Information
Information is something that has the power to inform. Information theory is the scientific study of the quantification, storage, and exchange of information.
In his book, Nexus: A Brief History of Information Networks from the Stone Age to AI, the author Yuval Noah Harari provides a comprehensive explanation of information. He begins with "stories" and how people first exchanged information by word of mouth. Then he explains how "lists" and the first "spreadsheets on clay tablets" supplemented stories. Then "documents" created by scribes, how the "printing press" changed things. Eventually Harari gets to artificial intelligence.
Many people tend to use the terms "data" and "information" almost interchangeably. But this era is called the information age and not the data age for a reason. To communicate more precisely it is important to understand which you are actually talking about.
There is a difference between data, information, knowledge, insight, and wisdom. Data is raw and unprocessed and tends to be understandable only in one, usually local, context. Information is data that has been processed, classified, organized, and put into context, therefore understandable globally by anyone. Knowledge is refined and actionable information that has been further processed, organized, and/or structured in some way making the information super-useful and therefore valuable. Insight and wisdom is even more valuable and comes from applying information stored as super-useful knowledge to some specific situation, usually by a subject matter expert with the skills and experience necessary to know how to use the knowledge, such as making a decision.
In essence, data is the raw material, and information is the product derived from processing that raw material. Information adds value to data by giving it context and meaning. Knowledge is a super-useful set of information. Insight and wisdom is what you get from applying knowledge stored as super-useful information.
New business models are possible when information which was only understandable by humans is now interpretable by machines. Data, information, knowledge and other products can be created that are machine-readable and can be used to drive modern software applications such as intelligent agents and such. It is my view that accountants, auditors, and analysts will create such products to package and sell their hard earned knowledge. These products could even be packaged as nonfungible tokens (NFTs) for product delivery, traceability, trustworthiness, curation, maintenance, and such.
Subject matter experts in specific areas of knowledge will have the ability, I believe, to earn passive income for their skills and experience in new ways. Organizations such as professional services firms will be able to retain knowledge accumulated by their employees. Software creators will be able to take advantage of data, information, knowledge and wisdom in order to make their software more functional and add useful new capabilities.
I have personally explored and experimented with this using XBRL-based knowledge graphs. While XBRL is quite general and useful, even more powerful alternatives such as RDF and graph databases can also be used to represent information.
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