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Revised EPO guidelines on the patentability of database management systems

Date: 17 December 2020

The revised Guidelines for Examination at the EPO due to be published in March 2021 include a whole new chapter G-II, 3.6.4 on the patentability of database management systems and information retrieval. Database management systems are technical systems that are implemented on a computer for storing and retrieving data using various data structures for efficient data management. Consequently, methods performed in a database system constitute methods using technical means and are not excluded from patentability under the EPC.


Features specifying the internal functioning of a database system are generally considered to be based on technical considerations, i.e., to have technical character, and may therefore contribute to inventive step. For example, in T 1924/17 the Board of Appeal concluded that the claimed database system was based on technical considerations “that concern a specific manner of improving response times for queries by automatically using different data stores, relational database management systems and NoSQL data stores, to manage data tables”. However, not all features of a database system necessarily contribute to its technical character. For instance, a feature related to the accounting of costs for using the database system is usually not considered technical.

Information retrieval

The Guidelines distinguish between i) the execution of structured queries by a database management system and ii) information retrieval, i.e., the determining what information to retrieve. Information retrieval includes, e.g., searching for information in a document, searching for documents as such, and searching for metadata that provides information about other data.

A user may, for example, enter a search query into a web search engine using informal natural language. If the subsequently performed method of information retrieval is solely based on non-technical considerations such as cognitive content, linguistic rules or other subjective criteria (for instance, relevance to friends in social networks), it is considered non-technical. For example, using for information retrieval a mathematical model that calculates the probability of a search term being semantically similar to another term by analysing the co-occurrence frequency of the two terms in a collection of documents does not make a technical contribution per se since it is based on considerations of a purely linguistic nature instead of technical considerations. In contrast, optimising the execution of structured search queries with respect to the required computer resources is considered technical.

Data structures

Regarding data structures used in database systems the Guidelines apply the same principles as described in Chapter G-II, 3.6.3 “Data retrieval, formats and structures”. If the data structures serve a functional purpose, i.e., contain functional data such as an index, a hash table or a query tree facilitating data access, they are considered of technical character since their aim lies in controlling the operation of the database system. On the other hand, data structures that are solely defined by cognitive data are not considered technical beyond the mere storing of the data. Data is classified as cognitive data if it is only relevant to the human user. Apart from functional data and cognitive data a data structure may, for example, include features solely aimed at facilitating the work of the programmer. However, facilitating the work of the programmer is not a technical function, and corresponding features can therefore not contribute to inventive step.


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