The standard for the quality of the dataset provided by the liable party is the division of the quality of the dataset into six levels:

• 0 - the dataset is not provided in electronic form,
• 1 - the dataset is available in a web environment,
• 2 - the dataset is structured, allowing automated processing,
• 3 - the dataset is in an open format independent of any particular proprietary software,
• 4 - the referable identifiers are used to identify the dataset data (URI),
• 5 - the dataset and its internal and external relationships are linked through URIs and described through the Central Data Model.

The open way of publication of a dataset is fulfilled if:

• the legal aspects of access to and use of the data are explicitly dealt with,
• it is possible to establish legal relationships for the use of the data also through anonymous remote automated access,
• the access to the data is made available to all persons under the same conditions, these conditions being explicitly stated,
• the data can be used for both non-commercial and commercial purposes and can be combined with other data, supplemented, corrected, modified, or used from the dataset without any obligation to use the other data in the dataset,
• the activities referred to in the previous point are gratuitous.

The standard for publishing data as open data is to publish it under an open licence - in particular Creative Commons CC0 or CC-BY.

The scope of mandatory metadata for the catalog, datasets and distributions is defined by the international application standard for metadata Data Catalog Vocabulary - Application Profile (DCAT-AP) and its national specialization DCAT-AP-SK 2.0. For internal use or to improve searchability, an organisation may extend the metadata list with additional metadata.

The standard for providing open data is:

• the designation of the dataset quality level (1 - 5),
• the use of formats according to Section 13 (CSV, JSON, XML version 1.0, RDF/XML, RDF/JSON-LD), with CSV and JSON formats having the highest achievable quality level of 3 and RDF formats having the highest achievable quality level of 5,
• when transferring data elements, providing the dataset data schema using the XML Schema Definition (.xsd) schema language at least in version 1.0, using a textual description when using CSV and JSON formats,
• when identifying each entry in the dataset, the use of a URI, a codebook code and a value representing that entry.

Datasets published as open data must not be published in the form of data that has already been processed or filtered in some way, either in the form of selection or aggregation of data.

The duality rule also applies to open data standards. This means that open data must be published simultaneously in both forms:

• readable to humans
• readable for machine processing

For some areas there are international standards, for other areas there are only unwritten "de-facto" standards, such as ISO, IETF, EU, OASIS, OGC. National standards need to be developed for these unwritten standards at all levels of semantic interoperability, and compliance needs to be enforced.

The machine processability of data is highly dependent on the ability to automatically make connections between data and derive insights from the dataset. Data links are created by identifying the content of a data attribute (e.g., people with the same name). The goal is to use universally referable identifiers (URIs), which, at the highest level of data quality, form the basic expressive element of a language for describing data.

Ontologies are structures describing some thematically coherent set of data in a way that enables machine inference, i.e. data processing with respect to the meaning of the data.

The use of ontologies in data definition is a prerequisite for achieving open data quality in levels 4 and 5.