Data Sharing Community

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Welcome to the Portal of the CDQ Data Sharing Community

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 Sources

1. CL.SINSII – Provides company information as published by the Chilean tax authority (Servicio de Impuestos Internos - SII). Includes:

  • Company name
  • RUT identifier
  • Business activity details (economic activities, category, VAT applicability)
  • Registration status


2. CL.SINPF – Offers business partner financial data from DICOM, a Chilean credit and risk assessment database. Includes:

  • Financial risk indicators
  • Outstanding debt information
  • Business partner’s activity history
  • Personal financial accreditations and property data


3. CL.SINPJ – Also retrieves company information from DICOM, specifically for legal entities. Provides:

  • Company name and RUT
  • Financial standing and debt records
  • Shareholder structure


Availability

The 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 Mirror: 1 per workspace
  • Mappings: 1000 per organization
  • Workspaces: 25 per organization
  • API KEY: 2000 per organization
  • Configurations: 100 configurations of specific type per workspace
  • Users: 1000 per ORG (SSO not included)
  • Knowledge Graphs: 100 per workspace
  • Knowledge Graph Models: 100 per knowledge graph


If needed, these limits can be adjusted upon request. Please contact us for further assistance.

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Data model

An 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.

This is a graph with borders and nodes that may contain hyperlinks.

Data maintenance procedures

A 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

Active data sourcesRecords
Data source BR.RF64,017,276
Data source CDQ.INTEL50,195,360
Data source VIES50,000,000
Data source FR.RC40,047,784
Data source GB-EAW.CR8,507,568
Data source US-FL.BER6,073,238
Data source JP.CR5,580,568
Data source AU.BR4,806,128
... further results
The CDQ Data Sharing Community uses a collaboratively managed reference data repository. This incorporates the integration of external data sources for enriching or validating business partner and address data. Examples of available data sources are 316 countries (e.g. WORLD (World), AT (Österreich, Austria, Autriche, 奥地利), BE (Belgien, Belgium, Belgique, België, 比利时)), 993 legal forms (e.g. ), and 72 active business partner data sources (e.g. Data source CDQ.POOL, Data source VIES, Data source CH.UIDR).

Metadata and Standards: Metadata-driven Data Quality

Data 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.

Short description
Managed reference data for administrative areas with language-specific terms and short names according to ISO 3166-2.
Managed reference data for bank accounts worldwide.
Managed reference data for types of identifiers per country.
Basic data concepts of CDQ Cloud Services.
Managed reference data about compliance lists considered in the sanction and watchlist screening services
Managed reference data for countries with language-specific names and short names according to ISO 3166-2.
Documentation of data quality rules with explanation and technical constraints to validate business partner data records.
Data quality rule functions are methods implemented in a programming language for being used in data quality rule implementations. They can be e.g. used in custom data quality rules similar to functions employed by business users in popular spreadsheet applications such as Microsoft Excel.
Managed reference data for legal forms with official and commonly used abbreviations and corresponding country.
Managed reference data for localities, such as exonyms.
Managed reference data for post codes
Managed reference data for postal delivery points, such as Post Office Boxes used for identification, extraction, harmonization and standardization.
Managed reference data for issuing bodies of identifiers
Managed reference data for thoroughfares of type Street (CDQ.POOL) used for harmonization and standardization.

Data Quality Rules

Transformation 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:

  • a public authority source
  • any other trustful webpage
  • a data standard of a specific community member

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.