The super fuss about Web 3.0, AI bots and Semantic Web Technologies

The most fascinating thing with AI and recent innovations is that, it was always there and the leaders are working towards integrating these concepts into publicly available tools. Artificial Intelligence is not new, to be frank as brown engineers with strict study paradigms, we absolutely enjoyed building, training and deploying our own bot with our little or limited verbiage, corpus data. It was a surreal experience to create the Tic-Tac-Toe game, play with a computer.

It's beautiful how all the computing concepts overlap with each other - Deep learning, Machine Learning, Natural Language Processing, Tensor Flow, Bag-of-words, Tf-Idf, Keyword Mapping etc. The huge difference in the recent ChatGPT or other AI tools for text, images, videos and designs is that the way the model was meaningfully trained incorporating security, privacy, risk management frameworks into the bot by carefully crafting the outputs to a human reader who can be naive, dangerous as well. The Game Changer is "DATA".

Here, I attach a small C-Map that shows up the interconnections between 9 important entities that shape Semantic web Technologies that are ought to be integrated with Cybersecurity and Cloud Computing concepts as well.

9 main entities that stood out as the heart of the modules Security Management and Risk Management. They are -

• Semantic Web Technologies
• Privacy
• Security
• Policies

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These cover technological problems and we also deal with the human aspect of problems arising from primary behavioral theories

How do Semantic Web Technologies simplify the distribution, sharing, and exploitation of Knowledge and information??

Privacy

Semantic Web technologies, such as Linked Data, RDF, and OWL, can be used to represent data in a way that allows for fine-grained access control. This means that access to sensitive information can be restricted to only those who have the proper authorization, improving privacy protection.?

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Security

The use of digital signatures and encryption in the Semantic Web makes it possible to secure data exchanges, ensuring that sensitive information is protected as it is transmitted and stored. In addition, the use of ontologies and formal logic can help prevent unauthorized access to sensitive information, as well as identify potential security vulnerabilities.?

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Policy

Semantic Web technologies can be used to represent policy statements in a machine-readable format. This makes it possible for automated systems to enforce policies, such as data protection regulations, consistently and transparently. This can help organizations comply with relevant privacy and security regulations, and reduce the risk of policy violations.?

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Semantic Web technologies simplify the exploitation of knowledge and information by improving interoperability, enabling Linked Data, making information machine-readable, and promoting reusability.?

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Interoperability

Semantic Web technologies, such as RDF and OWL, provide a common format for representing information, allowing data from multiple sources to be combined and linked together. This makes it possible for information from different systems to be integrated and analyzed, even if those systems were originally created using different technologies and standards.?

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Linked Data

The Semantic Web uses Linked Data to create a web of interconnected information, where data can be linked across multiple sources. This makes it possible to explore and discover new relationships between data and information, improving the overall quality and usefulness of the data.?

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Machine Readability

Semantic Web technologies represent information in a machine-readable format, making it possible for automated systems to process, analyze, and make use of the information. This opens up new possibilities for applications such as natural language processing, recommendation systems, and data analytics.?

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Reusability

The use of ontologies and formal logic in the Semantic Web makes it possible to define and reuse concepts and relationships, making it easier to manage and maintain large volumes of information. This reduces the effort required to maintain data consistency and improves the accuracy of data analysis.?

Since IT is good that people use, it results from the interaction of human and technological factors. The concept of "Risk Homeostasis" has not received as much attention as other fundamental behavioral theories like Reasoned Action, Planned Behavior, General Deterrence Theory, and Protection Motivation Theory. It clarifies and aids inconsistent human behavior. Research on behavioral information security is urgently needed, as are more comprehensive security and risk management strategies.??

Risk homeostasis is a concept in the field of risk management that describes the tendency for individuals and organizations to unconsciously adjust their behavior in response to changes in perceived risk. It suggests that, when perceived risk is reduced, people tend to take on more risk in their behavior, which can offset any safety benefits that may have been gained.?

For example, if a person feels safer driving because they have a new car with advanced safety features, they may be more likely to engage in risky driving behavior, such as driving faster or tailgating. Similarly, if an organization implements new safety measures to reduce risk, employees may feel less concerned about the safety and become more complacent, leading to an increase in accidents or incidents.??

Core Components for Semantic Web Technologies

1. RDF - Resource Description framework, a data model representing information in a tree like graph in a defined order of Subject - Predicate - Object, here is a code snippet ChatGPT gave me for an example

<rdf:Description rdf:about="https://example.com/person/1">
  <name>Hiranmayee Panchangam</name>
  <occupation>IT Supervisor</occupation>
</rdf:Description>
        

2. OWL - Web Ontology Language that is a tad bit more expressive and is best at defining the relationships between Subject and Object.

 If Professor is a subclass of Person, OWL can define that relationship.        

3. SPARQL - Query language used for manipulation

SELECT ?name WHERE { ?person <https://xmlns.com/foaf/0.1/name> ?name }        

4. Backlinks - Method to link data and allow connecting from different resources.

Now where is the live implementation of a few or all of the concepts spoken above - SEO - Search Engine Optimization is the answer you all. Now, traditional engineering courses won't include this course or subject at all, as it comes under the defined work profession of a Digital Marketer, while I think this is where Marketing is merged with computing intelligence that uses a lot of Data Analysis methodologies prominently NLP in Deep Learning.

Before the advent of AI text tools like Quill Bot, Chat GPT, Magic Media etc., Semantic Web Technologies frameworks were heavily utilized by applications like SEMrush, Screaming Frog, HubSpot etc. Virtual assistants like Cortana, Alexa, Siri work on these frameworks as well

References:??

Kirrane, S., Villata, S., & d'Aquin, M. (2018). Privacy, security, and policies: A review of problems and solutions with Semantic Web Technologies. Semantic Web, 9(2), 153–161. https://doi.org/10.3233/sw-180289?

Kearney, W. D., & Kruger, H. A. (2016). Theorising on risk homeostasis in the context of information security behaviour. Information and Computer Security, 24(5), 496-513. https://doi.org/10.1108/ICS-04-2016-0029?