Epistemic Interoperability:
Governments worldwide have invested heavily in technical interoperability—integrating information systems to eliminate redundant data entry and ensure data consistency across agencies. Similar patterns can be observed in various centralized or hybrid budgeting systems, particularly in countries with rapidly developing digital government transformations. However, empirical evidence shows that data synchronization alone does not guarantee policy success. Sectoral ego persists, assumptions remain untested, and dissenting voices go undocumented. This article introduces the concept of Epistemic Interoperability as a complementary layer operating at the pre‑decision level—aligning how agencies frame problems, test assumptions, explore alternatives, and document dissent. Drawing on theories of epistemic communities (Haas), collaborative governance (Ansell & Gash; Ulibarri et al.), deliberative democracy (Habermas), boundary objects (Star & Griesemer), and contemporary literature on epistemic governance in complex systems (Jalonen, 2025; Boin et al., 2020; Newig et al., 2019), the article develops a four‑protocol framework: (1) shared framing, (2) joint assumption testing, (3) multi‑option mandate, and (4) structured dissent. Using Indonesia's annual planning and budgeting cycle as an institutional illustration, the article demonstrates how these protocols can be operationalized—identifying actors, timing, and documentary outputs. The framework contributes to governance literature by extending boundary object theory: formal policy documents are conceptualized not merely as coordination artifacts, but as institutionalized reasoning infrastructures within executive governance. Two conceptual propositions are proposed to guide future empirical research, and operational indicators for measuring epistemic interoperability are developed as a potential diagnostic tool. The article positions epistemic interoperability within the broader turn toward epistemic governance—a mode of governing that recognizes the centrality of knowledge construction, validation, and alignment in addressing complex policy challenges.
Keywords: epistemic interoperability, epistemic governance, collaborative governance, boundary objects, planning and budgeting, pre‑decision governance
1. INTRODUCTION
1.1 The Global Governance Paradox Amid Technical Integration
Over the past decade, governments worldwide have pursued ambitious technical interoperability programs—integrating information systems to eliminate redundant data entry, ensure data consistency, and enable real‑time monitoring (OECD, 2022). Similar patterns can be observed across centralized and hybrid budgeting systems in both developed and developing economies. Indonesia, for instance, has successfully linked its national planning system (KRISNA), its budgeting and financial management system (SAKTI), and its regional government information system (SIPD) (Bappenas, 2024; Kemenkeu, 2025). This achievement mirrors comparable integration efforts in countries such as India's Public Financial Management System (PFMS), Brazil's SIAFI, and various European digital government initiatives.
Yet a persistent paradox remains. Despite technical interoperability, sectoral ego and coordination failures persist across diverse governance contexts. Senior officials in multiple countries openly acknowledge that "every ministry has its own instinct, creating its own systems." Policy failures continue to occur within formally compliant processes. Development projects stall not because of data inconsistency, but because underlying assumptions—about construction timelines, economic growth rates, or program effectiveness—remain untested and unaligned across agencies. Dissenting views, when they emerge, disappear into informal channels, leaving no trace for future learning.
This phenomenon reflects what recent scholarship identifies as epistemic gaps in global governance—structural mismatches between technical integration and cognitive alignment that manifest across social, economic, and technological domains (Zhang & Wang, 2025). As the Georgetown Journal of International Affairs observes, these gaps are not merely spatial or material; they "manifest themselves in epistemology, norms, and governing institutions, a neglect of which can impede fundamental, collective transformation." The challenge extends beyond individual countries to the very architecture of contemporary governance systems, where the increasing reliance on digital infrastructure has not been matched by corresponding investments in the quality of inter‑agency reasoning.
1.2 Research Gap: From Technical to Epistemic Governance
This paradox points to a fundamental gap in current governance scholarship and practice. Technical interoperability addresses data synchronization but does not touch cognitive alignment—the process by which agencies develop shared understandings of problems, jointly test assumptions, collectively explore alternatives, and systematically document disagreements. While rich theoretical traditions speak to related concerns—epistemic communities (Haas, 1992, 2015), collaborative governance (Ansell & Gash, 2007; Ulibarri et al., 2020), deliberative democracy (Habermas, 1996), and boundary objects (Star & Griesemer, 1989)—these literatures have not been synthesized into an actionable framework for aligning inter‑agency reasoning in routine policy processes.
Moreover, recent developments in epistemic governance scholarship offer new analytical resources for understanding these challenges. Jalonen (2025) defines epistemic governance as "the processes shaping collective perceptions and influencing the understanding of a situation," emphasizing that in complex, crisis‑prone environments, governance must move beyond traditional models to embrace uncertainty and diverse forms of knowledge. This complexity‑informed approach recognizes that effective governance requires not only institutional structures but also the capacity to integrate multiple epistemic perspectives—precisely the challenge that technical interoperability alone cannot address.
Similarly, research on global environmental assessments reveals the internal challenges that expert organizations face in maintaining epistemic coherence across diverse disciplinary traditions (Lidskog & Sundqvist, 2025). These include "epistemic hierarchies, leadership and management dynamics, the complexities of formulating recommendations, and inequities in recognition and reward systems." Such findings underscore that epistemic alignment is not merely a technical problem but a deeply social and institutional one—requiring deliberate protocols for managing diverse ways of knowing.
This article addresses that gap by asking: What protocols can enable epistemic alignment across government agencies without requiring organizational restructuring or new technical systems?
1.3 Contributions and Structure
The article makes three contributions. First, it introduces the concept of Epistemic Interoperability—defined as the capacity of multiple agencies to align their reasoning processes before strategic decisions are taken, through systematic protocols for shared framing, joint assumption testing, collective exploration of alternatives, and structured documentation of dissent—operating as a complementary layer to technical interoperability. Second, it develops a theoretically grounded framework drawing on established literatures as well as contemporary developments in epistemic governance and complexity thinking. Third, it demonstrates operational feasibility through an institutional illustration of Indonesia's annual planning and budgeting cycle, specifying actors, timing, and documentary outputs—while extending boundary object theory by conceptualizing formal policy documents as institutionalized reasoning infrastructures. Two conceptual propositions are proposed to guide future empirical research, and operational indicators for measuring epistemic interoperability are developed as a potential diagnostic tool.
This article adopts a conceptual design approach. Indonesia is used as an institutional illustration based on publicly available documents and established planning procedures, rather than as an empirical field study.
The article proceeds as follows. Section 2 reviews relevant theoretical literature and articulates its implications for inter‑agency coordination. Section 3 develops the epistemic interoperability framework and its four protocols, beginning with a conceptual model that outlines the framework's logic and concluding with conceptual propositions. Section 4 presents the Indonesian case illustration, showing how the protocols can be operationalized in practice. Section 5 discusses theoretical contributions, practical implications, limitations, and future research directions. Section 6 concludes by positioning epistemic interoperability within the broader turn toward epistemic governance.
2. THEORETICAL FOUNDATIONS
2.1 Epistemic Communities and the Politics of Knowledge
Peter Haas's concept of epistemic communities provides a crucial starting point. Haas defines an epistemic community as "a network of professionals from a variety of disciplines and backgrounds, [with] a shared set of normative and principled beliefs... shared causal beliefs... shared notions of validity... and a common policy enterprise" (Haas, 1992, p. 3; see also Haas, 2015). These communities play a critical role in international policy coordination, particularly under conditions of uncertainty and complexity.
For the study of inter‑agency coordination, the concept illuminates a fundamental challenge: each government agency develops its own epistemic community—its own framing of problems, its own causal assumptions, its own criteria for valid knowledge. Planning agencies, with their focus on long‑term development, constitute one epistemic community. Finance ministries, focused on fiscal sustainability, constitute another. Sectoral ministries develop still others. The resulting "epistemic silos" generate coordination failures not because of bad faith, but because of genuinely different ways of knowing and reasoning (Haas, 2004).
Contemporary research has extended this insight to the internal dynamics of expert organizations. Lidskog and Sundqvist (2025), studying the Intergovernmental Panel on Climate Change (IPCC), identify how "epistemic hierarchies" and disciplinary diversity create challenges for maintaining coherence in global assessments. Their findings highlight that epistemic alignment requires not merely shared goals but structured mechanisms for negotiating differences in disciplinary standards, methodological commitments, and criteria for valid evidence.
The implication is clear: technical data integration, while necessary, cannot resolve epistemic fragmentation. What is needed are mechanisms for epistemic coordination—processes through which distinct epistemic communities can align their reasoning without sacrificing their specialized perspectives.
2.2 Collaborative Governance and Deliberative Democracy
The collaborative governance literature, particularly the seminal work of Ansell and Gash (2007), offers insights into how such coordination might be structured. Collaborative governance is defined as "a governing arrangement where one or more public agencies directly engage non‑state stakeholders in a collective decision‑making process that is formal, consensus‑oriented, and deliberative" (Ansell & Gash, 2007, p. 544). Key conditions for success include face‑to‑face dialogue, trust‑building, commitment to the process, shared understanding, and intermediate outcomes.
Recent developments in this literature, such as Ulibarri et al.'s (2020) study on the evolution of collaborative governance, show that collaborative regimes have diverse developmental trajectories—from failing to launch, to achieving results relatively quickly, to maintaining operations for decades. The study also finds that many characteristics of collaborative governance peak at the midpoint of observation periods, indicating that even stable and healthy collaborations can decline over time. This finding underscores the importance of designing protocols that can sustain collaborative quality over time.
Complementing this literature, Habermas's theory of deliberative democracy (1996) emphasizes the importance of communicative rationality—the idea that legitimate decisions emerge from reasoned argumentation among free and equal participants. In contemporary contexts, Boin et al. (2020) highlight challenges for governments in balancing accountability and learning amid increasing challenges to expert knowledge and social solidarity. This is relevant to efforts to build robust deliberative processes within government settings.
These literatures converge on a key insight: process matters. The quality of inter‑agency coordination depends not only on formal structures and technical systems, but on the deliberative quality of interactions—whether assumptions are openly examined, whether alternatives are genuinely considered, and whether dissenting views are heard and documented.
2.3 Boundary Objects and Interpretive Flexibility
The concept of boundary objects, developed by Star and Griesemer (1989), provides a crucial mechanism for operationalizing epistemic coordination. Boundary objects are "objects which are both plastic enough to adapt to local needs and constraints of the several parties employing them, yet robust enough to maintain a common identity across sites" (Star & Griesemer, 1989, p. 393). These objects enable coordination without requiring consensus, allowing different communities to collaborate while maintaining interpretive flexibility.
Classic examples include museum specimens, field notes, and maps—objects used differently by amateur collectors and professional scientists, yet structured enough to enable joint work. Subsequent research has extended the concept to information systems (Bowker & Star, 1999), cross‑disciplinary collaboration (Nicolini, Mengis & Swan, 2011), and boundary negotiating artifacts in unstable contexts (Lee, 2007).
For inter‑agency coordination in government, the boundary object concept suggests a strategy: design formal documents that can be interpreted flexibly by different agencies, yet structured enough to support joint deliberation and accountability. The protocols proposed in this article—Framing Charters, Assumption Testing Sheets, Option Portfolios, and Dissent Records—function precisely as boundary objects of this kind.
2.4 Epistemic Governance in Complex Systems
Recent scholarship has advanced the concept of epistemic governance as a distinct analytical framework for understanding how knowledge shapes collective decision‑making. Jalonen (2025) defines epistemic governance as encompassing "self‑organization, diversity, trust, feedback loops, attractor, and agency" in the context of complex systems. This approach recognizes that governance in conditions of uncertainty requires continuous negotiation of what counts as relevant knowledge, who has epistemic authority, and how diverse perspectives can be integrated.
Crucially, Jalonen argues that traditional governance models—network governance, participatory governance, experimentalist governance, collaborative governance, anticipatory governance, and adaptive governance—each have specific limitations regarding "the production, dissemination, and utilization of information" during crises. Epistemic governance addresses these limitations by focusing directly on "the epistemic challenges posed by a multitude of complex, interconnected, and persistent crises."
This perspective aligns with broader calls to reconceptualize governance for an era of complexity and epistemic fragmentation. Zhang and Wang (2025) observe that "behind today's turbulence in material and geopolitical transformations lie deep epistemic and representational gaps," noting that "prevailing media and legal frameworks have failed to account for the lived experience and political agency of those most affected." The challenge, they suggest, is not merely technical but fundamentally epistemic—requiring governance architectures that can bridge differences in how problems are understood and addressed.
2.5 Synthesizing the Literature: From Technical to Epistemic Interoperability
Table 1 synthesizes the theoretical foundations and their implications for the proposed framework.
| Theory | Key Scholars | Core Insight | Implication for Framework |
|---|---|---|---|
| Epistemic Communities | Haas (1992, 2015); Lidskog & Sundqvist (2025) | Agencies develop distinct ways of knowing; epistemic hierarchies create coordination challenges | Need mechanisms that align reasoning across epistemic communities |
| Collaborative Governance | Ansell & Gash (2007); Ulibarri et al. (2020) | Face‑to‑face dialogue, trust‑building, shared understanding are critical; collaboration has evolutionary trajectories | Protocols must create structured spaces for deliberation and sustain collaborative quality |
| Deliberative Democracy | Habermas (1996); Boin et al. (2020) | Legitimate decisions emerge from reasoned argumentation; reasons must be documented; expert knowledge must be carefully managed | Protocols must require documentation of assumptions and dissent |
| Boundary Objects | Star & Griesemer (1989); Bowker & Star (1999) | Objects with interpretive flexibility enable coordination without consensus | Formal documents can function as boundary objects across agencies |
| Epistemic Governance | Jalonen (2025); Zhang & Wang (2025) | Governance in complex systems requires continuous negotiation of knowledge, authority, and perspectives | Framework contributes to epistemic governance by providing operational protocols for cognitive alignment |
Table 1: Theoretical Foundations of Epistemic Interoperability
This synthesis reveals that technical interoperability, while necessary, addresses only the surface layer of coordination. Beneath the data lie distinct epistemic communities, each with its own framing, assumptions, and validity criteria. Bridging these communities requires not just data exchange, but epistemic interoperability—a set of protocols for aligning reasoning processes across agencies that operationalizes the broader project of epistemic governance.
3. EPISTEMIC INTEROPERABILITY: A FOUR‑PROTOCOL FRAMEWORK
3.0 Conceptual Model of Epistemic Interoperability
In summary, epistemic interoperability can be modeled as follows:
- Input: Epistemic fragmentation across agencies—divergent problem framings, untested assumptions, limited alternative exploration, and undocumented dissent.
- Mechanism: Four sequentially operating protocols—shared framing, joint assumption testing, multi‑option mandate, and structured dissent.
- Output: Documented reasoning traces in the form of Framing Charters, Assumption Testing Sheets, Option Portfolios, and Dissent Records.
- Outcome: Improved policy quality through tested assumptions, explored alternatives, and sustained institutional learning.
This model emphasizes that epistemic interoperability is not merely a series of coordination meetings, but a reasoning infrastructure that produces documentary artifacts as the foundation for accountability and learning.
3.1 Definition and Scope
Epistemic Interoperability is defined as:
The capacity of multiple agencies to align their reasoning processes before strategic decisions are taken, through systematic protocols for shared problem framing, joint assumption testing, collective exploration of alternatives, and structured documentation of dissent—operating as a complementary layer to technical interoperability and contributing to the broader project of epistemic governance.
The framework is designed to be:
- Complementary, not substitutive: It adds to, rather than replaces, existing technical systems and coordination mechanisms.
- Selective and proportional: Applied only to strategic decisions, priority programs, and complex cross‑sectoral issues.
- Learning‑oriented: Designed to generate documented traces that enable institutional learning over time.
3.2 Four Protocols of Epistemic Interoperability
3.2.1 Protocol 1: Shared Framing
Function: Align problem definitions and basic assumptions across agencies before detailed planning begins.
Theoretical grounding: Epistemic communities literature shows that different communities frame problems differently (Haas, 2004). Collaborative governance research emphasizes developing shared understanding at the outset (Ansell & Gash, 2007).
Operational elements:
- Inter‑agency forum at H‑90 (90 days before budget ceilings are set).
- Explicit documentation of each agency's framing of national priorities.
- Negotiation of shared operational definitions.
- Agreement on a common set of macroeconomic assumptions with multiple scenarios.
- Output: Framing Charter signed by senior officials.
3.2.2 Protocol 2: Joint Assumption Testing
Function: Systematically test the critical assumptions underlying each agency's proposals.
Theoretical grounding: Haas (1992) emphasizes that epistemic communities are partly defined by shared causal beliefs. Testing assumptions reveals where such beliefs diverge and where they can be aligned.
Operational elements:
- Sectoral forums at H‑60.
- Each priority ministry presents one‑page statements of critical assumptions.
- Cross‑agency teams test assumptions against historical data, benchmarks, and expert judgment.
- Output: Assumption Testing Sheets with clear recommendations (realistic, needs revision, requires alternative scenario).
3.2.3 Protocol 3: Multi‑Option Mandate
Function: Ensure that multiple alternatives are explored before decisions are finalized.
Theoretical grounding: Deliberative democracy requires that alternatives be genuinely considered (Habermas, 1996). Collaborative governance research shows that premature convergence is a common source of failure (Ansell & Gash, 2007).
Operational elements:
- For each priority program, agencies develop three substantially different options.
- Each option accompanied by brief cost‑benefit‑risk analysis.
- Inter‑agency forum discusses trade‑offs and selects preferred option with documented rationale.
- Output: Option Portfolio documenting all options considered and reasons for selection/rejection.
3.2.4 Protocol 4: Structured Dissent
Function: Document and respond to dissenting views in final decision forums.
Theoretical grounding: Boundary object theory suggests that coordination without consensus requires mechanisms for managing difference (Star & Griesemer, 1989). Deliberative democracy requires that all views be heard and reasons exchanged (Habermas, 1996). Boin et al. (2020) emphasize balancing accountability and learning amid challenges to expert knowledge.
Operational elements:
- One‑page Dissent Form available in final decision forums.
- Participants may submit formal dissent with grounds and proposed alternatives.
- Chair must read each dissent aloud and provide written response (accepted, rejected with reasons, deferred).
- All forms and responses attached to final minutes.
- Output: Dissent Record as permanent annex to decisions.
3.3 What Distinguishes Epistemic Interoperability from Conventional Coordination?
Unlike conventional coordination meetings that rely heavily on informal negotiation and participants' collective memory, epistemic interoperability requires formal documentary artifacts that create structured reasoning traces across agencies. Framing Charters, Assumption Testing Sheets, Option Portfolios, and Dissent Records are not merely ordinary meeting minutes—they are boundary objects explicitly designed to accommodate interpretive differences across agencies while maintaining accountability. Thus, epistemic interoperability shifts coordination from easily lost informal negotiation toward institutionalized cognitive alignment that can be traced over time.
It is important to emphasize: epistemic interoperability does not aim to add bureaucratic layers, but rather to formalize deliberative practices that have long occurred informally and without documentation. It is not "additional meetings," but a new way of conducting existing meetings—with disciplined documentation and clear reasoning traces. This is what distinguishes it from ordinary coordination practices.
3.4 Differences Between Technical and Epistemic Interoperability
| Dimension | Technical Interoperability | Epistemic Interoperability |
|---|---|---|
| Object | Data and systems | Reasoning and assumptions |
| Goal | Data synchronization, no redundant input | Cognitive alignment, tested assumptions |
| Timing | When data is entered | Before data is entered (pre‑decision) |
| Method | APIs, data exchange, system integration | Shared framing, assumption testing, multi‑option, structured dissent |
| Outputs | Integrated databases | Framing Charters, Assumption Sheets, Option Portfolios, Dissent Records |
| Coordination mechanism | Automated, system‑based | Deliberative, artifact‑based |
| Accountability trace | Data trail | Reasoning trail |
| Success measure | Data consistency | Policy quality |
3.5 Conceptual Propositions
To guide future empirical research and clarify the theoretical structure of the framework, two conceptual propositions are advanced:
Proposition 1: The higher the level of documented shared framing among agencies at the outset of the planning cycle, the lower the likelihood of late‑stage policy revisions due to macroeconomic assumption misalignment.
Proposition 2: The availability of structured dissent mechanisms in final decision forums positively correlates with the quality of post‑implementation policy learning, as reflected in documented evaluations and subsequent policy improvements.
Both propositions are conceptual and have not been empirically tested. They are offered as starting points for future research to test the validity and relevance of the epistemic interoperability framework.
4. OPERATIONALIZING EPISTEMIC INTEROPERABILITY: THE INDONESIAN ILLUSTRATION
While this illustration draws on Indonesia's planning cycle, the designed protocols are adaptable to other centralized or hybrid budgeting systems with necessary contextual adjustments.
4.1 Current Planning and Budgeting Cycle
| Timing | Activity | Actors | Recurring Problems |
|---|---|---|---|
| February | Bappenas drafts initial RKP (Government Work Plan) | Bappenas | Macro assumptions not yet aligned with Finance Ministry |
| March | Ministry of Finance sets indicative budget ceilings | Finance Ministry | Disagreement on macro assumptions emerges late |
| April-May | Ministries prepare proposals based on ceilings | Line ministries | Ministries complain of shifting assumptions |
| June | Coordination forums discuss proposals | All parties | Discussions focus on numbers, not assumptions |
| July-August | Final budget ceilings set | Finance Ministry | Late rejections due to unsound assumptions |
4.2 Implementing Protocol 1: Shared Framing (February, H‑90)
Actors: Bappenas (Deputy for Economy), Ministry of Finance (Fiscal Policy Agency, Tax Directorate), Bank Indonesia.
Activities:
- Two‑day joint workshop addressing: "What are the operational definitions of the five national priorities for 2027?"; "What macroeconomic assumptions will we use jointly?"; "What scenarios should be prepared if assumptions prove wrong?"
Output: 2027 RKP Framing Charter (5‑7 pages) containing operational definitions of each priority, macroeconomic assumptions table with three scenarios (optimistic, moderate, pessimistic), and signed commitment to use shared assumptions in all documents. Boundary object function: The Charter is interpreted differently by each agency—Bappenas focuses on planning implications, Finance on fiscal implications—but its common structure enables coordinated action.
4.3 Implementing Protocol 2: Joint Assumption Testing (March, H‑60)
Actors: Technical teams from Bappenas (Macro Planning Directorate), Ministry of Finance (Fiscal Policy Agency, Tax Directorate), and priority line ministries (Public Works, Health, Education, etc.).
Activities: Three‑day Cross‑Sector Assumption Testing Forum. Each priority ministry presents one‑page critical assumptions (e.g., Public Works: "Dam X will be completed in 3 years with budget Y."). Cross‑agency teams test assumptions against historical data, benchmarks, and expert judgment.
Output: Assumption Testing Sheets for each priority ministry: realistic → can be used; needs revision → recommended new figures; requires alternative scenario → high uncertainty.
4.4 Implementing Protocol 3: Multi‑Option Mandate (April-May, H‑30)
Actors: Priority line ministries, facilitated by Bappenas and Finance Ministry.
Activities: For each national priority program, ministries develop three substantially different options (e.g., for food security: intensification, extensification, public‑private partnership). Each option accompanied by brief analysis (cost‑benefit‑risk).
Output: Option Portfolio for 10‑15 priority programs, stored in KRISNA.
4.5 Implementing Protocol 4: Structured Dissent (June, Final Budget Ceiling Forum)
Actors: Echelon I officials from Bappenas, Finance Ministry, and line ministries.
Activities: Forum provides one‑page Dissent Forms. Participants may submit formal dissent with grounds and proposed solution. Chair must read each dissent aloud and provide written response (accepted, rejected with reasons, deferred). All forms and responses attached to final minutes.
Output: Dissent Record signed by chair and archived by Bappenas and Finance Ministry. Boundary object function: Enables accountability and learning—if policies later fail, there is documented evidence of who warned and why warnings were not heeded.
5. DISCUSSION: THEORETICAL CONTRIBUTIONS AND PRACTICAL IMPLICATIONS
5.1 Theoretical Contributions
This article makes three theoretical contributions.
First, it introduces the concept of Epistemic Interoperability as a distinct layer of governance coordination. While technical interoperability addresses data exchange, epistemic interoperability addresses cognitive alignment—the processes by which agencies develop shared problem frames, jointly test assumptions, collectively explore alternatives, and systematically document dissent. This distinction explains why data‑synchronized systems still produce coordination failures and suggests a complementary pathway for improvement. Furthermore, by requiring formal documentary artifacts, epistemic interoperability shifts coordination from easily lost informal practices toward institutionalized, traceable cognitive alignment.
Second, it synthesizes classical and contemporary literatures into an actionable framework. The concept uses epistemic communities theory to diagnose the problem (epistemic silos), collaborative governance and deliberative democracy to design processes (structured deliberation, reason documentation), and boundary object theory to operationalize mechanisms (formal documents with interpretive flexibility). Integrating contemporary literature on epistemic governance (Jalonen, 2025; Zhang & Wang, 2025) and the internal dynamics of expert organizations (Lidskog & Sundqvist, 2025) strengthens the framework's relevance in contemporary contexts where knowledge fragmentation and institutional complexity pose fundamental challenges to governance.
Third, it extends boundary object theory by conceptualizing formal policy documents as institutionalized reasoning infrastructures within executive governance. While boundary object research has focused on scientific and technical domains (Star & Griesemer, 1989; Bowker & Star, 1999), this article shows how Framing Charters, Assumption Testing Sheets, Option Portfolios, and Dissent Records function as boundary objects across government agencies. More than mere coordination artifacts, these documents constitute reasoning infrastructures—artifact systems that enable, constrain, and record collective thinking processes. They are plastic enough to accommodate different agency perspectives yet robust enough to enable shared reasoning—and crucially, they leave documented traces enabling learning over time. This conceptualization extends our understanding of how policy documents can be designed not only for administration, but also for epistemic accountability and institutional learning.
5.2 Practical Implications
For government planners and budgeters, the framework suggests that further investment in technical integration, while welcome, should be complemented by investment in process design. The four protocols can be piloted without requiring new systems or organizational changes—only commitment to structured early dialogue and disciplined documentation.
To facilitate operationalization and evaluation, the framework can be translated into epistemic interoperability indicators usable as a diagnostic tool. Table 3 presents indicators for each protocol with potential scoring schemes.
| Protocol | Indicator | Possible Score | Verification Source |
|---|---|---|---|
| Shared Framing | Existence of jointly signed framing charter | 0: None; 1: Exists but unsigned; 2: Exists and signed | Charter document |
| Number of documented assumption scenarios | 0: 1 scenario; 1: 2 scenarios; 2: ≥3 scenarios | Framing charter | |
| Participation rate of key agencies in framing forum | 0: <50%; 1: 50‑80%; 2: >80% | Attendance list | |
| Joint Assumption Testing | Percentage of critical assumptions jointly tested | 0: <30%; 1: 30‑70%; 2: >70% | Assumption Testing Sheets |
| Percentage of assumptions revised after testing | 0: <10%; 1: 10‑30%; 2: >30% | Comparison of initial vs final proposals | |
| Availability of written recommendations for each assumption | 0: None; 1: Partial; 2: Complete | Assumption Testing Sheets | |
| Multi‑Option Mandate | Percentage of priority programs with ≥3 substantive options | 0: <30%; 1: 30‑70%; 2: >70% | Option Portfolio |
| Quality of option analysis (cost‑benefit‑risk) | 0: None; 1: Partial; 2: Complete for all options | Option Portfolio | |
| Documentation of reasons for option selection/rejection | 0: None; 1: Partial; 2: Complete | Option Portfolio | |
| Structured Dissent | Availability of dissent forms | 0: None; 1: Available but unused; 2: Available and used | Forms, records |
| Number of documented dissents per forum | 0: 0; 1: 1‑3; 2: >3 | Records | |
| Percentage of dissents receiving written responses | 0: <30%; 1: 30‑70%; 2: >70% | Records |
Table 3: Operational Indicators for Epistemic Interoperability
For line ministries, the framework offers protection. Documented dissent protects officials raising legitimate concerns. Tested assumptions protect ministries from being held accountable for failures rooted in unrealistic assumptions imposed by others. Multi‑option mandates ensure that ministries' preferred solutions are not accepted uncritically, but also not rejected without alternative consideration.
For regional governments, the framework addresses the root cause of redundant data input. When central agencies align their assumptions and definitions early, regional data can be collected once and used by all. Technical interoperability then delivers its promised efficiency gains.
5.3 Limitations and Future Research
This article is conceptual and non‑empirical. The proposed framework remains untested in actual practice. However, as outlined above, it can be operationalized into measurable indicators, opening pathways for future empirical validation.
Future research should:
- Pilot the four protocols in actual government settings and evaluate their effectiveness, attending to collaborative evolution dynamics as identified by Ulibarri et al. (2020).
- Empirically test Propositions 1 and 2—for example, by comparing late‑stage policy revision rates between units that implement shared framing versus those that do not, or by analyzing correlations between documented dissent and post‑program evaluation quality.
- Develop and validate an epistemic interoperability index based on the indicators above, including reliability and construct validity testing.
- Compare framework applicability across different governance systems and cultures.
- Explore how digital technologies can support (rather than replace) the deliberative processes at the framework's core, particularly in light of challenges to expert knowledge identified in the epistemic governance literature (Boin et al., 2020; Jalonen, 2025).
6. CONCLUSION: EPISTEMIC INTEROPERABILITY AS A CONTRIBUTION TO EPISTEMIC GOVERNANCE
Technical interoperability has transformed government information systems, eliminating redundant data entry and ensuring data consistency across agencies. Yet data synchronization alone cannot resolve the deeper challenge of epistemic fragmentation—the reality that different agencies, with distinct mandates and professional cultures, develop different ways of framing problems, testing assumptions, and evaluating alternatives.
Epistemic interoperability addresses this challenge by adding a complementary layer at the pre‑decision level. Its four protocols—shared framing, joint assumption testing, multi‑option mandate, and structured dissent—create structured spaces for inter‑agency deliberation, produce documentary traces enabling accountability and learning, and function as boundary objects that coordinate action without requiring consensus on every point. Unlike ordinary coordination, epistemic interoperability requires formal documentary artifacts that create structured reasoning traces, shifting coordination from informal negotiation toward institutionalized cognitive alignment—not by adding bureaucracy, but by formalizing deliberative practices that have long been informal and undocumented.
Epistemic interoperability is not a governance model, but a reasoning protocol layer embedded within existing governance structures. This framework contributes to the broader project of epistemic governance—a mode of governing that recognizes the centrality of knowledge construction, validation, and alignment in addressing complex policy challenges. As Jalonen (2025) argues, epistemic governance in complex systems requires attention to "self‑organization, diversity, trust, feedback loops, attractor, and agency." The protocols proposed here operationalize these principles in the specific context of inter‑agency planning and budgeting, demonstrating how epistemic governance can be made actionable.
Moreover, the framework responds to the challenge identified by Zhang and Wang (2025): that "epistemic and representational gaps" in global governance require "potential architectures to bridge these gaps." By providing a structured approach to aligning reasoning across diverse epistemic communities, epistemic interoperability offers one such architecture—modest in its ambitions but potentially significant in its effects.
While illustrated using Indonesia, the protocols are structurally adaptable to centralized, federal, or hybrid budgeting systems. The Indonesian illustration demonstrates that these protocols can be operationalized without new systems or organizational restructuring. They require only what good governance has always required: disciplined early dialogue, systematic assumption testing, genuine alternative exploration, and respectful documentation of disagreement. In an increasingly complex and interdependent world—where knowledge fragmentation and institutional complexity pose fundamental challenges—these are not luxuries but necessary components of effective governance.
It must be emphasized that epistemic interoperability is not a substitute for technical interoperability, but a necessary complement. The two operate at different layers and reinforce each other. Technical interoperability ensures data flows smoothly and consistently; epistemic interoperability ensures that flowing data emerges from quality reasoning processes. Governments that have invested heavily in technical integration need not repeat that investment—they need only add the simple process layer outlined in this article. Together, technical and epistemic interoperability form the foundation for governance that is not only administratively efficient, but also substantively intelligent—a contribution to the ongoing project of building governance architectures adequate to the complexities of our time.
REFERENCES
Ansell, C., & Gash, A. (2007). Collaborative governance in theory and practice. Journal of Public Administration Research and Theory, 18(4), 543-571.
Bappenas. (2024). Integrasi Perencanaan dan Penganggaran: Tantangan dan Inovasi. Jakarta.
Boin, A., Brock, K., Craft, J., Halligan, J., 't Hart, P., Roy, J., Tellier, G., & Turnbull, L. (2020). Beyond COVID-19: Five commentaries on expert knowledge, executive action, and accountability in governance and public administration. Canadian Public Administration, 63(3), 339-368.
Bowker, G. C., & Star, S. L. (1999). Sorting things out: Classification and its consequences. MIT Press.
Doberstein, C. (2016). Building a collaborative advantage: Network governance and homelessness policy‑making in Canada. UBC Press.
Haas, P. M. (1992). Introduction: Epistemic communities and international policy coordination. International Organization, 46(1), 1-35.
Haas, P. M. (2004). When does power listen to truth? A constructivist approach to the policy process. Journal of European Public Policy, 11(4), 569-592.
Haas, P. M. (2015). Epistemic communities, constructivism, and international environmental politics. Routledge.
Habermas, J. (1996). Between facts and norms: Contributions to a discourse theory of law and democracy (W. Rehg, Trans.). MIT Press.
Jalonen, H. (2025). Epistemic governance in the context of crisis: A complexity‑informed approach. Administration & Society, 57(2), 218-253.
Kemenkeu. (2025). SAKTI: Sistem Akuntansi dan Pelaporan Keuangan Instansi. Jakarta.
Lee, C. P. (2007). Boundary negotiating artifacts: Unbinding the routine of boundary objects and embracing chaos in collaborative work. Computer Supported Cooperative Work, 16(3), 307-339.
Lidskog, R., & Sundqvist, G. (2025). Expert advice and global environmental governance: Institutional and epistemic challenges for assessment bodies. Sustainability, 17(17), 7876.
Newig, J., Derwort, P., & Jager, N. W. (2019). Sustainability through institutional failure and decline? Archetypes of productive pathways. Ecology and Society, 24(1), 18.
Nicolini, D., Mengis, J., & Swan, J. (2011). Understanding the role of objects in cross‑disciplinary collaboration. Organization Science, 23(3), 612-629.
OECD. (2022). Digital government review of Indonesia: Towards a citizen‑centred digital transformation. OECD Publishing.
Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, 'translations' and boundary objects: Amateurs and professionals in Berkeley's Museum of Vertebrate Zoology, 1907‑39. Social Studies of Science, 19(3), 387-420.
Torfing, J. (2016). Collaborative innovation in the public sector. Georgetown University Press.
Ulibarri, N., Emerson, K., Imperial, M. T., Jager, N. W., Newig, J., & Weber, E. P. (2020). How does collaborative governance evolve? Insights from a medium‑n case comparison. Policy & Society, 39(4), 617-637.
Zhang, Y., & Wang, J. (2025). Global gaps: Bridging differences, disparities, and disconnections. Georgetown Journal of International Affairs, 26(1), 1.
