# Data standards

As systems become more digitized, solving incompatibilities between data from different systems can be expensive and time-consuming. A key precursor to interoperability is a shared understanding of the meaning of data used in communication. Data standards refer to the guidelines that dictate how data should be documented and recorded. These standards are essential for the effective exchange, sharing, and comprehension of data, as they ensure both the syntax (structure) and the semantics (meaning) of the data are uniform. By establishing clear definitions and expected formats for data, data standards facilitate the creation, sharing, and integration of data. They also play a crucial role in eliminating uncertainties and inconsistencies in data usage.&#x20;

Some examples of data standards are ISO 10962 Classification of Financial Instruments, [ICD 10](https://icd.who.int/browse10/2019/en),[ LOINC](https://loinc.org/)  in healthcare, [FI information standards](https://api.rebit.org.in/) in Account Aggregator, and many more!

Many of these standards are extendable implying countries can adopt some of these global standards as a base and contextualize it to suit their local requirements.

Any country on the journey of adopting a national standard can use adaptors (to solve incompatibility issues in the interim) to hasten the process. As harmonizing data standards used by all institutions is a behemoth task, multiple data standards can **co-exist as long as they are self-identifying**.


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