Some ideas I've been pondering around models for knowledge hierarchies. I would love to hear your feedback, as this is ongoing, informal theoretical research.
The document provides an overview of warehousing under customs in India. Some key points:
- Goods can be deposited in public, private, or special warehouses licensed by customs authorities.
- Goods remain warehoused for up to one year, though extensions are possible. Interest applies if goods remain over 90 days.
- Owners can inspect, sort, manufacture, or deal with warehoused goods with permissions.
- Goods can be cleared for home consumption or export upon payment of duties and permissions.
- Provisions for transfer between warehouses, allowance for volatile goods, and consequences for improper removal are explained.
The Right to Information Act 2005 aims to promote transparency and accountability by giving all Indian citizens the right to information. Key aspects include the right to inspect records, take notes and obtain copies of documents. Public authorities must publish information about their functions and processes, and designate Public Information Officers to provide information to requesters within defined timeframes. Exemptions exist for information that could harm national security or investigations. Citizens can appeal to Information Commissions if their requests are denied.
The document discusses India's Right to Information Act of 2005. It notes that the Act aims to promote transparency and accountability in government by giving citizens the right to access government information. It outlines what types of information can be accessed, including documents, records, samples, and electronic information. It also discusses exemptions to disclosure, such as information related to national security or that received in confidence. The Act established the Central Information Commission to hear complaints about non-compliance with information requests.
Managing Institutions for Juveniles in Conflict with Law and Recommendations
HAQ: Center for Child Rights
B1/2, Ground Floor,
Malviya Nagar
New Delhi - 110017
Tel: +91-26677412,26673599
Fax: +91-26674688
Website: www.haqcrc.org
FaceBook Page: https://www.facebook.com/HaqCentreForChildRights
The Right to Information Act 2005 establishes a regime of transparency in India that overrides the Official Secrets Act. It gives Indian citizens the right to access information held by public authorities. The Act defines 'information' broadly and places obligations on public authorities to proactively disclose information. It also establishes procedures for citizens to request information, appeal rejections of requests, and penalties for non-compliance. The Act aims to promote transparency and contain corruption in governance.
The DIKW model describes the hierarchy of data, information, knowledge, and wisdom. Data are discrete facts, information provides context to data, knowledge comes from experiences and insights, and wisdom involves using knowledge to make well-informed decisions. For example, the time an incident is logged is data, the average time to close priority incidents is information, recognizing factors that impact closure times is knowledge, and determining solutions based on that knowledge is wisdom.
This document provides an overview of knowledge management. It defines data, information, and knowledge and describes explicit and tacit knowledge. It discusses the history of knowledge management from the 1970s to present. It also outlines several common knowledge management models and describes the typical stages in the knowledge management life cycle including information mapping, storage, retrieval, use, and auditing. Finally, it discusses some key terms used in knowledge management.
This document discusses the progression from data to wisdom. [1] Data is transformed into information through organization and patterns, information is transformed into knowledge through analysis and application, knowledge is transformed into intelligence through decision-making and skill, and intelligence is transformed into wisdom through accountability, foresight, and synthesis. [2] Knowledge provides the power to apply attributes critically or practically to make good decisions and balance execution with uncertainty. [3] Knowledge is important for both organizational adaptation and individual problem-solving.
The Future of Technology and InformationNick Finck
Evidence-driven design focuses on making sense of information by understanding relationships and patterns in data. As the cost of collecting and sharing data declines, transparency is increasing. However, simply having more accessible information does not equal wisdom; we must work to develop understanding from the data. Future technology will be less about finding information and more about making sense of what we find. Design will play a key role in helping people connect information to gain knowledge and wisdom. We should embrace failure as part of the learning process toward creating technologies and experiences that enhance comprehension.
2002 aera making decision support systems useful in the classroomChristopher Thorn
The document discusses improving school improvement processes through better use of decision support systems. It presents two models - an information seeking model and a decision making model - that can help administrators craft improvement processes. Sensemaking is identified as important as decision making. Needs assessment and data collection skills are areas that need strengthening. Rubric-based surveys could help educate schools and provide feedback on data acquisition, management, analysis and application capacities. The document provides examples of rubrics and recommendations for improving data access and use at both district and school levels.
1) Colleges and universities have opportunities to apply knowledge management practices used in corporations to support their missions.
2) Knowledge management involves capturing both explicit knowledge found in documents and tacit knowledge held by individuals, and making it widely accessible.
3) Higher education institutions could benefit from knowledge management by improving decision making, reducing development cycles, and improving services through increased sharing of best practices and lessons learned.
Knowledge Management in the Department of Defensejoannhague
The document discusses knowledge management (KM) in the Department of Defense (DoD). It provides definitions of knowledge and KM, and outlines the importance of KM for the DoD. The presentation covers the various KM tools and platforms used across the different branches of the military, including the Air Force Knowledge Now portal. It emphasizes that the future of KM is now, with new technologies like blogs, wikis and cloud computing playing a key role. The presentation encourages continuing the journey of KM.
This document outlines different metastructures in nursing informatics including data, information, knowledge, and wisdom. It defines data as measurable facts without interpretation. Information is defined as data that has been interpreted and organized to acquire knowledge. Knowledge is information that has been learned through education and experience, providing understanding. Wisdom involves applying knowledge with insight and judgment to solve problems.
Knowledge management the ability of an organization to create, share and use the collective
knowledge of its products, processes and people to increase workplace productivity and reduce
activities that reinvent the wheel is being moved to the forefront of many corporate agendas.
As firms seek to build competitive advantage in increasingly competitive markets, they are
turning to a previously untapped resource: their employees’ knowledge.
This document discusses a knowledge dissemination model for sustainable agriculture production. The model focuses on participatory systems thinking involving common pool resources and users. It emphasizes collaboration, trust, communication and knowledge sharing through online channels and social networks to empower users and facilitate adaption, efficacy and positivity towards sustainable agriculture goals.
Knowledge management (KM) deals with sharing lessons learned through databases, information management (IM) focuses on library services, and data management handles automation. KM involves validated data given meaning through experience, while information involves context and understanding. Intelligence applies knowledge through learning. Organizations approach these differently based on internal business units and external industry factors. Data quality, business intelligence, information security, and intellectual property are additional concerns for organizations.
This document discusses knowledge management and the evolution of approaches over time. It identifies three eras: 1) content management focused on capturing knowledge, 2) knowledge distribution focused on search and assisting work, and 3) knowledge consumption focused on transforming processes by leveraging networks. Most current approaches don't support collaborative work, instead information is siloed. The document proposes an optimal solution would unify information access, connecting people to people and people to information through a navigation and collaboration portal.
This document provides an overview of information and knowledge management. It discusses the differences between information technology, information systems, and information. It also describes the types of knowledge, knowledge management processes, and knowledge management activities. The key topics covered are the capture, storage, organization, and distribution of information and knowledge within an organization.
This document provides an overview of information and knowledge management. It discusses the differences between information technology, information systems, and information. It also describes the types of knowledge, knowledge management processes, and knowledge management activities. The key topics covered are the capture, storage, organization, and distribution of information and knowledge within an organization.
The document provides an overview of management information systems and information technology in business. It discusses the history of IT and how it has evolved from manual transactions to modern business software, computer communications, data warehousing, and business intelligence tools. It also describes how physical and virtual (information) resources are used by businesses to address problems and pressures. Information systems are presented as virtual systems that represent and control physical systems in organizations.
Big data refers to the large volumes of structured, unstructured and semi-structured data that organizations now have that is beyond their ability to process using traditional databases and software. This document discusses how organizations can leverage big data through improved information management strategies to gain valuable business insights. It provides examples of how different industries and sectors could increase their value by hundreds of billions annually by better utilizing the vast amounts of information they now have access to through big data analytics.
This is the slideshow i am using now (2013) to open design courses. This part goes over a bit of my background, a bit of history and inspiration for permaculture and its development, and the state of the world. It also begins to explore how permaculture is manifested in the world, which is a reflection of the 14 chapters of the Designers manual which acts as a framework for how the course is structured.
This document provides an introduction to advanced data analytics. It discusses [1] how organizations lose millions annually due to inefficient use of data, [2] the sources and types of big data being generated, and [3] the multi-disciplinary nature of data analytics, drawing on fields like database technology, statistics, machine learning, and visualization. The key steps of analytics projects are outlined, including understanding the domain, preprocessing data, reducing and transforming it, selecting analytical approaches, communicating results, and deploying and evaluating new systems.
Semantics empowered Physical-Cyber-Social Systems for EarthCubeAmit Sheth
Presentation at the EarthCube Face Face-to-Face Workshop of Semantics & Ontologies Workgroup: April 30-May 1, 2012, Ballston, VA.
Workshop site: http://earthcube.ning.com/group/semantics-and-ontologies/page/workshops
For more recent material on this topic, see: http://wiki.knoesis.org/index.php/PCS
This document summarizes a study on innovation intermediaries in smallholder agriculture in Kenya. The study identified a range of organizations serving as intermediaries, including NGOs, consultants, government agencies, private companies, a consortium, and a producer association. The intermediaries perform various functions like gathering information, facilitating collaboration and partnerships, capacity building, and disseminating knowledge. The study developed a typology of intermediaries and explored their changing roles in supporting innovation in the evolving Kenyan agricultural system.
1) Knowledge management is the systematic process of finding, organizing, and sharing information to improve employees' understanding in a specific area.
2) It turns knowledge into an organizational asset that can be used by more individuals to help with problem solving, learning, planning, and decision making.
3) Effective knowledge management helps deliver better services, build capacity through activities like training and skill development, and strengthen communication and community networks.
This document discusses the need to govern taxonomies and ontologies to ensure they remain up to date and effective as technologies, domains of knowledge, and user needs evolve. It describes what should be governed (concept labels, definitions, relationships, file formats), who should be responsible (taxonomists, SMEs, business stakeholders), and the workflow that should be followed (gathering inputs, scanning the environment, designing, developing, testing, and improving the taxonomy). Regular governance meetings are recommended to continually assess needs and make refinements. Having the right tools, expertise, and process in place from the start helps to properly develop and maintain taxonomies over time.
This document discusses the progression from data to wisdom. [1] Data is transformed into information through organization and patterns, information is transformed into knowledge through analysis and application, knowledge is transformed into intelligence through decision-making and skill, and intelligence is transformed into wisdom through accountability, foresight, and synthesis. [2] Knowledge provides the power to apply attributes critically or practically to make good decisions and balance execution with uncertainty. [3] Knowledge is important for both organizational adaptation and individual problem-solving.
The Future of Technology and InformationNick Finck
Evidence-driven design focuses on making sense of information by understanding relationships and patterns in data. As the cost of collecting and sharing data declines, transparency is increasing. However, simply having more accessible information does not equal wisdom; we must work to develop understanding from the data. Future technology will be less about finding information and more about making sense of what we find. Design will play a key role in helping people connect information to gain knowledge and wisdom. We should embrace failure as part of the learning process toward creating technologies and experiences that enhance comprehension.
2002 aera making decision support systems useful in the classroomChristopher Thorn
The document discusses improving school improvement processes through better use of decision support systems. It presents two models - an information seeking model and a decision making model - that can help administrators craft improvement processes. Sensemaking is identified as important as decision making. Needs assessment and data collection skills are areas that need strengthening. Rubric-based surveys could help educate schools and provide feedback on data acquisition, management, analysis and application capacities. The document provides examples of rubrics and recommendations for improving data access and use at both district and school levels.
1) Colleges and universities have opportunities to apply knowledge management practices used in corporations to support their missions.
2) Knowledge management involves capturing both explicit knowledge found in documents and tacit knowledge held by individuals, and making it widely accessible.
3) Higher education institutions could benefit from knowledge management by improving decision making, reducing development cycles, and improving services through increased sharing of best practices and lessons learned.
Knowledge Management in the Department of Defensejoannhague
The document discusses knowledge management (KM) in the Department of Defense (DoD). It provides definitions of knowledge and KM, and outlines the importance of KM for the DoD. The presentation covers the various KM tools and platforms used across the different branches of the military, including the Air Force Knowledge Now portal. It emphasizes that the future of KM is now, with new technologies like blogs, wikis and cloud computing playing a key role. The presentation encourages continuing the journey of KM.
This document outlines different metastructures in nursing informatics including data, information, knowledge, and wisdom. It defines data as measurable facts without interpretation. Information is defined as data that has been interpreted and organized to acquire knowledge. Knowledge is information that has been learned through education and experience, providing understanding. Wisdom involves applying knowledge with insight and judgment to solve problems.
Knowledge management the ability of an organization to create, share and use the collective
knowledge of its products, processes and people to increase workplace productivity and reduce
activities that reinvent the wheel is being moved to the forefront of many corporate agendas.
As firms seek to build competitive advantage in increasingly competitive markets, they are
turning to a previously untapped resource: their employees’ knowledge.
This document discusses a knowledge dissemination model for sustainable agriculture production. The model focuses on participatory systems thinking involving common pool resources and users. It emphasizes collaboration, trust, communication and knowledge sharing through online channels and social networks to empower users and facilitate adaption, efficacy and positivity towards sustainable agriculture goals.
Knowledge management (KM) deals with sharing lessons learned through databases, information management (IM) focuses on library services, and data management handles automation. KM involves validated data given meaning through experience, while information involves context and understanding. Intelligence applies knowledge through learning. Organizations approach these differently based on internal business units and external industry factors. Data quality, business intelligence, information security, and intellectual property are additional concerns for organizations.
This document discusses knowledge management and the evolution of approaches over time. It identifies three eras: 1) content management focused on capturing knowledge, 2) knowledge distribution focused on search and assisting work, and 3) knowledge consumption focused on transforming processes by leveraging networks. Most current approaches don't support collaborative work, instead information is siloed. The document proposes an optimal solution would unify information access, connecting people to people and people to information through a navigation and collaboration portal.
This document provides an overview of information and knowledge management. It discusses the differences between information technology, information systems, and information. It also describes the types of knowledge, knowledge management processes, and knowledge management activities. The key topics covered are the capture, storage, organization, and distribution of information and knowledge within an organization.
This document provides an overview of information and knowledge management. It discusses the differences between information technology, information systems, and information. It also describes the types of knowledge, knowledge management processes, and knowledge management activities. The key topics covered are the capture, storage, organization, and distribution of information and knowledge within an organization.
The document provides an overview of management information systems and information technology in business. It discusses the history of IT and how it has evolved from manual transactions to modern business software, computer communications, data warehousing, and business intelligence tools. It also describes how physical and virtual (information) resources are used by businesses to address problems and pressures. Information systems are presented as virtual systems that represent and control physical systems in organizations.
Big data refers to the large volumes of structured, unstructured and semi-structured data that organizations now have that is beyond their ability to process using traditional databases and software. This document discusses how organizations can leverage big data through improved information management strategies to gain valuable business insights. It provides examples of how different industries and sectors could increase their value by hundreds of billions annually by better utilizing the vast amounts of information they now have access to through big data analytics.
This is the slideshow i am using now (2013) to open design courses. This part goes over a bit of my background, a bit of history and inspiration for permaculture and its development, and the state of the world. It also begins to explore how permaculture is manifested in the world, which is a reflection of the 14 chapters of the Designers manual which acts as a framework for how the course is structured.
This document provides an introduction to advanced data analytics. It discusses [1] how organizations lose millions annually due to inefficient use of data, [2] the sources and types of big data being generated, and [3] the multi-disciplinary nature of data analytics, drawing on fields like database technology, statistics, machine learning, and visualization. The key steps of analytics projects are outlined, including understanding the domain, preprocessing data, reducing and transforming it, selecting analytical approaches, communicating results, and deploying and evaluating new systems.
Semantics empowered Physical-Cyber-Social Systems for EarthCubeAmit Sheth
Presentation at the EarthCube Face Face-to-Face Workshop of Semantics & Ontologies Workgroup: April 30-May 1, 2012, Ballston, VA.
Workshop site: http://earthcube.ning.com/group/semantics-and-ontologies/page/workshops
For more recent material on this topic, see: http://wiki.knoesis.org/index.php/PCS
This document summarizes a study on innovation intermediaries in smallholder agriculture in Kenya. The study identified a range of organizations serving as intermediaries, including NGOs, consultants, government agencies, private companies, a consortium, and a producer association. The intermediaries perform various functions like gathering information, facilitating collaboration and partnerships, capacity building, and disseminating knowledge. The study developed a typology of intermediaries and explored their changing roles in supporting innovation in the evolving Kenyan agricultural system.
1) Knowledge management is the systematic process of finding, organizing, and sharing information to improve employees' understanding in a specific area.
2) It turns knowledge into an organizational asset that can be used by more individuals to help with problem solving, learning, planning, and decision making.
3) Effective knowledge management helps deliver better services, build capacity through activities like training and skill development, and strengthen communication and community networks.
This document discusses the need to govern taxonomies and ontologies to ensure they remain up to date and effective as technologies, domains of knowledge, and user needs evolve. It describes what should be governed (concept labels, definitions, relationships, file formats), who should be responsible (taxonomists, SMEs, business stakeholders), and the workflow that should be followed (gathering inputs, scanning the environment, designing, developing, testing, and improving the taxonomy). Regular governance meetings are recommended to continually assess needs and make refinements. Having the right tools, expertise, and process in place from the start helps to properly develop and maintain taxonomies over time.
This document summarizes a presentation by Christine Connors on taxonomies and their role as a foundation for more complex semantic structures like thesauri and ontologies. It outlines a continuum of increasing complexity from folksonomies to taxonomies to thesauri to ontologies. It provides examples of existing taxonomies, thesauri and ontologies like OpenCyc and DBpedia. It discusses how information would be indexed using these structures and capabilities semantic technologies provide to clients in areas like reducing costs, increasing revenue and compliance.
A brief introduction to taxonomies through ontologies for indexing given to the American Society of Indexers at their annual conference in Providence, RI on April 30, 2011.
Accentuate the Positive: Modeling Enterprise OntologiesChristine Connors
The document provides guidance on developing enterprise ontologies, recommending starting simply with a small scope that solves key problems, keeping the team focused on building a multi-dimensional graph rather than a hierarchy, and engaging both classification and subject matter experts. It also suggests determining user needs and how the ontology will be accessed before defining complex relationships to ensure usability and integration across the enterprise.
Presentation given at the 2009 Semantic Technology Conference discussing the kinds of people that are desirable on teams building semantic applications.
This document discusses ontologies for cultural heritage management. It presents a continuum showing the increasing complexity from folksonomies to full ontologies. Folksonomies are personalized labels while ontologies have defined classes, properties, and allow for reasoning. Ontologies provide benefits like interoperability, consistency, dynamism, and improved discovery and analytics by establishing shared meaning. The document notes specifications and standards used in cultural heritage like CIDOC and Dublin Core and benefits of ontologies like authority, trust, provenance, and larger audiences. It provides examples of projects using ontologies like the MultimediaN Eculture Project and artifacts described like Maggie's ABC Book at the Powerhouse Museum.
The document discusses the semantic web and its key components. It describes what the semantic web is, how it differs from the current web by embracing existing technologies and adding technologies that allow computers to perform tasks on a user's behalf. It addresses common myths about the semantic web and provides overviews of semantic data modeling from folksonomies to complex ontologies. Examples of semantic data models and applications are also presented.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
Want to learn practical tips for designing systems that can scale efficiently without compromising speed?
Join us for a workshop where we’ll address these challenges head-on and explore how to architect low-latency systems using Rust. During this free interactive workshop oriented for developers, engineers, and architects, we’ll cover how Rust’s unique language features and the Tokio async runtime enable high-performance application development.
As you explore key principles of designing low-latency systems with Rust, you will learn how to:
- Create and compile a real-world app with Rust
- Connect the application to ScyllaDB (NoSQL data store)
- Negotiate tradeoffs related to data modeling and querying
- Manage and monitor the database for consistently low latencies
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...SOFTTECHHUB
I started my online journey with several hosting services before stumbling upon Ai EngineHost. At first, the idea of paying one fee and getting lifetime access seemed too good to pass up. The platform is built on reliable US-based servers, ensuring your projects run at high speeds and remain safe. Let me take you step by step through its benefits and features as I explain why this hosting solution is a perfect fit for digital entrepreneurs.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company
Explore the benefits and features of advanced logistics management software for businesses in Riyadh. This guide delves into the latest technologies, from real-time tracking and route optimization to warehouse management and inventory control, helping businesses streamline their logistics operations and reduce costs. Learn how implementing the right software solution can enhance efficiency, improve customer satisfaction, and provide a competitive edge in the growing logistics sector of Riyadh.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
TrsLabs - Fintech Product & Business ConsultingTrs Labs
Hybrid Growth Mandate Model with TrsLabs
Strategic Investments, Inorganic Growth, Business Model Pivoting are critical activities that business don't do/change everyday. In cases like this, it may benefit your business to choose a temporary external consultant.
An unbiased plan driven by clearcut deliverables, market dynamics and without the influence of your internal office equations empower business leaders to make right choices.
Getting things done within a budget within a timeframe is key to Growing Business - No matter whether you are a start-up or a big company
Talk to us & Unlock the competitive advantage
Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍
Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
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Noah Loul Shares 5 Steps to Implement AI Agents for Maximum Business Efficien...Noah Loul
Artificial intelligence is changing how businesses operate. Companies are using AI agents to automate tasks, reduce time spent on repetitive work, and focus more on high-value activities. Noah Loul, an AI strategist and entrepreneur, has helped dozens of companies streamline their operations using smart automation. He believes AI agents aren't just tools—they're workers that take on repeatable tasks so your human team can focus on what matters. If you want to reduce time waste and increase output, AI agents are the next move.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
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📄 Talk: Power Up Document Processing
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Cyber Awareness overview for 2025 month of securityriccardosl1
Ad
Knowledge Hierarchies
1. KNOWLEDGE HIERARCHY –
MATURITY MODEL
Functionally Absent – these needs
are not being met. Effort is needed
to address these gaps.
Maturity
Wisdom
Knowledge
An Indication of
Current State
Information
Data
Fully integrated processes, behaviors
and technological enablers. Energy is no
longer expended solving for these needs.
Time
2. KNOWLEDGE HIERARCHY –
SYSTEMS MODEL
Connectedness
Wisdom
Knowledge
Information Understanding
principles
Data
Understanding
patterns
Understanding
relations
See: http://www.systems-thinking.org/dikw/dikw.htm
Understanding
Editor's Notes
#2: The poet T.S. Eliot was the first to mention the "DIKW hierarchy" without even calling it by that name. In 1934 Eliot wrote in "The Rock"[5]:
Where is the Life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?
http://www-personal.si.umich.edu/~nsharma/dikw_origin.htm
Maslow’s Hierarchy of Needs – on its side
DIKW (See Wikipedia)
Data-Information-Knowledge-Wisdom
One variation
DIKS: Data-Information-Knowledge-Strategy
Data
Facts, measurements
is analyzed and/or connected to provide
Information
Facts, intelligence
when acted upon becomes
Knowledge
A range of contextual information and experiences
when reflected upon or analyzed becomes
Wisdom
Enables smart decisions
Explicit KM
DIKW are codified: recorded in text, audio, video, computer file or another capture method and systematically arranged
When knowledge and wisdom are codified they become information
Tacit KM
DIKW are implicit – assumed, understood; internal – experiential, personal
A person can combine new data with past training to internally generate knowledge
People-to-people interactions, such as sharing, learning, and mentoring