XBRL Data Collection and Parsing
XBRL is becoming the “de facto” standard for the reporting of corporate financial data. XBRL is an XML/HTML based data format. XBRL data can be embedded in HTML documents, in a format called iXBRL (or XBRLi). By mixing XBRL and HTML, corporates can publish their financial reports on the internet in a format which is readable both for humans and computers.
Several countries started to require their national companies to publish their financial reports in XBRL a few years ago. The United Kingdom (The Company House) was one of the first countries to embrace the standard. The USA and the SEC also started to promote the use of XBRL on an early stage (2009). Today, the adoption of the standard accelerates, with the help of the XBRL association.
A large variety of software are available today to publish XBRL documents. Most financial reporting software such as Sage, SAP and the likes can export data in XBRL format effortlessly.
A key challenge: XBRL parsing
A real technical challenge remains: reading XBRL documents to collect data from XBRL documents and to make sense of the data. Very often, financial institutions or financial departments have specific data models, which need to be properly feed with external data. This is the challenge XBRL parsing and of field mapping.
XBRL Taxonomies: mapping fields to sectors or reporting standards
Taxonomies: these are dictionaries which specific how data fields are mapped. Taxonomies can be specific to some business sectors and reporting standards (IFRS, US GAAP).
XBRL Contexts, XBRL Units and Data fields
Within an XBRL document, the information can be contained in several types of nodes:
XBRL Context Nodes specify the context in which the information is provided. The context specifies the reporting entity, the reporting period and sometimes the taxonomy which applies to the data items which are reported.
XBRL Unit nodes specify the units in which the data is reported. For instance, the unit can be “GBP” (if it is UK financial data), or “Share” if the numbers relate to shares. Units can also be combinations of basic units, such as “square meters”, or “euros per kilogram”.
XBRL Data nodes contain the information itself. Data nodes often have attributes which relate them to the context (“contextref”) or the unit (“unitref”).
Basedig, the leading provider of structured data collection service and software, provides XBRL data collection services and an XBRL Parsing module. Do not hesitate to contact us for more details.
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