Data Sharing Community
Welcome to the Portal of the CDQ Data Sharing CommunityThe CDQ Data Sharing Community is a trusted network of user companies to manage business partner data collaboratively. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
What's new? (RSS)Sorting of Identifier Qualification results in Tax Guard introduced (7 February 2025)We are happy to announce that Tax Guard Identifier Qualification supports now the sorting of qualification results. VALID and INVALID decisions are now visible at first since they are the most important ones. After them, all the other decisions except NOT PROCESSED ones that are provided at the end. The algorithm behind takes into account the decisions separately as well as all of them together. As a result important results are visible at first page(s) whereas not important ones (NOT PROCESSED) at the end. This minor feature is extremely powerful when using different data data sources for multiple business partner identifiers. It is available out of the box and does not have to be set in the configuration. It is introduced in both: in the API and in the apps. New Data Sources: Business Partner Information from Chile (30 January 2025)We are excited to announce the integration of three new commercial data sources providing business partner information from Chile. These sources, offered by SintegraWS, allow retrieving company data using the Chilean tax identifier (RUT) and cover different aspects of business entity verification. Integrated Data Sources1. CL.SINSII – Provides company information as published by the Chilean tax authority (Servicio de Impuestos Internos - SII). Includes:
AvailabilityThe new data sources are now available to customers using our Business Partner Lookup service, as long as they have the required API token from SintegraWS. To enable access and discuss integration details, please contact your CDQ representative. CDQ Resource Limits for Organizations (17 January 2025)To comply with OWASP certification requirements, CDQ has implemented resource limits for organizations. The following restrictions apply:
Data modelAn important prerequisite for collaborative data management is a common understanding of the shared data. For the CDQ Data Sharing Community, this common understanding is specified by the CDQ Data Model. The concepts of this model are defined and documented in this wiki which can be used as a business vocabulary. Moreover, the wiki provides a machine-readable interface to reuse this metadata by using semantic annotations. ![]() Data maintenance proceduresA procedure is a common standard or "how-to" for a specific data management task. Within the CDQ Data Sharing Community, companies agree on such procedures to ensure similar rules and guidelines for similar tasks. For several countries, the CDQ Wiki provides such information, e.g. data quality rules, trusted information sources, legal forms, or tax numbers. Try
or select another country from the list. |
Data sources
Metadata and Standards: Metadata-driven Data QualityData quality plays a pivotal role in ensuring compliance with legal, regulatory, and industry standards. One of the core challenges in achieving high data quality is adhering to dynamic data requirements that evolve due to changes in national regulations. These requirements vary by country, making it essential for businesses to track and update compliance criteria continuously. In many countries, official company information is available as Open Data, but the lack of a standardized data model or provision method complicates the process of integrating this data. The Data Sharing Community actively collaborates to identify global data requirements and reference data sources, whether Open Data or commercial.
Data Quality RulesTransformation of human-documented data requirements into executable data quality rules is mostly a manual IT effort. Changing requirements cause IT efforts again and again. Some checks, e.g. tax number validity (not just format!), require external services. Other checks, e.g. validity of legal forms, require managed reference data (e.g. legal forms by country, plus abbreviations). Continuous data quality assurance (i.e. batch analyses) and real-time checks in workflows often use different rule sets. Data requirements and related reference data are collected and updated collaboratively by the Data Sharing Community. Data quality rules are derived from these requirements automatically. All data quality rules are executed behind 1 interface, in real-time. Batch jobs and single-record checks use the same rule set and can be integrated by APIs. For proving that a data quality rule is content-wise correct we maintain supporting document(s) per data quality rule which share the rule's source. This could be:
We manage the URL (if any), a screenshot of the relevant parts (if any) and the source's name (e.g. Community member data standard, European Commission, National ....) See Identifier format invalid (SIREN (France)) as an exemplary rule that was specified and implemented based on information provided by the OECD. |