Competition Law and Knowledge Interoperability

1. Introduction

Knowledge interoperability refers to the ability of different platforms, databases, software systems, research repositories, AI systems, knowledge graphs, information services, and other knowledge infrastructures to exchange, understand, access, and use information across technological or organisational boundaries.

From a competition-law perspective, knowledge interoperability becomes important where a firm controls a critical body of information or a technical interface and uses that control to restrict rivals. The issue is particularly significant in:

• AI and machine-learning ecosystems;
• knowledge graphs and databases;
• scientific and academic repositories;
• digital libraries;
• search engines;
• cloud and enterprise software;
• healthcare-information systems;
• financial-information platforms;
• professional information services;
• mapping and geospatial databases; and
• standards and technical interfaces.

Competition law generally does not create an unrestricted right to obtain another firm's information. The central question is whether control over knowledge or interoperability infrastructure is being used in a manner that excludes competitors, raises barriers to entry, reduces innovation, or protects an existing market position.

2. Meaning of Knowledge Interoperability

Knowledge interoperability has several dimensions.

A. Data interoperability

Different systems can exchange datasets.

Example: A healthcare platform allows authorised hospitals to transfer patient-record information into another compatible system.

B. Semantic interoperability

Different systems can understand the meaning of information in the same way.

For example, two AI systems may use different internal structures but recognise that "customer ID," "consumer number," and "account identifier" refer to the same underlying concept.

C. Technical interoperability

Systems can communicate through:

• APIs;
• protocols;
• schemas;
• software interfaces;
• data formats; and
• authentication systems.

D. Functional interoperability

A product or service can work with complementary products supplied by competitors.

E. Knowledge-graph interoperability

Different knowledge graphs can exchange entities, relationships, ontologies and metadata.

This is increasingly significant because a dominant company may possess a proprietary knowledge graph that becomes an important input for:

• search;
• recommendation;
• AI training;
• enterprise intelligence;
• navigation;
• advertising;
• scientific research; and
• automated decision-making.

3. Competition-Law Problem

The competition concern arises when interoperability is necessary for effective competition but a powerful undertaking controls the relevant interface.

A simplified chain is:

Control of knowledge infrastructure → control of interoperability → dependence of rivals → higher entry barriers → reduced competitive pressure

The conduct can potentially fall within several competition-law doctrines.

4. Relevant Competition-Law Theories

A. Abuse of Dominance

A dominant undertaking may potentially abuse its position by:

• refusing interoperability;
• restricting API access;
• withholding essential metadata;
• degrading access;
• providing inferior interfaces to competitors;
• imposing discriminatory technical conditions;
• changing standards strategically;
• preventing data portability; or
• making interoperability conditional on purchasing another service.

The mere possession of proprietary information is not automatically unlawful.

The additional competition effects are crucial.

5. Refusal to Interoperate

A refusal to provide interoperability may become problematic where several conditions are present.

Typical considerations include:

1. dominance;
2. control of an important infrastructure or input;
3. lack of realistic alternatives;
4. substantial foreclosure of competition;
5. inability of competitors to reproduce the relevant resource within a reasonable period;
6. absence of a legitimate justification; and
7. potential harm to consumers or innovation.

This connects knowledge interoperability with the essential-facilities/refusal-to-deal doctrine.

6. Essential Facilities and Knowledge Infrastructure

An information resource may theoretically become strategically important enough to constitute an indispensable input.

Examples could include:

• a dominant knowledge database;
• an industry-wide technical ontology;
• a unique scientific dataset;
• a dominant search index;
• a proprietary interoperability protocol;
• a widely adopted identity database; or
• an indispensable API.

However, courts generally apply refusal-to-deal doctrines cautiously because compulsory access can reduce incentives to invest and innovate.

7. The Bronner Principle

The leading EU authority is:

1. Oscar Bronner GmbH & Co. KG v Mediaprint

The European Court of Justice established stringent conditions for treating refusal to provide access to infrastructure as abusive.

The case concerned a newspaper distribution system rather than a knowledge platform. Its importance for knowledge interoperability lies in the principle that an undertaking should not normally be forced to provide access to infrastructure unless the infrastructure is effectively indispensable and duplication is not realistically possible.

Competition-law relevance: A proprietary knowledge platform should not automatically be treated as an essential facility merely because competitors would benefit from access.

8. IMS Health and Indispensable Information

2. IMS Health GmbH & Co. KG v NDC Health GmbH & Co. KG

This case is particularly important for knowledge interoperability because it concerned a proprietary information structure used by pharmaceutical companies.

The Court identified circumstances in which refusal to license intellectual-property-protected information could constitute abuse.

The famous conditions included:

• access being indispensable;
• refusal being capable of excluding competition;
• refusal preventing the emergence of a new product for which consumer demand exists; and
• absence of objective justification.

Importance: IMS Health demonstrates how competition law can intervene when proprietary information becomes indispensable for downstream competition.

9. Microsoft and Interoperability

3. Microsoft Corp. v Commission

The Microsoft decision is one of the most important authorities concerning interoperability.

Microsoft was found to have abused its dominant position through restrictions concerning interoperability information for work-group server operating systems.

The Commission's theory was that withholding interoperability information could prevent rival products from effectively competing within a broader technological ecosystem.

The case demonstrates that interoperability can itself become a competitive parameter.

Key lesson

A dominant technology company cannot necessarily use control over technical information to make competing products structurally incompatible.

10. Magill and Information Reuse

4. RTE and ITP v Commission — Magill

The Magill litigation concerned television-programme information.

The case is significant because the underlying resource was information, rather than a conventional physical facility.

The Court developed circumstances in which refusal to license copyright-protected information could constitute an abuse.

The case is particularly relevant to knowledge interoperability because it illustrates the tension between:

intellectual-property exclusivity

and

competition in downstream information markets.

11. Google Shopping

5. Google Search (Shopping)

The European Commission's Google Shopping decision concerned Google's treatment of competing comparison-shopping services within its general search results.

Although the case was not formally a knowledge-interoperability case, it demonstrates the importance of access to information-distribution infrastructure.

Google controlled an important gateway through which consumers discovered information.

The competition concern was not simply that Google possessed information. Rather, the concern involved how the dominant platform used its position to favour its own downstream service.

Relevance to knowledge interoperability

Similar concerns may arise where a dominant knowledge platform:

• indexes rival information;
• controls discoverability;
• determines data visibility;
• privileges its own knowledge services; or
• restricts rival systems from accessing or using information.

12. Slovak Telekom

6. Slovak Telekom a.s. v Commission

This case concerned access to telecommunications infrastructure and margin-squeeze/refusal-of-access issues.

Although it did not concern knowledge infrastructure directly, it provides an important analytical analogy.

Where competitors depend upon infrastructure controlled by a dominant undertaking, competition law may examine whether the access conditions effectively prevent viable downstream competition.

Application to knowledge interoperability

The same reasoning can become relevant where:

A dominant knowledge platform controls an upstream interoperability layer and competitors must access that layer to compete downstream.

13. Bronner, IMS Health and Microsoft Compared

14. Knowledge Interoperability and Data Portability

Data portability is closely connected to interoperability.

A platform may make it technically possible for consumers to download their data but make it practically useless by providing:

• incomplete exports;
• incompatible formats;
• delayed transfers;
• loss of metadata;
• loss of relationships between data points;
• artificial technical barriers; or
• restrictions on automated transfer.

From a competition perspective, poor portability can increase switching costs.

15. Network Effects

Knowledge platforms frequently benefit from network effects.

For example:

More users → more information → better knowledge system → more users → more complementary services → greater data advantage

This can create a feedback loop.

If interoperability is restricted, the incumbent may preserve this advantage by preventing competitors from obtaining sufficient scale.

Thus, interoperability can act as a competitive counterweight to network effects.

16. Knowledge Silos

A dominant undertaking may create a knowledge silo by preventing external systems from accessing or understanding its information.

Examples include:

• proprietary schemas;
• closed ontologies;
• inaccessible APIs;
• incompatible metadata;
• restrictive licences;
• technical throttling;
• non-standard formats;
• authentication barriers; and
• contractual restrictions.

A knowledge silo becomes particularly important where competitors cannot realistically reproduce the underlying knowledge resource.

17. Discriminatory Interoperability

A particularly serious concern can arise where the dominant undertaking gives:

full interoperability to its own services but restricted interoperability to rivals.

For example:

• the platform's own AI system receives real-time data;
• independent AI systems receive delayed data;
• the platform's own application receives privileged API access;
• rival applications receive limited API calls.

This can transform interoperability from a neutral technical function into a foreclosure mechanism.

18. Interoperability and Self-Preferencing

Self-preferencing may occur when a dominant platform:

1. controls a knowledge infrastructure;
2. operates downstream services;
3. provides interoperability to those services; and
4. disadvantages competing downstream providers.

Potential effects include:

• reduced visibility;
• degraded service quality;
• higher costs;
• slower innovation;
• reduced consumer choice.

The Google Shopping litigation provides an important reference point for analysing this type of conduct.

19. AI and Knowledge Interoperability

AI creates particularly significant interoperability issues.

Modern AI ecosystems may depend upon:

• foundation models;
• knowledge graphs;
• vector databases;
• proprietary datasets;
• embeddings;
• APIs;
• model interfaces;
• retrieval systems;
• evaluation datasets; and
• agent protocols.

A dominant AI ecosystem could potentially restrict competitors through:

A. Model interoperability restrictions

Preventing other systems from accessing model outputs or interfaces.

B. Knowledge-graph restrictions

Preventing rival systems from querying proprietary knowledge structures.

C. API restrictions

Limiting:

• query volume;
• functionality;
• latency;
• metadata;
• authentication;
• exportability.

D. Training-data restrictions

Using contractual or technical mechanisms to prevent competing systems from accessing legally available information.

20. Competition and Semantic Interoperability

Semantic interoperability is especially important.

Suppose Platform A uses:

"Customer"

while Platform B uses:

"Account Holder"

and Platform C uses:

"Subscriber."

If the systems cannot translate these concepts, switching becomes costly.

A dominant platform might deliberately maintain proprietary semantic standards that make interoperability difficult.

Competition authorities may therefore examine whether apparently technical incompatibility has a strategic exclusionary effect.

21. Standard-Setting and Interoperability

Industry standards can solve interoperability problems.

However, standard-setting can itself raise competition issues.

Potential concerns include:

• exclusion of rival technologies;
• discriminatory participation;
• manipulation of standards;
• refusal to license essential standards;
• excessive licensing restrictions;
• discriminatory technical specifications.

The standard-setting process must therefore be examined both as a solution to interoperability problems and as a possible source of market power.

22. Intellectual Property and Competition Law

Knowledge interoperability often involves intellectual property.

A company may argue:

"This knowledge structure, database, protocol or interface is proprietary."

Competition law does not generally eliminate intellectual-property rights.

However, exceptional circumstances may justify intervention where IP rights are used in a manner that seriously undermines downstream competition.

The key balance is:

Innovation incentives ↔ competitive access

23. Objective Justifications

A refusal to interoperate may have legitimate reasons.

Examples include:

• cybersecurity;
• privacy;
• protection of trade secrets;
• system integrity;
• prevention of fraud;
• technical limitations;
• capacity constraints;
• intellectual-property protection;
• protection of confidential information.

Therefore, competition analysis should distinguish between:

legitimate interoperability limitations

and

strategic exclusionary restrictions.

24. Remedies

Competition authorities may employ several remedies.

Structural remedies

In extreme cases:

• divestiture;
• separation of business units;
• separation of data assets.

Behavioural remedies

More commonly:

• mandatory API access;
• interoperability obligations;
• data portability;
• non-discrimination;
• access on FRAND-type terms;
• technical standards;
• prohibition of self-preferencing;
• transparency obligations.

Technical remedies

Authorities may require:

• open APIs;
• common data formats;
• machine-readable exports;
• metadata portability;
• interoperability protocols;
• interface documentation.

25. Competition Effects

Authorities may consider whether restricted interoperability causes:

Foreclosure

Competitors cannot effectively compete.

Entry barriers

New entrants cannot obtain sufficient knowledge or technical compatibility.

Reduced innovation

Competitors cannot develop complementary services.

Higher switching costs

Consumers remain locked into the dominant ecosystem.

Reduced consumer choice

Fewer interoperable alternatives emerge.

Quality degradation

Consumers may experience inferior services even where prices remain zero.

26. Countervailing Innovation Considerations

Interoperability mandates can also have negative effects.

Excessive compulsory access may:

• reduce incentives to develop proprietary technologies;
• facilitate free-riding;
• compromise security;
• reduce investment in databases;
• undermine privacy;
• expose trade secrets.

Consequently, competition authorities generally need to calibrate remedies carefully.

27. A Competition-Law Test for Knowledge Interoperability

A useful analytical framework is:

Step 1 — Define the relevant market

Identify whether the relevant market concerns:

• knowledge databases;
• search;
• AI services;
• enterprise software;
• data analytics;
• information distribution;
• cloud services; or
• another downstream market.

Step 2 — Establish market power

Consider:

• market shares;
• network effects;
• switching costs;
• data advantages;
• technological barriers;
• economies of scale;
• ecosystem effects.

Step 3 — Identify the interoperability bottleneck

Determine precisely what is controlled:

• API;
• database;
• protocol;
• ontology;
• knowledge graph;
• metadata;
• identity layer;
• search index.

Step 4 — Examine indispensability

Can competitors realistically reproduce or replace the resource?

Step 5 — Examine foreclosure

Does the restriction materially impair competitors?

Step 6 — Examine innovation effects

Does interoperability promote or undermine innovation?

Step 7 — Consider objective justification

Are privacy, cybersecurity, IP or other legitimate interests involved?

Step 8 — Select proportionate remedies

The remedy should address the competition problem without unnecessarily eliminating legitimate proprietary incentives.

28. Additional Case Laws

The following authorities are also useful for studying the subject:

7. Commercial Solvents Corp. v Commission

Established important principles concerning refusal to supply and exclusion of downstream competitors.

8. Sea-Land Service Inc. v European Commission

Relevant to access and competitive conditions involving infrastructure and dominant undertakings.

9. Deutsche Telekom v Commission

Important for analysing access conditions and exclusionary effects involving infrastructure.

10. Bronner

Particularly important for determining when compulsory access to a facility may be required.

11. IMS Health

Especially relevant where the controlled resource is information or a proprietary information structure.

12. Microsoft

Especially important where the competitive problem arises from technological interoperability.

29. Relationship Between the Major Cases

The jurisprudence can be understood as an evolution:

Commercial Solvents
↓
Refusal to supply can exclude downstream competitors

Magill
↓
Information/IP can become competitively significant

Bronner
↓
Compulsory access requires strict indispensability

IMS Health
↓
Proprietary information structures may exceptionally require access

Microsoft
↓
Technical interoperability itself can be competitively significant

Google Shopping
↓
Control over information gateways can facilitate downstream foreclosure

This progression is highly relevant to modern AI and knowledge ecosystems.

30. Conclusion

Knowledge interoperability occupies an increasingly important position at the intersection of competition law, data governance, intellectual property, technology regulation and digital-market regulation.

The fundamental competition question is not simply:

"Does a company own valuable knowledge?"

Rather, it is:

"Does the company possess market power over a knowledge or interoperability layer and use that control in a way that materially restricts effective competition?"

The most relevant authorities include Magill, Bronner, IMS Health, Microsoft, Commercial Solvents, Slovak Telekom and Google Shopping. Together, they provide principles concerning refusal to deal, indispensability, proprietary information, interoperability, infrastructure access, foreclosure and downstream competition.