to advance digital governance. Collaboration among government organizations and across ministries and levels of government. Popularizing IT-focused education in universities allows users to have relevant skills to use data and develop new services via startup initiatives. Cooperation with the local nongovernmental sector, independent developers, and journalists.
Ruijer et al., 2020	✓	✔	✓	✔	✔	France	Reticence to publish some data types to avoid negative public perceptions and pushback. High degree of interconnectedness among different layers of involved administrations and supplier services. Organizing conferences and hackathons to encourage ICT startups. Lack of employees for data management and digitalization.
Wirtz et al., 2018	✓	✔	✓	✔	✓	Germany	Focus on making the portal easy to use to enhance citizens’ use of OGD. Internet competence significantly determines citizens’ intention to use OGD.
Cho & Lee, 2022	✔	✔	✔	✔	✓	Korea	Consistent national policies and plans. Open organizational culture of government agencies. Financial capabilities and support. Data and OGD guidelines standardization and quality data management. Notes are requirement for skilled human resources.
Cahlikova & Mabillard, 2020	✔	✓	✔	✔	✓	Switzerland	Incentive-based policies. Open organizational culture of government agencies. Legal frameworks to guide data publishing. Lack of data management know-how and competencies.
Ruijer et al., 2020; Safarov, 2019	✔	✔	✔	✔	✔	Netherlands	Adjusting the relevant policy frames of privacy, freedom of information, open government, and information security regulations. Reuse of data becomes part of policy proposals, project assignments, and agreements, while resistance to data-sharing exists. Preexisting regulations guide data-sharing. Highly interconnected multilevel governance. Lack of management support and certain data highly politically sensitive. Workshops, discussions, and meetings to increase the skills of government officials. Awards and competitions enhance public awareness. Partnership among nongovernmental organizations to raise awareness. Data journalism to achieve public support.
Bates, 2014; Wang & Shepherd, 2020	✔	✔	✓	✓	✔	United Kingdom	Gaining legitimacy via transparency-related policies to overcome public distrust on government. Most of the published data are informational rather than granular data. Only a small percentage of data are actually open data, which severely limits OGD utilities. Forming a new board to initiate and structure the process. Civil society OGD advocates put pressure on the government for greater transparency and civic engagement.
Piotrowski, 2017	✔	✓	✔	✔	✔	United States	Lack of complementary policies (e.g., trade policy negotiations, access to justice and civil rights issues, ethics, and integrity of governance). Lack of integration on initiatives within state and local government. An emphasis on public participation and stakeholder involvement.
						Transition
Kassen, 2017; Safarov, 2020	✔	✔	✔	✔	✔	Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Moldova, and Ukraine	All five institutional dimensions in these transition countries are similar to their developed counterparts. OGD implementation in transition countries is much more fragile and highly dependent on foreign aid initiatives. A strictly centralized approach with no distinction between local and national open data projects. Traditional directives could paradoxically be effective in advancing open data even in a less collaborative political culture. Organizing prize contests, competitions, and hackathons are cost-effective tools that promote engagement. The existence of independent developers is crucial in promoting various open data-driven projects and sharing related expertise. The open data movement encourages participation of the nongovernmental sector and promotes civil engagement.
						Developing
Zhang et al., 2022; Zhao et al., 2022	✓	✔	✔	✓	✔	China	Establishing a dedicated agency for OGD implementation. Establishing an OGD evaluation assessment mechanism for responsible government officials and offering incentives (e.g., bonuses and promotions). Creating top-down organizational pressure. Formulating OGD rules and regulations. Attracting the public to actively participate through developing and publishing OGD technology road maps.
Gonzalez-Zapata & Heeks, 2015	✔	✔	✓	✓	✓	Chile	Technical challenges include data interoperability and data accessibility. Complex bureaucratic processes. Interests of central government tend to dominate implementation without involving civil society.
Altayar, 2018	✔	✓	✔	✓	✔	Saudi Arabia	Political reforms emphasize transparency and accountability. Complementary e-government program creates internal and external institutional pressure. Regulatory reform of freedom of information mandates all government agencies to publish their data. The presence of a data portal with datasets that are machine-readable formats is beneficial. Low awareness and knowledge of OGD among citizens, yet a high demand for requesting access to open data.
Current study	✔	✔	✔	✔	✔	Indonesia	Lack of leadership in policymaking processes to remove overlapping OGD initiatives. Need for harmonization of laws and regulations. Limited central government support for OGD implementation. Minor focus on fostering relevant skills and educational support, public support, and awareness.

Note. *We include empirical insights that relate (explicitly or implicitly) to the institutional dimensions framework at the national level and are published in academic journals listed as Q1 in Scimago Journal Rank (to include quality publication). PS = Policy and strategy: Availability of concrete open data policies that are consistent and guide strategic actions. OA = Organizational arrangements: Deployment and adjustment of organizational structure to ensure strong leadership, quick response to societal and technical requirements, and adequate open organizational culture. LF = Legislative foundations: Availability of strong guidelines, rules, and operational regulations concerning information openness, data protection, and data management. RSED = Relevant skills and educational support: Knowledge and skills of government officials and potential users and availability of educational programs and training. PSA = Public support and awareness: Involvement of nongovernmental organizations, civic society, and private companies. ✔= Explicitly or implicitly relate and ✔= Does not relate to the institutional dimensions. **Per the United Nations’ (2020) classification of developed, transition, and developing nations concerning economic situation and prospects.

Figure 1. Evolution of Open Government Data implementation in Indonesia.

Table 2. The formal organizational structure of Open Government Data (OGD) implementation in Indonesia.

Structure	Government organization/agency	Role/responsibility
Governing Board or Steering Committee	Consists of BAPPENAS, Central Bureau of Statistics (BPS), KemenPANRB, Ministry of ICT (KOMINFO), Ministry of Home Affairs (MOHA), Ministry of Finance (MOF), and Geospatial Information Agency (BIG)	Coordinating and shaping policies for enhancing government data governance Resolving issues and obstacles in implementing government data governance
SDI Forum	Staffed with SDI steering committee members and the working group of data custodians	Governance boards, data coaches, data guardians, data custodians, and data producers Promoting reference codes and master data adoption in the SDI portal, establishing data custodians among government organizations/agencies
SDI Secretariat	Ex-officio or a taskforce at BAPPENAS	Enhancing coordination among government organizations/agencies Reaching consensus on data lists and priority data collection Monitoring and evaluating the SDI action plan (RENAKSI)
SDI Secretariat Coordinator Subnationally	Local development planning agency (Berdasarkan Peraturan Daerah, BAPPEDA) is the SDI Secretariat’s provincial and local coordinating body	Carrying out planning, research, and development support functions at regional level Helping local government leaders (governors at the provincial level, or mayors at city or district levels) in implementing government affairs in the field of planning, research, and development
Data Coaches or Data Stewards	SDI focus on three data domains: statistical data (BPS), financial data (MoF), geospatial data (BIG)	Establishing data standards, metadata, data formats, reference codes, and data interoperability Overseeing data collection procedures and ensuring data quality Supervising the implementation of SDI
Data Guardians or Data Custodians	A dedicated unit that manages government data at ministerial or agency (central government) or local government organization (regional level) called Data and Information Center (PUSDATIN)	Offering technical guidance Managing the data life cycle (collection, validation, storage, publication, and dissemination)
Data Owners or Data Producers	Government organizations both national and subnational levels that produce data	Generating data in line with SDI principles Providing input to the SDI portal and collaborating with data stewards on SDI implementation Complying with relevant laws and regulations in data production roles
Data Users	Regional agencies, individuals, groups of people, or legal entities that use data from SDI portal	Using government data for any purpose such as research, policymaking, evaluation, business, and strategy

Note. Compiled through open inquiry of interview data. SDI = Satu Data Indonesia.

Figure 2. The regulatory framework of Satu Data.

Figure 3. Indonesia’s Satu Data implementation coordination chart, push factors, and constraints.

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