Knowledge Representation 

The frontiers of knowledge are always on the move across many dimensions and perhaps at varying speeds along each of these dimensions. Inter-disciplinary and cross-disciplinary knowledge is becoming more valuable. The question of how to organise and represent human knowledge is an old problem. But now it has assumed critical importance. Our ability to deal with the complex challenges of the future will depend upon our ability to manage knowledge organisation and representation. 

Knowledge representation refers to the technical problem of encoding human knowledge and reasoning  into a symbolic language that enables it to be processed by information systems. In systems biology, knowledge representation is used to infuse data with scientific concepts and understanding in order to maximize its utility for furthering scientific insight.

Here is the link to a good survey article on Knowledge Organisation: https://www.isko.org/cyclo/knowledge_organization

In this piece I draw attention to a few examples. In the future we may have automated Artificial Intelligence  tools for us to do so. 

• The periodic table
• Mind maps
• Knowledge graphs 
• Data representation 
• Valency of ideas/concepts
• Taxonomy/ Classification

The periodic table  (also known as the periodic table of elements) is organized so that scientists can quickly discern the properties of individual elements such as their mass, electron number, electron configuration and their unique chemical properties. Metals reside on the left side of the table, while non-metals reside on the right. Organizing the elements to help further our understanding was first provided by Dmitri Mendeleev.

The periodic table of the elements has their names, atomic number, symbol and mass is color-coded for easier reference by students and researchers.

The periodic table is the most important chemistry reference there is. It arranges all the known elements in an informative array. Elements are arranged left to right and top to bottom in order of increasing atomic number.  Order generally coincides with increasing atomic mass. 

The different rows of elements are called periods. The period number of an element signifies the highest energy level an electron in that element occupies (in the unexcited state). The number of electrons in a period increases as one traverses down the periodic table; therefore, as the energy level of the atom increases, the number of energy sub-levels per energy level increases.

Using the data in the table scientists, students, and others that are familiar with the periodic table can extract information concerning individual elements. For instance, a scientist can use carbon’s atomic mass  to determine how many carbon atoms there are in a 1 kilogram block of carbon.

People also gain information from the periodic table by looking at how it is put together. By examining an element’s position on the periodic table, one can infer the electron configuration. Elements that lie in the same column on the periodic table (called a “group”) have identical valence electron configurations and consequently behave in a similar fashion chemically. For instance, all the group 18 elements are inert gases. The periodic table contains an enormous amount of important information. People familiar with how the table is put together can quickly determine a significant amount of information about an element.

“The disappearing spoon” is a 2010 book about the periodic table written by science reporter Sam Kean. Sam Kean begins this book by explaining the basics of the periodic table and how it works. He explains the set-up of the table and why it is organized the way it is. He emphasizes the importance of its organization and justifies why it must be this way. He discusses how the periodic table would not function if it were not for the layout. He states that an element’s position describes its function and strength. He describes the table of elements as a castle and the elements as bricks to build this castle. He then discusses how the periodic table contains, and is organized into, metals, gases, noble gases, halogens, etc. Here is a link for further information on the periodic table: https://www.sigmaaldrich.com/technical-documents/articles/biology/periodic-table-of-elements-names.html

Mind maps: 

The Mind Map first conceptualised by Tony Buzan  is an easy way to brainstorm thoughts organically without worrying about order and structure. It allows you to visually structure your ideas to help with analysis and recall.

A Mind Map is a diagram for representing tasks, words, concepts, or items linked to and arranged around a central concept or subject using a non-linear graphical layout that allows the user to build an intuitive framework around a central concept. A Mind Map can turn a long list of monotonous information into a colorful, memorable and highly organized diagram that works in line with your brain’s natural way of doing things.

Mind Mapping is perfect for:

• Brainstorming and visualizing concepts
• Presenting and communicating ideas
• Graphic organizers and electronic note books
• Running meetings more effectively
• Outlining reports and documents
• Simplifying task and project management
• Writing essays

Software for creating mind-maps: https://thedigitalprojectmanager.com/mind-mapping-software/

Knowledge Graphs:

A Knowledge Graph is a model of a knowledge domain created by subject-matter experts with the help of intelligent machine learning algorithms. It provides a structure and common interface for all of your data and enables the creation of smart multilateral relations throughout your databases. Structured as an additional virtual data layer, the Knowledge Graph lies on top of your existing databases or data sets to link all your data together at scale – be it structured or unstructured.

Knowledge graphs are data. They have to be stored, managed, extended, quality-assured and can be queried.

Knowledge graphs: https://www.poolparty.biz/what-is-a-knowledge-graph/

Data representation: 

Even before we start on Knowledge representation, we have the challenge of data representation. Let’s take a simple problem. Assume that the average distance of the earth from the sun is 93 million miles. Also let’s assume that the speed of light is 186,000 miles per second. The question: how much time does light take to reach from the surface of the sun to the surface of the earth. You may remember it from your school days as about 8 minutes, or you could calculate it by dividing 93000000/186000 to get 500 seconds, which is 8 minutes 20 seconds. Now try to do the same calculation using Roman arithmetic in which the numbers 1 to 10 are written as: I,II,III,IV,V,VI,VII,VIII,IX and X. And then we have L, C, D and M……for 50,100,500 and 1000. Feel free to  search the Internet to find the rules for Roman arithmetic. You will find that not only is it very difficult to write these two numbers, it is impossible to do the division in any reasonable time. 

• Valency of ideas/concepts

We considered the organisation of the periodic table as a very important reference diagram in Chemistry. Another important concept in Chemistry is valency. The combining capacity of an atom is known as its valency. The number of bonds that an atom can form as part of a compound is expressed by the valency of the element. 

The concept has been extended to the field of linguistics. 

In linguistics, valency or valence is the number and type of arguments controlled by a predicate, content verbs being typical predicates. A major authority on the valency of the English verbs is Allerton (1982), who made the important distinction between semantic and syntactic valency. As we saw in the making of mind-maps, the number of connections of any Ned on the mind map may be considered as its valency. The value of an idea may become higher if it has a higher valency and connected with others. 

• Taxonomy/ classification :

Taxonomy is the Science and practice of classification of things or concepts, including the principles underlying such classification. While it was originally used for biological classification, the word taxonomy is now used as a synonym for classification. For example, in the field of education Bloom’s Taxonomy is a standardized categorization of learning objectives in an educational context. In the present times, there would be considerable interest in Virus classification, taxonomic system for viruses. In the field of Computing the following are quite important: Folksonomy, classification based on user’s tags and search engine taxonomy, considered as a tool to improve relevance of search within a vertical domain. 

Abraham Maslow first introduced his concept of a hierarchy of needs in his 1943 paper “A Theory of Human Motivation” and his subsequent book Motivation and Personality. This hierarchy suggests that people are motivated to fulfill basic needs before moving on to other, more advanced needs. There are five different levels of Maslow’s hierarchy of needs. Maslow’s hierarchy of needs is also a taxonomy. 

In analogy, the different levels of self-driving cars is also a taxonomy. 

Level 5 (Full Driving Automation)

Level 4 (High Driving Automation)

Level 3 (Conditional Driving Automation)

Level 2 (Partial Driving Automation)

Level 1 (Driver Assistance)

Level 0 (No Driving Automation)

To see the descriptions for each of these levels : https://www.synopsys.com/automotive/autonomous-driving-levels.html

We now have machine learning to do the classification for you. An enhanced version of the universally accepted Dewey decimal classification for all library books and resources, would be evolved for all types of digital content and automated systems for classification, storage and retrieval. This is very important as the amount of data/knowledge is growing exponentially, with user generated content being a large fraction. The goal of such systems is not only classification and storage but more importantly efficient retrieval when needed. 

While the technologies of the day are changing very rapidly, we have more and more knowledge and data which is long-lived and this must be borne in mind. Long-lived digital data collections are increasingly crucial to research and education in science and engineering. A number of well-known factors have contributed to this phenomenon. Powerful and increasingly affordable sensors, processors, and automated equipment (for example, digital remote sensing, gene sequencers, micro arrays, and automated physical behavior simulations) have produced a proliferation of data in digital form. Reductions in storage costs have made it cost-effective to create and maintain large databases. And the existence of the Internet and other computer-based communications have made it easier to share data. As a result, researchers in such fields as genomics, climate modeling, and demographic studies increasingly conduct research using data originally generated by others and frequently access this data in large public databases found on the Internet.