On the surface, Data may appear to be a simple, straightforward concept that “everyone” understands, but it's not. It is actually a complex concept with multiple facets and interpretations. Data is generally considered a plural term with the singular form being datum, however, common usage allows for data to be considered as singular with the singular-plural differentiation being restricted to academic and scientific usage. 1)
A more formal definition of data is provided by the Organisation for Economic Co-operation and Development (OECD)2):
In essence, Data are individual elemental facts, statistics, or items of information, often numeric, collected through observation. Technically, data is a set of qualitative or quantitative values about one or more persons or objects, 3) while a datum (singular of data) is a single value of a single variable. 4)
Unfortunately, the terms “data” and “information” are commonly used interchangeably. Nevertheless, these terms have distinct meanings and are part of a larger framework defining an increasingly ordered set of cognitive layers. See: Appendix I: Cognitive Model.
At the lowest layer of the Cognitive Model, data forms the basis for the other layers with each layer above being a transformation of the layer(s) below. For example, at the lowest Business Management cognitive layer is the Data layer, which includes basic data like sales data, revenue, profits, and stock prices. The next layer of the Cognitive model is for information that is usually an association of data to each other. For example, stock prices as related to profits. The next layer is knowledge which might be a correlation of how profits are related to stock price. At the highest layers of the cognitive models – Understanding and Wisdom – data, information and knowledge are presented in the form of data visualizations (e.g., scatter plots, heat maps, and network models).
Data has been described as the new oil of the digital economy. 5)6)
There are several taxonomies that cover Data within a DIDO. These taxonomies are not additive in nature but also not mutually exclusive. For example, any data within the DIDO can have a Cognitive classification, as well as, a state and/or a digital taxonomy. A piece of data can be classified as Knowledge, At Rest, and a Coin; or might just as easily have been classified as Understanding, In Motion, and a Non-Fungible asset.
Data taxonomies are described in detail in the following sections:
Data is a complex concept that, unfortunately, when employed as a term is overloaded. Generically, it can describe any of a range of concepts from a simple data point to a complex range of data and their associations. In the Cognitive Model data is just one level in the human cognitive hierarchy.
We usually do not think of data content as separate from the system in which it is stored; however, this distinction is very important from the perspective of intellectual property rights. The question is what, if anything, is protected by Copyright. Under U.S. law, data that is merely factual has no copyright protection; it is not possible to copyright facts. Not all data is in the public domain. A project might, for example, use copyrighted photographs because the photographs are part of the project’s “data.” In many cases, the data in a data management system, as well as, the metadata describing that data will be factual, and hence not protected by copyright.
A database, on the other hand, can have a thin layer of copyright protection. Deciding what data needs to be included in a database, how to organize the data, and how to relate different data elements are all creative decisions that may receive copyright protection.
Because of the different copyright statuses accorded to databases and their data content, different mechanisms are required to manage each. Copyright can govern the use of databases and some data content (that which is itself original). In contrast, contract law, trademarks, and other mechanisms are required to regulate factual data.
The third word in the acronym DIDO is Data, therefore every node manages and controls data. The data within a node is classified as either: ledger data, ancillary data or external data.
[char]This section has been heavily revised -- need to review