This page helps separate connected products, related services, product data, related-service data, metadata, readily available data, and excluded derived information before building access or sharing processes.
Use this classification aid with Regulation (EU) 2023/2854 and current European Commission guidance, then validate the result against the product architecture, contracts, and applicable law.
The Data Act Chapter II analysis starts with two questions: whether the object or software-service relationship is in the framework, and which generated data is product data or related-service data that is readily available with the metadata needed for use. Raw and pre-processed data will usually form the access package; inferred or derived information and content require a separate classification.
1
Section 1
What counts as a connected product within the scope of the EU Data Act?
A is not every digital device or every cloud service. The Regulation focuses on an item that obtains, generates, or collects data about its use or environment, can communicate product data through an electronic communications service, physical connection, or on-device access, and is not primarily used to store, process, or transmit data for someone other than the user.
That means the scope test should start from the physical item and its data path. Connected cars, health-monitoring devices, smart-home devices, aircraft, robots, industrial machines, agricultural machinery, smartphones, and TVs are examples in the Commission material, but the label is not enough; the item must generate or collect use, performance, or environment data and be able to communicate it.
Record the item, model or product family, firmware or embedded software, market configuration, and how data can leave the product.
Separate connected products from infrastructure the user does not own, rent, lease, or otherwise have contractual rights to use.
Do not treat servers, routers, or other products whose primary function is storing, processing, or transmitting data for another party as Chapter II connected products unless the user owns, rents, or leases them.
Mark prototypes and products not yet placed on the market separately because the Chapter II data-sharing analysis can differ.
Clarifies connected-product boundaries, including products whose main function is data storage, processing, or transmission and infrastructure-sensor examples.
2
Section 2
Which dates and enterprise exclusions change the Chapter II result?
The Data Act generally applies from 12 September 2025. The Article 3(1) duty to design connected products and related services so data is accessible by default applies only to products and related services placed on the market after 12 September 2026. That delayed design duty is separate from the Article 4 and Article 5 request-based access rules.
Chapter II excludes data generated through products manufactured or designed, or related services provided, by qualifying microenterprises and small enterprises. The exclusion is lost where the enterprise has a partner or linked enterprise that is not micro or small, or is subcontracted to manufacture, design, or provide the product or service. Article 7 also gives a narrower temporary exclusion to a newly medium-sized enterprise and certain recently placed products.
Keep product placement date, manufacturer size, related-service provider size, partner and linked enterprises, and subcontracting status in the scope map.
Do not apply the Chapter II enterprise exclusion automatically to B2G, cloud switching, unfair-term, data-space, or smart-contract duties.
Do not label every product placed on the market by 12 September 2026 out of scope; the transition in Article 50 postpones Article 3(1), not all Chapter II duties.
Recheck the temporary medium-sized-enterprise position after the one-year periods in Article 7 expire.
Article 7 sets the Chapter II enterprise exclusions, and Article 50 separates the general application date from the delayed Article 3(1) design duty.
Recommended next step
Build a Data Act product-and-data scope map
Turn connected-product architecture, related services, data fields, metadata, exclusions, and safeguards into a maintained scope record before implementing user or third-party access.
When is software a related service that falls under the Data Act scope?
A related service is a digital service other than an electronic communications service, including software, that is connected with the product at purchase, rental, or lease in a way that absence of the service would prevent one or more product functions, or that is later connected by the manufacturer or a third party to add to, update, or adapt the product's functions.
The practical test is whether the service affects the 's operation or behaviour. A washing-machine app that adjusts a cycle based on sensor data can be a related service. In the vehicle guidance, remote door locking, cockpit pre-conditioning, charging management, driver-preference syncing, and route optimisation shown on the dashboard are treated as examples of vehicle-related services.
Classify apps, software modules, cloud functions, and integrations by whether they add to, update, adapt, or control product functions.
Separate related services from analytics, consulting, insurance pricing, financial services, or offline repair work that only uses data and does not affect product operation.
Expect multiple data holders where a product maker and an app or service provider each obtain data from the same user relationship.
Attach the related-service contract and product-function dependency to the scope record.
Defines related service as software or another digital service connected to a product so that it enables, adds to, updates, or adapts product functions.
Explains the automotive related-service test and distinguishes vehicle-related services from offline repair, analytics, financial, and insurance services.
4
Section 4
Which product data and related service data are in scope of the Data Act?
Product data is data generated by use of the that the manufacturer designed to be retrievable by a user, data holder, or third party. Related-service data is data representing digitised user actions, inaction, or events related to the connected product during the provision of a related service.
Scope is field-level, not product-line-level. For each data stream, identify the event or sensor source, whether the data comes from the product or the related service, who can lawfully obtain it, and whether the user or a chosen third party needs metadata to interpret and use it.
Product data examples include sensor signals, status data, event logs, location, speed, pressure, temperature, liquid level, acceleration, and component condition where generated by product use.
Related-service data examples include app commands, service events, user settings, charging-management events, remote-control actions, and dashboard service interactions tied to the product.
Purely descriptive material in user manuals, packaging, or marketing copy is not product data for Chapter II access purposes, though Article 3 pre-contract information still matters.
For mixed datasets, flag personal-data fields separately because Data Act access and sharing must still comply with GDPR and ePrivacy conditions.
Clarifies that product data relates to product performance, use, or environment and that related-service data represents user actions, inaction, and product-related events during the service.
Lists vehicle-sector examples of raw and pre-processed product data, including sensor signals, component status, speed, battery level, odometer values, and fault codes.
5
Section 5
How should readily available data and metadata be classified under the Data Act?
Readily available data means product data and related-service data that the data holder lawfully obtains or can lawfully obtain from the or related service without disproportionate effort beyond a simple operation. The analysis should therefore cover both data already retrieved and data the architecture can lawfully retrieve without disproportionate effort.
Metadata is part of the access package when it is necessary to interpret and use the data. A useful metadata dictionary names units, timestamps, identifiers, sampling or collection frequency, format, quality limits, location or context fields, retention, and the source system that supplies the value.
Classify each field as directly accessible from the product, indirectly available through the data holder, lawfully retrievable but not currently stored, or not readily available.
Record the technical reason when a field cannot be obtained without disproportionate effort, such as architecture limits, transmission constraints, or data deleted before any party can access it.
Include metadata needed for practical use, not only schema labels; examples include units, time zone, sensor identity, calibration state, collection conditions, and quality notes.
Do not omit metadata protected as a trade secret from the analysis; identify protected metadata and the confidentiality measures needed if it must be shared.
Explains metadata as information needed to understand conditions such as time, weather, or location under which data was collected or generated.
6
Section 6
Where is the Data Act line between raw, pre-processed, and derived data?
Chapter II covers raw and pre-processed data, plus metadata needed to make that data understandable and usable. Pre-processing can include preparing sensor output so it describes a physical quantity or quality, such as temperature, pressure, flow rate, audio, pH value, liquid level, position, acceleration, or speed.
Inferred or derived information is different. It is usually the result of additional investment, proprietary or complex algorithms, substantial transformation, sensor fusion that creates new insight, or analytics that assign new value beyond the underlying measurement. The data holder should still assess whether the underlying raw or pre-processed input data remains in scope.
Treat calibrated, normalised, reformatted, filtered, timestamped, unit-converted, or basic calculated measurements as potentially in scope when they still describe the underlying event or condition.
Treat predictions, proprietary scoring, behavioural profiles, object detection, complex diagnostics, and model-derived insights as candidates for the derived-data exclusion.
Do not use the word derived as a blanket exclusion for any data that passed through a pipeline; explain what new information or investment changes the classification.
Keep content such as films on a smart TV or creative audiovisual material separate from device-use telemetry such as brightness, battery, timestamps, location, and event logs.
Provides sector examples of raw data, pre-processed data, derived information, sensor fusion, predictions, and basic mathematical operations.
7
Section 7
What exclusions and safeguards should appear in the Data Act scope record?
A complete scope record should list data to share and explain excluded data, protected data, and conditions that may affect delivery. Tie each exclusion to a legal definition, guidance example, technical architecture fact, or protection measure.
Common exclusions or constraints include inferred or derived information, content protected by intellectual property rights, unavailable edge-processed data that no party can access, personal data without a valid processing basis, trade secrets needing confidentiality measures, security restrictions based on EU or national law, gatekeeper ineligibility for third-party access, and the ban on using accessed data to develop a competing .
For each excluded field, name the reason: not product data, not related-service data, not readily available, inferred or derived, content, personal-data constraint, trade secret, security restriction, or other law.
For each protected but shareable field, record the safeguard: access control, confidentiality terms, encryption, metadata marking, quality limits, recipient restrictions, or authority notification route.
For each third-party request path, check whether the recipient is eligible and whether the requested use could develop a competing .
Review the record when product architecture, related services, data pipelines, retrieval design, guidance, or contracts change.
Supports the access, third-party sharing, trade-secret, security, personal-data, gatekeeper, and competing-product limitations that affect scope records.
Explains that content and highly enriched data are out of scope and gives examples for cameras, smart TVs, and sensor-like imagery.
8
Section 8
What should the finished Data Act scope map for connected products contain?
Create a product-and-data scope map before product, legal, security, engineering, and support teams write notices, access portals, APIs, contracts, or helpdesk scripts. A reviewer should be able to trace each field from product architecture to Data Act classification.
Keep the map concise enough to maintain, but specific enough to stop overbroad exports and unsupported exclusions. The record should show the product or service, user relationship, data holder, data category, availability, metadata, safeguards, delivery route, source, owner, and review trigger.
Product/service fields: name, related service name, product function affected by the service, user type, data holder, recipient paths, and relevant contracts.
Data fields: source event or sensor, product data or related-service data classification, raw/pre-processed/derived label, readily available status, metadata needed, format, quality, and retention.
Exclusion fields: excluded category, cited reason, technical fact, safeguard or restriction, reviewer, and escalation path for trade-secret, security, or personal-data issues.
Maintenance fields: product owner, legal reviewer, engineering owner, last reviewed date, change trigger, and citation to the official source used for the classification.
Article 3 pre-contract information requirements and Articles 4-5 access duties support maintaining a field-level record of data types, formats, access means, metadata, and data holders.
Provides the data-in-scope factors that can be translated into scope-map columns: data category, availability, enrichment level, personal-data status, and trade-secret status.
Binding legal source for connected product, related service, user, data holder, product data, related-service data, readily available data, metadata, direct access, user access, and third-party sharing duties.
Defines connected product, user, data holder, product data, related-service data, and readily available data for the Chapter II scope analysis.
Article 7 sets the Chapter II enterprise exclusions, and Article 50 separates the general application date from the delayed Article 3(1) design duty.
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Defines related service as software or another digital service connected to a product so that it enables, adds to, updates, or adapts product functions.
Provides the legal definitions of product data and related-service data and ties access duties to those categories.
Defines metadata and readily available data, and requires relevant metadata where data is made accessible to users or third parties.
Supports the access, third-party sharing, trade-secret, security, personal-data, gatekeeper, and competing-product limitations that affect scope records.
Article 3 pre-contract information requirements and Articles 4-5 access duties support maintaining a field-level record of data types, formats, access means, metadata, and data holders.
Implementation FAQ used for data-in-scope factors, enrichment boundaries, metadata, content exclusions, edge processing, and connected-product boundary examples.
Clarifies connected-product boundaries, including products whose main function is data storage, processing, or transmission and infrastructure-sensor examples.
Clarifies that product data relates to product performance, use, or environment and that related-service data represents user actions, inaction, and product-related events during the service.
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Explains metadata as information needed to understand conditions such as time, weather, or location under which data was collected or generated.
Explains the distinction between raw and pre-processed data in scope and inferred or derived data outside Chapter II.
Explains that content and highly enriched data are out of scope and gives examples for cameras, smart TVs, and sensor-like imagery.
Provides the data-in-scope factors that can be translated into scope-map columns: data category, availability, enrichment level, personal-data status, and trade-secret status.
Commission overview used for practical examples of connected products, related services, raw and pre-processed data, metadata, user access, third-party sharing, and limitations.
Gives practical examples of connected products and explains user control over data generated by owned, rented, or leased connected products.
Uses smart-fridge and washing-machine app examples to show how related services can sit beside the connected product.
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Explains that Chapter II covers raw and pre-processed data readily available to the data holder, including relevant metadata.
States that inferred or derived data and content, such as highly enriched data and audiovisual material, are out of scope.
Summarises practical limits on use of accessed data, GDPR interaction, trade secrets, security requirements, and third-party sharing.
Official Journal guidance used for concrete automotive examples of related services, raw data, pre-processed data, derived information, readily available data, and access-quality expectations.
Explains the automotive related-service test and distinguishes vehicle-related services from offline repair, analytics, financial, and insurance services.
Lists vehicle-sector examples of raw and pre-processed product data, including sensor signals, component status, speed, battery level, odometer values, and fault codes.
Show 2 more
Provides sector examples of raw data, pre-processed data, derived information, sensor fusion, predictions, and basic mathematical operations.
Shows how a sector-specific implementation can turn Data Act scope rules into data-point classifications and access-quality checks.