What is a Knowledge Economics?

The meaning of knowledge economy in traditional Macroeconomics refers to intellectual capital as the mean of production and consumption.1 

However there is a different approach of Knowledge Economy and a very interesting definition of “metadata capital” and it’s role in knowledge organization systems presented by Jane Greenberg:

Metadata capital – is an asset, the value of which may increase via reuse.(..) If a good quality metadata is reused over time, there might be an increase in it’s value in comparison to the initial investment to produce it.” 2

A refined definition of metadata capital presents the following meanings:

An asset that contains contextual knowledge about content.
a. Content is the data or information contained in any information object (any “entity, form, or mode”).
b. Context is who, what, where, when, how, why, etc., which can be captured via metadata attributes (Kunze, 2001).
2. A product or service generated by human labor and/or machine-driven
processes with value that increases over time or that enables the value increase of other assets.
3. A good (a service facilitator) supporting a range of functions such as discovery, provenance tracking, rights management, authentication, preservation and other functions associated with lifecycle management and access.
4. A public good if the product (metadata) is open, following which the services can be open.” 3

The role of Ontologies

In the modern world where the amount data is overwhelming – Ontologies and Knowledge Graphs play particularly important role.

Considering the Ontologies for the Financial Industry a key role plays FIBO Ontology (Financial Industry Business Ontology) which enables understanding of data among various financial institutions and regulators.
For more information, please visit: FIBO

Another example of a world wide known Ontology is the ICARUS Ontology which represents knowledge for the aviation sector.
For more information please visit: ICARUS

The role of Knowledge Graphs

As Barassa, Holder and Webber present in their book “Knowledge Graphs. Data in Context for Responsive Business”  “Data is one of a modern business best assets and knowledge graphs are a tool that we can use to restore sanity of data by imposing an organizing principle to make data smarter.” 4

Moreover Knowledge Graphs with their features of findability, accessability, interoperability and resuability help to build data fabric on top of data lakes and data warehouses.5

The role of Graphchain in Knowledge Economics

With its key feature of building trusted, irrefutable, immutable, and secure graph databases in blockchain Graphchain can be sucessfully implemented in the following business use cases:

1. Enhanced Know Your Customer (KYC) for B2B transactions

Data about businesses available in knowledge graphs like  for example in lei.info portal could be enhanced by some provider that would offer much deeper information about the company. This combined data could be sold to credit bureaus, potential business partners or banks. Moreover such transactions could be represented as smart contracts in blockchain nodes.

2. Scientific and engineering data marketplace.

A data included in scientific or engineering publications (such as: tables, numerical data, figures) could be encoded as an RDF object and offered to readers by blockchain based subsystems.
Ontologies represented in Knowledge Graphs could be adopted to every marketplace related to the exchange of knowledge and data.

3. Intelectual property rights for digital art in Blockchain.

One of the most interesting business use cases is the exchange of intellectual property rights in Blockchain like for instance objects of digital art. In such case every digital artefact could be presented as Knowledge Graph and encrypted by our iHash algorithm. Such digitial objects could be also tokenized on various digital marketplaces and every single operation related to them could be registered and represented as a smart contract in Blockchain. Moreover, such approach could enable collection of the whole taxonomies and ontologies of various collections of digital art.

1. https://www.investopedia.com/terms/k/knowledge-economy.asp 6.11.2021.
2. Jane Greenberg “Metadata Capital: Raising Awareness, Exploring a New Concept”, Bulletin Bulletin of the Association for Information Science and Technology – April/May 2014 – Volume 40, Number 4. page 31 https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/bult.2014.1720400412  accessed on 6.11.2021..
3. Jane Greenberg “Big Metadata, Smart Metadata, and Metadata Capital: Toward Greater Synergy Between Data Science and Metadata” Journal of Data and Information Science. Vol. 2 No. 3, 2017. https://sciendo.com/pdf/10.1515/jdis-2017-0012, accessed on 6.11.2021.
4. Jesus Barrasa, Amy E. Holder & Jim Webber, “Knowledge Graphs. Data in Context for Responsive Businesses”, O’Reilly Media 2001, page 77.
5. “Data Lake or Data Swamp. Pandemic-accelerated Issue.” Webinar organized by Enterprise Management Council (EDMC) and MakoLab 27.01.2021 recording available at: https://datalakeorswamp.makolab.com/  acessed on: 6.11.2021.

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