bigRing Knowledge Studio™

Explainable AI for knowledge experts, data scientists and end-users

bigRing Knowledge Studio™ is a Knowledge Mining Artificial Intelligence software module designed for capturing, modeling, analyzing, sharing, transferring and enhancing any kind of knowledge, wisdom and/or experience, i.e. the information at its most basic form. The innovative approach for knowledge modeling allows to create bigRing Knowledge Deep Graph, the cause-effect graph connecting data and associated metadata matched into Knowledge Elements, also capturing Causality relationships between data in the bigRing Causality Model™. The complex Knowledge Deep Graph can model, access and integrate the information assets of the entire corporation into bigRing Genomes™, the graph database that represents real-world entities, processes, events, physical objects as well as all the relationships between them yielding a more accurate and more comprehensive representation of an organization’s data and its overall “mirror of reality”. bigRing Genomes are computed and executed by bigBrain™, the graph computer (OLTP, OLAP, AI) and the meta-source code generator for data processing and artificial intelligence algorithms that allow computer, bot or robot to recognize data in cognitive form and context common to humans, obtain its real world meaning, and its causal relationship with other data.

bigRing Knowledge Studio™ is built on the novel approach to software architecture defined by the fractal, metaheuristic-model bigRing Causality Model™ that:

consists of the core components called “Knowledge Elements” that express in its definitive abstract form the categorized description of real-world element categories as humans perceive them
all that you need to understand for successful visual modeling capability is to understand the five basic Knowledge Elements, out of which four elements are specific in its substance and one element is unspecific

the model defines the Cause & Effect Relationships that express and describe the mutual relationship between the knowledge elements, determine the relationship and direction of causes and consequences. Together with elements and their metrics, they create logical data structures and knowledge maps into the Causality Graph as the higher abstract of reality (the first principle of knowledge representation)

The uniqueness of bigRing Causality Model™ is its explicit reality interpretation, that is common across all disciplines, thus allowing knowledge and information sharing even at the higher level of knowledge concept – the wisdom

Metrics and Measures describe the measurable properties of the knowledge elements in greater detail, for example physical, mathematical, financial and other measurable quantities expressed in values and units

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by mapping the data into the Knowledge Elements of bigRing Causality Model™, it is possible to define the basic information level, so called “first principle of knowledge reproduction”, capture causal relationships and causal-based processes between the elements, expressed in math and grammar logic, and record even the most complex knowledge and experience through multiple data layers (Phase Logic, Knowledge, Experience, Solution, Prediction and Simulation) into bigRing Genomes™, executed and computed by AI algorithms of bigBrain™

Unique features and critical functionalities of bigRing Knowledge Studio™

Knowledge Mining

Connect & Select to existing data sources and connectors (structured, semi-structured and/or unstructured), various technological infrastructures, or IoT, capture, reference, anonymize and process information, extract knowledge from it, create, enrich and maintain the “mirror of reality”
Match & Recognize data pieces into Knowledge Elements of BigRing Causality Model
Verify & Calibrate Causality, Taxonomy & Influence Factors, set-up Metrics, Limits & Targets
Setup & Execute Algorithm, Flow & Sequencing as well as Distribution of Computing
Publish & Monitor your application, Manage Controls, Track Changes, Share with experts, Monitor Notifications

Knowledge Modeling

visualize knowledge in the reality model that includes processes and all elements, capturing causal relationship between the knowledge elements, with the data (experience) flowing through the reality model, define meanings of each piece of data, thus capturing an understandable basis of the reality model
generate or design complex causality models and patterns, design research procedures, manage and automate the data collection, survey and measurement of missing information, simulate and verify processes, anticipate opportunities, risks and threats, design optimal solutions or plan changes
explain and understand causality, plan and predict its development, justify the causes and consequences of decisions

Knowledge Enhancement

enhance knowledge by optimizing processes, structures, outcomes and overall business flow, find and minimize bottle-necks and roadblocks to deliver unprecedented efficiency to your organization
connect various technological infrastructures, IoT and thus unify the comprehensively developing ecosystem of knowledge transfer, analysis, research and planning of a given image of reality

Knowledge Discovery

find the optimal path by detecting and recognizing the cause and effect relationships between knowledge elements
generate from simple information system to more complex workflow process management applications, through business intelligence tools, to advanced analysis components
unique causality model to effectively investigate causal relationships, investigate their origins and derive or justify their consequences and impacts, with decision support and approval process to automate knowledge reproduction

Knowledge Representation

represent knowledge in order to design formalisms that will make complex systems easier to design, build and automate knowledge reproduction or transfer
automate decision-making by incorporating various kinds of reasoning and logic decision structures
set-up visualizations and actions for knowledge-based management that generate automatic solutions for business optimization (private and public) in the necessary scope and detail

Unique zero-coding approach

allows visual modeling in the Knowledge Deep Graph (causality model) to instantly produce software solutions (bigRing Intelligent Information Systems™) tailor-made for end-users
user do not need to master any software programming languages to create applications
software apps are dynamically generated according to digital bigRing Genomes™, users work in dymanic forms front-end or populate pre-prepared templates and/or allow subjective solutions
questionnaires, surveys, process management systems, education applications, and many other options can be generated for individual users
allows manual or platform-controlled launching of solutions in view, editing or presentation (storytelling) modes in various forms of display and visual interpretation

Collaborative software platform

supports collaborative development and sharing of digital genomes and allows the internal communication within the expert network through chat functionality
editing implemented and managed based on the modeled processes and controls
work supported by the online collaboration, such as user connection to process, joint processing of multiple users, lock down of specific parts processed by another user
synchronization of central and user versions of reality models, orchestrated management of processes, notifications or messages and protection of intellectual property

Visualization and integrated components

solutions and applications can be displayed in different visualization and control components (widgets) in different locations (gadgets)
Visualization and control components (widgets): Table, Grid, Pivot Table, Tree Grid, Charts, Gantt, GeoMap, Graph, Diagram, Kanban, Calendar, Navigation Menu, Filter, Forms, Views, Reports and any other desired