Data Standards: Rosetta Stones for the Digital Age & FDTA

Author: Dean Ritz, Senior Fellow, Data Foundation

This is part of a series of articles for the benefit of implementing the Financial Data Transparency Act of 2022 (FDTA), and shortened form of an associated paper. In this contribution to the series we address what is meant by the phrase “data standard.”

Disclosure: The author made use of generative AI tools to assist his research and drafting. 

Data standards play a crucial role in ensuring efficient and accurate communication and information exchange, as they serve as the “Rosetta Stone” for data. Data standards consist of two parts: 

1) a conceptual model that captures the meaning and relationships of each piece of data in a way that humans can understand, and 

2) a machine-readable implementation that expresses the conceptual model in a format that computers can process and share. 

For government agencies implementing data standards under the Financial Data Transparency Act (FDTA) of 2022, the data standardization effort primarily, though not trivially, involves documenting in a machine-readable format the knowledge already understood by people, as reflected in existing information collection requirements and practices.

Data standards transform your documentation, one byte at a time.

Imagine a world where every book was written with different symbols, not just different language, every sign and stroke in an unknowable script. Chaos, yes? The digital landscape without data standards is not that different. In the interconnected world, data standards serve as modern-day Rosetta Stones, translating the diverse representation of data meanings into a common language comprehensible to both machines and humans. 

The original Rosetta Stone, with its trilingual inscription, was pivotal in deciphering Egyptian hieroglyphs, providing a breakthrough in linguistic archaeology. Similarly, data standards act as crucial interpreters in the digital realm, enabling the seamless exchange of information across a variety of platforms and systems. The standardization of meaning ensures that data is not only accessible but consistently interpretable across disparate technological landscapes.

The enactment of the FDTA underscored the critical importance of robust data standards in our modern economy. The FDTA's focus on the Financial Stability Oversight Council (FSOC) agencies emphasizes the need for interoperable data among agencies working on similar topics and establishes a strategic priority for semantic data—organizing information based on meaning rather than format or storage location. Semantic standards required by the FDTA can transcend technical specifications; they are fundamental frameworks ensuring data integrity and interoperability across governmental and private sectors. 

One of the key lessons from the global financial crisis is the necessity for data standards as a mechanism for interoperability, facilitating earlier detection of systemic risks. 

What would such a standard look like? Consider a simplified example from our technical report, Data Standards: A Rosetta Stone for the Digital Age, which illustrates how a single data element can be encoded in multiple formats (XML and JSON). This demonstration underscores the efficacy of data standards in maintaining consistency and accuracy across different systems.

For those inclined to greater levels of detail about the information theory and frameworks for semantic data, consider these two Data Foundation reports: Implementing the FDTA: From Data Sharing to Meaning Sharing (2022), and Understanding Machine-Readability in Modern Data Policy (2020).

In short, context matters and standards bodies rarely start from scratch. Instead, standards groups build upon existing, fundamental data standards to create new, more specialized ones. This layered approach allows for efficient and consistent development of data standards across various domains.

By building upon existing data standards, new standards can be developed more efficiently, ensuring consistency and compatibility with established systems and processes. This layered and interoperable approach to data standards enables the creation of a rich ecosystem of machine-readable data formats that can be used across various industries and domains.

The importance of interoperability extends beyond regulatory bodies to capital markets and law enforcement, particularly in detecting sophisticated financial crimes like money laundering. 

Data standards play a pivotal role in bridging the gap between human semantic understanding and machine syntactic processing. This alignment not only facilitates more efficient data retrieval for human users but also enhances the capabilities of artificial intelligence applications to better serve human interests.

Data standards play a crucial role in enabling efficient communication and information exchange across various sectors.

In essence, data standards make data make sense, weaving together our digital infrastructure, enabling everything from personal financial management to global economic analysis, and improving efficiency, transparency.