Heather Hedden presented on tools for taxonomies. She defined taxonomies as controlled lists of terms arranged hierarchically to facilitate navigation and matching of concepts. Taxonomy tools include thesaurus management software for maintaining term relationships, auto-categorization software for applying taxonomies to documents, and tools that combine both. While no list is definitive, she reviewed features of various thesaurus management and auto-categorization software products. Some tools specialize in taxonomy editing while others focus on auto-categorization, but connectors allow combining capabilities.
• The method of classifying organisms into monophyletic group of a common ancestor based on shared apomorphic characters is called cladistics.
• Cladistics is now the most commonly used and accepted method for creating phylogenetic system of classifications.
Cladistics produces a hypothesis about the relationship of organisms to predict the morphological characteristics of organism.
From its initiation in 1998, the Angiosperm Phylogeny Group (APG) has focused on the production of an ever-more stable system of classification of the flowering plants (angiosperms). Based largely on analyses of DNA sequence data, the system is compiled by a larger group of experts than any previous system and has the advantage of being testable, allowing for confidence levels in the system to be estimated for the first time.
One major challenge is the time consumed by the interplay between the taxonomist and the publisher in preparing taxonomic data and going to print. Breaking this bottleneck requires seamless integration between compilation of the descriptive taxonomic data and the publication upon which the data are based
• The method of classifying organisms into monophyletic group of a common ancestor based on shared apomorphic characters is called cladistics.
• Cladistics is now the most commonly used and accepted method for creating phylogenetic system of classifications.
Cladistics produces a hypothesis about the relationship of organisms to predict the morphological characteristics of organism.
From its initiation in 1998, the Angiosperm Phylogeny Group (APG) has focused on the production of an ever-more stable system of classification of the flowering plants (angiosperms). Based largely on analyses of DNA sequence data, the system is compiled by a larger group of experts than any previous system and has the advantage of being testable, allowing for confidence levels in the system to be estimated for the first time.
One major challenge is the time consumed by the interplay between the taxonomist and the publisher in preparing taxonomic data and going to print. Breaking this bottleneck requires seamless integration between compilation of the descriptive taxonomic data and the publication upon which the data are based
Classification denotes the arrangement of a single plant or group of plants an distinct category following a system of nomenclature, and in accordance with a particular and well established plan.
Angiosperm Phylogeny Group classification
APG I
APG II
APG III
APG IV
Molecular Based system
features and organization
Merits and demerits
Difference in APG system.
Angiosperms are the flowering plants also known as Magnoliophyta. The botanical term "Angiosperm" meaning ‘bottle or vessel’ is derived from the ancient Greek. These are the most diverse group of land plants. Angiosperms are seed-producing plants and the distinguished features of angiosperms over gymnosperms are angiosperms bear flowers, endosperm within the seeds and the production of fruits that contain the seed. According to the botanists the flowering plants diversified and widespread 120 million years ago. The classification of the flowering plants also has a long history.
In the past, classification systems were typically produced by an individual botanist or by a small group resulting large number of systems. Different systems and their updates were generally favored in different countries. Bentham and Hooker’s system was popular in the Britain and the Engler’s system was famous in the Europe etc. These systems were introduced before the availability of genetic evidences and angiosperms were classified using their morphology and biochemistry. After the 1980’s genetic evidences were available and phylogenetic methods came into the classification procedures.
In the late 1990s, an informal group of researchers from major institutions worldwide came together and they established the Angiosperm Phylogeny Group (APG). The objective was to provide a widely accepted and more stable point of reference for angiosperm classification. APG I was published in 1998 as their first attempt in Annals of the Missouri Botanical Garden. The initial 1998 paper by the APG made angiosperms the first large group of organisms to be systematically re-classified primarily on the basis of genetic characteristics. The group emphasized the need for a classification system for angiosperms at the level of families, orders and above. The existed systems are rejected is because they are not phylogenetically classified. The outline of a phylogenetic tree of all flowering plants became established and several well supported major clades involving many families of flowering plants were identified. The new knowledge of phylogeny revealed relationships in conflict with the then widely used modern classifications.
The principles of APG system are retaining the Linnean system of orders and families, Use of monophyletic groups (Consist of all descendants of a common ancestor), taking a broad approach to defining the limits of groups such as orders and families and use of term ‘clades’ above or parallel to the level of orders and families. A major outcome of the classification is the disappearance of the traditional division of the flowering plants into two groups, which are monocots and dicots.
Even though there are several controversies about APG the botanists worldwide are influenced by the concept and are currently practice the system.
The naming of taxonomic groups of plants is determined by nomenclatural types.This PPT explores the basic principles of ICBN with species emphasis on the nomenclatural types used in plant taxonomy intended for UG & PG students of Botany.
SharePoint Connections Coast to Coast Overview of Enterprise Content ManagementIvan Sanders
This session walks you through some of the enterprise content management features in SharePoint 2010 such as metadata management, document sets, records management, search, and more. The demos will include declarative and programmatic creation of document sets and document ids, records management routing, and search
Classification denotes the arrangement of a single plant or group of plants an distinct category following a system of nomenclature, and in accordance with a particular and well established plan.
Angiosperm Phylogeny Group classification
APG I
APG II
APG III
APG IV
Molecular Based system
features and organization
Merits and demerits
Difference in APG system.
Angiosperms are the flowering plants also known as Magnoliophyta. The botanical term "Angiosperm" meaning ‘bottle or vessel’ is derived from the ancient Greek. These are the most diverse group of land plants. Angiosperms are seed-producing plants and the distinguished features of angiosperms over gymnosperms are angiosperms bear flowers, endosperm within the seeds and the production of fruits that contain the seed. According to the botanists the flowering plants diversified and widespread 120 million years ago. The classification of the flowering plants also has a long history.
In the past, classification systems were typically produced by an individual botanist or by a small group resulting large number of systems. Different systems and their updates were generally favored in different countries. Bentham and Hooker’s system was popular in the Britain and the Engler’s system was famous in the Europe etc. These systems were introduced before the availability of genetic evidences and angiosperms were classified using their morphology and biochemistry. After the 1980’s genetic evidences were available and phylogenetic methods came into the classification procedures.
In the late 1990s, an informal group of researchers from major institutions worldwide came together and they established the Angiosperm Phylogeny Group (APG). The objective was to provide a widely accepted and more stable point of reference for angiosperm classification. APG I was published in 1998 as their first attempt in Annals of the Missouri Botanical Garden. The initial 1998 paper by the APG made angiosperms the first large group of organisms to be systematically re-classified primarily on the basis of genetic characteristics. The group emphasized the need for a classification system for angiosperms at the level of families, orders and above. The existed systems are rejected is because they are not phylogenetically classified. The outline of a phylogenetic tree of all flowering plants became established and several well supported major clades involving many families of flowering plants were identified. The new knowledge of phylogeny revealed relationships in conflict with the then widely used modern classifications.
The principles of APG system are retaining the Linnean system of orders and families, Use of monophyletic groups (Consist of all descendants of a common ancestor), taking a broad approach to defining the limits of groups such as orders and families and use of term ‘clades’ above or parallel to the level of orders and families. A major outcome of the classification is the disappearance of the traditional division of the flowering plants into two groups, which are monocots and dicots.
Even though there are several controversies about APG the botanists worldwide are influenced by the concept and are currently practice the system.
The naming of taxonomic groups of plants is determined by nomenclatural types.This PPT explores the basic principles of ICBN with species emphasis on the nomenclatural types used in plant taxonomy intended for UG & PG students of Botany.
SharePoint Connections Coast to Coast Overview of Enterprise Content ManagementIvan Sanders
This session walks you through some of the enterprise content management features in SharePoint 2010 such as metadata management, document sets, records management, search, and more. The demos will include declarative and programmatic creation of document sets and document ids, records management routing, and search
The presentation I gave at the 2007 Semantic Technology Conference. Declarative programming” has become the latest buzzword to describe languages that abstractly define systems requirements (the what) and leave the implementation (the how) to be determined by an independent process. This makes the semantics (meaning) of declarative data elements even more critical as these systems are shared between organizations. This presentation: (1) Provides a background of declarative programming (2) Describes why understanding the semantic aspects of declarative systems is critical to cost-effective software development.
Presentation to the Information & Knowledge Management Society in Singapore, March 2008, on approaches to integrating controlled and uncontrolled vocabularies.
Semantic Web in Action: Ontology-driven information search, integration and a...Amit Sheth
Amit Sheth's Keynote talk given at: “Semantic Web in Action: Ontology-driven information search, integration and analysis,” Net Object Days 2003 and MATES03, Erfurt, Germany, September 23, 2003. http://knoesis.org
Note: slides 51-55 have audio.
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “The Role of Taxonomy and Ontology in Semantic Layers” at a webinar hosted by Progress Semaphore on April 16, 2024.
Taxonomies at their core enable effective tagging and retrieval of content, and combined with ontologies they extend to the management and understanding of related data. There are even greater benefits of taxonomies and ontologies to enhance your enterprise information architecture when applying them to a semantic layer. A survey by DBP-Institute found that enterprises using a semantic layer see their business outcomes improve by four times, while reducing their data and analytics costs. Extending taxonomies to a semantic layer can be a game-changing solution, allowing you to connect information silos, alleviate knowledge gaps, and derive new insights.
Hedden, who specializes in taxonomy design and implementation, presented how the value of taxonomies shouldn’t reside in silos but be integrated with ontologies into a semantic layer.
Learn about:
- The essence and purpose of taxonomies and ontologies in information and knowledge management;
- Advantages of semantic layers leveraging organizational taxonomies; and
- Components and approaches to creating a semantic layer, including the integration of taxonomies and ontologies
Looking Under the Hood -- Australia SharePoint ConferenceChristian Buckley
"Looking Under the Hood: How Your Metadata Strategy Impacts Everything You Do" was presented on 3/9/2011 at the Australia SharePoint Conference in Sydney.
Business Strategies for Content Management - Part 3: Publishing Web Content U...TJ O'Connor
How do you manage your print content? The latest print publishing tools allow you to quickly and easily populate a print document with database-driven content using XML.
* Do you need a centralized, fully managed repository of data; allowing greater control and end to end assignment management?
* Would you like to reduce document production lead times?
* Reduce costs in editing and proofing?
If you answered yes to any of the above questions, this is a must attend webinar for marketers, business leaders, content editors, and developers. Join TJ O'Connor, Principal Consultant, CrossTech Partners, along with Mark Boisvert Account Executive, CrossTech Partners, in part three of our four part series on Business Strategies for Content Management and learn strategies and technologies that will help you automate the publishing of content from a digital repository into your print publications.
Marjorie M.K. Hlava, President and founder of Access Innovations, Inc., unveils the newest version and module updates of the Data Harmony indexing software suite.
TSPUG: Content Management in SharePoint 2010Eli Robillard
This presentation was delivered at the Toronto SharePoint User Group's December 2009 meeting. Note that all slides containing graphics were aggregated from Microsoft decks presented during SPC 2009, corrections and text-only slides are original.
How your metadata strategy impacts everything you doChristian Buckley
"Looking Under the Hood - How Your Metadata Strategy Impacts Everything You Do" is a 101 topic for business users to help them understand the importance of metadata, taxonomy, and governance in SharePoint 2010.
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You DoChristian Buckley
A SharePoint 101 presentation that outlines metadata, taxonomy, and governance - what they are, why they are important, and how they affect everything you do inside SharePoint (specifically, SP2010)
Get a practical, hands-on review of the new managed metadata services for managing taxonomies, folksonomies, tags, metadata and content types in SharePoint 2010.
In an era where artificial intelligence (AI) stands at the forefront of business innovation, Information Architecture (IA) is at the core of functionality. See “There’s No AI Without IA” – (from 2016 but even more relevant today)
Understanding and leveraging how Information Architecture (IA) supports AI synergies between knowledge engineering and prompt engineering is critical for senior leaders looking to successfully deploy AI for internal and externally facing knowledge processes. This webinar be a high-level overview of the methodologies that can elevate AI-driven knowledge processes supporting both employees and customers.
Core Insights Include:
Strategic Knowledge Engineering: Delve into how structuring AI's knowledge base is required to prevent hallucinations, enable contextual retrieval of accurate information. This will include discussion of gold standard libraries of use cases support testing various LLMs and structures and configurations of knowledge base.
Precision in Prompt Engineering: Learn the art of crafting prompts that direct AI to deliver targeted, relevant responses, thereby optimizing customer experiences and business outcomes.
Unified Approach for Enhanced AI Performance: Explore the intersection of knowledge and prompt engineering to develop AI systems that are not only more responsive but also aligned with overarching business strategies.
Guiding Principles for Implementation: Equip yourself with best practices, ethical guidelines, and strategic considerations for embedding these technologies into your business ecosystem effectively.
This webinar is designed to empower business and technology leaders with the knowledge to harness the full potential of AI, ensuring their organizations not only keep pace with digital transformation but lead the charge. Join us to map a roadmap to fully leverage Information Architecture (IA) and AI chart a course towards a future where AI is a key pillar of strategic innovation and business success.
Many Organizations are struggling with the best way to govern and manage the use of Generative AI in the enterprise. There are many dimensions to this challenge ranging from ethical issues, data architecture and quality, legal and copywrite, operational and more.
This is why a governance framework needs to be carefully designed and put into place so the business can make the most use of this truly revolutionary technology, reduce and mitigate risks, control costs, maintain a positive employee and customer experience and most importantly, find competitive advantage in the marketplace.
Improving product data quality will inevitably increase your sales. However, there are other benefits (beyond improved revenue) from investing in product data to sustain your margins while lowering costs.
One poorly understood benefit of having complete, accurate, consistent product data is the reduction in costs of product returns. Managing logistics and resources needed to process returns, as well as the reduction in margins based on the costs of re-packaging or disposing of returned products, are getting more attention and analysis than in previous years.
This is a B2C and a B2B issue, and keeping more of your already-sold product in your customer’s hands will lower costs and increase margins at a fraction of the cost of building new market share.
This webinar will discuss how EIS can assist in all aspects of product data including increasing revenue and reducing the costs of returns. We will discuss how to frame the data problems and solutions tied to product returns, and ways to implement scalable and durable changes to improve margins and increase revenue.
In the rapidly evolving world of ChatGPT and Large Language Models (LLMs), businesses are understandably apprehensive. Numerous potential hazards and hurdles exist such as:
Unrealistic expectations of LLMs as a magic solution to managing corporate content without requisite human involvement
Difficulty distinguishing between creative outputs and fabricated responses (hallucinations)
Decisions around training models: balancing usefulness with the threat of exposing trade secrets or other proprietary knowledge
Absence of clear audit trails and citation sources
The risk of generating responses misaligned with company policies or brand image
Potential financial burden of proprietary LLMs and related enterprise software platforms
In this webinar, we will examine a structured approach to harvest, utilize, and protect corporate knowledge resources. We will explore how both commercial and open-source large language models can be leveraged to deliver precise conversational responses without jeopardizing intellectual property.
Learn how your organization can effectively use LLM based applications for competitive advantage. Using a general LLM will provide efficiency, but through standardization. Differentiation using your corporate terminology and knowledge will allow for competitive advantage. You don’t have to deploy ChatGPT to benefit from these approaches. They will improve the information metabolism of the enterprise and pave the way for advanced AI applications.
In this session we will be discussing the challenges the organization faced in content usability, traceability, and findability, hindering their internal training workflows and access to critical knowledge assets.
We will also discuss what’s next on the content and information horizon, including the role of machine learning and why these approaches are needed for AI-Powered applications, including LLMs and ChatGPT types of information access.
Generative AI is getting all the attention, headlines, and industry hype. Organizations are looking at how it can be used to create better employee and customer experiences by unlocking the potential stored in the vast troves of unstructured data that house knowledge assets.
We will begin by providing an overview of the fundamental concepts and advances in generative AI, followed by an in-depth examination of the importance of knowledge management in developing, implementing, and improving these systems.
We’ll discuss knowledge management approaches for the organization and retrieval of information, how retrieval fits in with content generation, and the challenges and opportunities it presents for the enterprise.
The Increasing Criticality of MDM for Personalization for Customers and Employees
Master data management seems to be one of those perennial, evergreen programs that organizations continue to struggle with.
Every couple of years people say, “we're going to get a handle on our master data” and then spend hundreds of thousands to millions and tens of millions of dollars working toward a solution.
The challenge is that many of these solutions are not really getting to the root cause of the problem. They start with technology and begin by looking at specific data elements rather than looking at the business concepts that are important to the organization.
MDM programs are also difficult to anchor on a specific business value proposition such as improving the top line. Many initiatives are so deep in the weeds and so far upstream that executives lose interest and they lose faith in the business value that the project promises. Meanwhile frustrated data analysts, data architects and technology organizations feel cut off at the knees because they can't get the funding, support and attention that they need to be successful.
We've seen this time after time and until senior executives recognize the value and envision where the organization can go with control over its data across domains, this will continue to happen over and over again. Executives all nod their heads and say “Yes! Data is important, really important!” But when they see the price tag they say, “Whoa hold on there, it's not that important”.
Well, actually, it is that important.
We can't forget that under all of the systems, processes and shiny new technologies such as artificial intelligence and machine learning lies data. And that data is more important than the algorithm. If you have bad data your AI is not going to be able to fix it. Yes there are data remediation applications and there are mechanisms to harmonize or normalize certain data elements. But looking at this holistically requires human judgment: understanding business processes, understanding data flows, understanding dependencies and understanding of the entire customer experience ecosystem and the role of upstream tools, technologies and processes that enable that customer experience.
Until we take that holistic approach and connect it to business value these things are not going to get the time, attention and resources that they need.
Seth Earley, Founder & CEO, Earley Information Science
Dan O'Connor, Senior Product Manager at inriver
A knowledge graph is a type of data representation that utilizes a network of interconnected nodes to represent real-world entities and the relationships between them. This makes it an ideal tool for data discovery, compliance, and governance tasks, as it allows users to easily navigate and understand complex data sets.
In this webinar, we will demystify knowledge graphs and explore their various applications in data discovery, compliance, and governance. We will begin by discussing the basics of knowledge graphs and how they differ from other data representation methods. Next, we will delve into specific use cases for knowledge graphs in data discovery, such as for exploring and understanding large and complex datasets or for identifying hidden patterns and relationships in data.
We will also discuss how knowledge graphs can be used in compliance and governance tasks, such as for tracking changes to data over time or for auditing data to ensure compliance with regulations. Throughout the webinar, we will provide practical examples and case studies to illustrate the benefits of using knowledge graphs in these contexts.
Finally, we will cover best practices for implementing and maintaining a knowledge graph, including tips for choosing the right technology and data sources, and strategies for ensuring the accuracy and reliability of the data within the graph.
Overall, this webinar will provide an executive level overview of knowledge graphs and their applications in data discovery, compliance, and governance, and will equip attendees with the tools and knowledge they need to successfully implement and utilize knowledge graphs in their own organizations.
*Thanks to ChatGPT for help writing this abstract.
Some product information management (PIM) tools make it difficult to change core data models once they have been set up in the system. To avoid costly rework, you can utilize a “pre-PIM” design tool as a PIM accelerator. This class of software allows you to:
**Iterate on designs before committing to a PIM architecture
Improve data quality
**Collaborate on decision-making and audit trails
**Set up metrics around product data and attribute structure
**Correlate performance measures with metrics – product data and hierarchy improvements are correlated with user behaviors and outcomes
**Integrate governance content prior to PIM load
**Decrease reliance on spreadsheets
While some PIM tools include a subset of these functions, they are often lacking in flexibility, functionality, and integration capabilities, especially around product data model and hierarchy design changes.
In this webinar our PIM experts introduce a pre-PIM software solution that enables fluid design changes while ensuring data integrity, reducing risk, increasing stakeholder engagement, and showing clear ROI on investments in product data.
If you want to deliver a truly personalized product experience and strengthen customer loyalty, a Product Information Management System (PIM) is a must. PIM systems ensure clean, complete, and consistent data to enhance both the customer and employee experience. With intuitive management of complex product information, PIM unites internal teams with better visibility and reporting.
In this session our experts in enterprise information architecture and PIM technology explain ways you can:
--Streamline the complexity of supply chain information
--Publish consistent product information across all channels
--Adapt quickly to market changes and bring products to market faster
--Increase the total performance and profitability your Ecommerce business
Speakers:
Chantal Schweizer, Director of Solution Delivery at Earley Information Science
Jon C. Marsella, Founder, Chairman, and CEO at Jasper Commerce Inc.
How Large Enterprises are Saving Millions in Operational Costs and Improving the Employee Experience.
In this session, Earley Information Science, with partner PeopleReign, will show how these programs can rapidly produce measurable results in weeks rather than months and years. While large-scale knowledge problems cannot be solved overnight, by focusing on narrow AI with clearly defined processes and curated knowledge, organizations can see ROI in as little as 30 days.
In today's world everyone, including your B2B customers, expect personalized buying experiences. Unless you have the right information architecture in place to power your digital experience tools you will not be able to scale and retain trust with your customers.
In this webinar, B2B ecommerce experts Allison Brown with Earley Information Science and Jason Hein with Bloomreach walk through the reasons why you must invest in information architecture foundations in order to compete.
Understand the key steps to set up your next data discovery initiative for success using the latest methodology and technologies with Earley Information Science. In this webinar we partner with Expert.AI, a recognized leader in document-oriented text analytics platforms to explain the technical and methodological advances that enable better data discovery.
Seth Earley, CEO & Founder of Earley Information Science and Peter Crocker, CEO & Co-founder of Oxford Semantic Technologies discuss powering personalized search with knowledge graphs to transform legacy faceted search into personalized product discovery.
In this webinar Seth Earley establishes the formula for AI success, demystifies the topic for executives and provides actionable advice for data strategists.
Key Takeaways:
**AI-Powered solutions begin with a focus on business goals
**Successful AI requires a semantic data layer built on a solid enterprise information architecture.
**Instrumenting measuring ROI should be part of every AI program
Enterprises are increasingly recognizing the critical need for knowledge management (KM) to power cognitive AI. In fact, KM and AI are two sides of the same coin. Training a chatbot requires the same organized information that we use to train a human. When you engineer knowledge correctly, you serve the needs of people today and prepare for greater automation in the future. In fact, the long term success of the organization will depend on doing just that – especially when the competition builds high functionality bots that will produce lower costs and better customer service. Those without the capability will not be competitive.
In this panel discussion, our experts discuss examples and approaches that show how KM supports AI and how to ensure the success of your KM initiative.
Knowledge management and AI
People and cultural considerations
Business justification for long term investment
In this session Seth Earley, author of the AI Powered Enterprise, discusses how to harness the power of artificial intelligence to drive extraordinary competitive advantage.
Seth Earley, Founder & CEO of Earley Information Science and author of the award winning book, "The AI Powered Enterprise" explains how advanced concepts in information architecture, such as ontologies and knowledge engineering, are the basis for streamlined content workflows.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
2. About Heather Hedden Taxonomy consultant, Earley & Associates Indexer, Hedden Information Management Instructor, Continuing Education, Simmons College Graduate School of Library & Information Science Formerly taxonomist at Viziant Corporation and Thomson Learning (Gale) Author, The Accidental Taxonomist (Information Today, Inc., May 2010)
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4. What are Taxonomy Tools? No authoritative industry list of taxonomy software “Taxonomy software” can mean different things Auto-categorization vs. taxonomy management Existing Web lists are miscellaneous taxonomy-related tools or out-of-date http://taxocop.wikispaces.com/TaxoTools www.taxotips.com/resources/tools www.searchtools.com/info/classifiers-tools.html www.willpowerinfo.co.uk/thessoft.htm
5. Taxonomy Tool Types Thesaurus/ontology management software Other software with thesaurus/taxonomy modules Auto-categorization/text mining software Other software supporting creating taxonomies mindmapping or concept modeling tools Cardsorting tools Web analytics
7. Thesaurus Management Software Basics Maintains terms and their relationships (equivalencies, hierarchical, and associative) As reciprocals When renaming, merging, subsuming, or deleting terms Disallows invalid relationships (according to standards) Supports term notes and other attributes for terms Supports candidate/approved terms; includes term creation and update dates Generates reports in various thesaurus display formats (hierarchical, alphabetical) Exports data in interoperable formats for importing into a content management, indexing, search, retrieval system Supports thesaurus standards: ANSI/NISO Z39.19 or ISO 2788
8. Thesaurus Management Software Feature Comparisons interface design and ease of use multiple taxonomy display options term searching spell-checking speed (limited mouse clicks) for repeated term and relationship additions single-step new term & relationship creation single-step branch (term and narrower terms) moving drag & drop relationship adding user-defined (customizable) relationships user-defined term notes and term attributes bilingual or multilingual taxonomy support importing and exporting formats connectors to enterprise search systems
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11. Thesaurus Management Software MultiTes Pro Multisystems (Miami, FL) www.multites.com Since 1983. Hector Echeverria, president. $295 single user; $1295 for 5 users$2495 for 10 users; $3950 enterprise deployment Add-on products: web development kit, enterprise development kit Imports text; exports text, HTML (as a web page), XML, CSV Free limited-time downloadable trial and online tutorial Online discussion group for tips
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13. Thesaurus Management Software Cognatrix LGOSystems Pty. Ltd. (Australia) www.cognatrix.com For Mac OS X 10.4.5 and later US $499, or $199 for an “Education” version limited to 500 terms. Imports from plain text with tab separations.With CognatrixImporter add-on, imports from various XML schemas: Cognatrix, MultiTes, Term Tree, and Zthes. Exports to XML and HTML. Free limited-time downloadable trial and manual
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15. Thesaurus Management Software One-2-One This to That Pty. Ltd. t/a A.C.S.Active Classification Solutions (Australia) www.acs121.com Price: $800 Australian (approximately $700-750) For thesauri and classification systems, but also has features and connectors for records management Replaces a previous thesaurus-only product, Term Tree Drag-and-drop hierarchy feature Free limited-use and limited-size trial
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17. Thesaurus Management Software TheW32 Tim Craven Freeware (Ontario, Canada) http://publish.uwo.ca/~craven/freeware.htm Started as thesaurus feature in his TEXNET auto-abstracting tool in early 1990s. Free Also provides web site indexing software XRefHT and machine-aided indexing and abstracting software
19. Thesaurus Management Software High-end, multi-user client-server, large scale systems ($3000/single user - $75,000+; or annual hosted options) Data Harmony Synaptica Smartlogic Wordmap SchemaLogic STAR/Thesaurus SoutronTHESAURUS Mondeca ITM T3 PoolParty TheMa a.k.a.
20. Thesaurus Management Software Data Harmony Thesaurus Master Access Innovations (Albuquerque, NM) www.dataharmony.com Indexing services since 1978, commercial software (originally used in-house) offered since 1998. Multi-platform java-based (used on Windows, Mac, Solaris, Linux). Client software allows remote access. All standard thesaurus displays types as view options User defined associative and equivalence, but no user-defined hierarchical relationships Sold separately or combined with M.A.I. (Machine Aided Indexer) as MAIstro. Other software extensions available.
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23. Thesaurus Management Software Synaptica Synaptica Software LLC (Franktown, CO) http://synapticasoftware.com Since 1995. Owned by Dow Jones 2005-2009. Web browser-based, priced per user, per year, per vocabulary 12 graduations of permission levels Can assign relationship weights Global term and relationships editor, creating a list of terms to edit Side-by-side editor with drag-and-drop Imports: CSV, text, MS Excel, XML (including schemas of ZThes, RDF, SKOS, and OWL) Exports: CSV, HTML, MS Word, MS Excel, XML (including schemas of ZThes, RDF, SKOS, and OWL)
24. There are also browse options including a Tree Browse and Alpha-numeric browse option to review terms.
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26. Thesaurus Management Software Semaphore Ontology Manager Smartlogic Semaphore Ltd. (London, UK) + US office www.smartlogic.com Supports creating thesauri according to ISO 2788 standard Supports creating ontologies, through customizable relationships and user-created classes User-defined term attributes and metadata Multiple user access/privilege levels Imports/export in CSV, XML, Zthes, SQL databases, and MultiTes files Related products: Classification Server for automated classification Ontology Service for a navigation system
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28. Thesaurus Management Software Wordmap Taxonomy Manager Wordmap Inc. (Concord, MA) www.wordmap.com In UK since 1998. Acquired by Earley & Associates in 2007. Multi-platform java-based One of a suite of products including Wordmap Intelligent Text Classifier, Taxonomy Connectors for SharePoint and Endeca. User-defined relationships; can also turn on or off relationship name display. Can display two taxonomies side by side and drag and drop. User access/privileges can be set at the individual node level. Imports: CSV, Excel, XML; Exports: XML Real-time access: Java API
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31. Thesaurus Management Software SchemaLogic Enterprise Suite SchemaLogic Inc. (Kirkland, WA) www.schemalogic.com Provides thesaurus management according to ANSI/NISO standards, plus broader structural metadata support Can create customizable relationships Can assign various permission levels to vocabularies or terms Classification module supports 3rd party auto-indexing Connectors to SharePoint, EMC Documentum, and FAST ESP Can import CSV or XML files
32. Thesaurus Management Software STAR/Thesaurus Cuadra Associates, Inc. (Los Angeles) www.cuadra.com Stand-alone or integrates with STAR family of products for records mngmt, collections mngmt, archives mngmt, DAM Supports standard thesaurus relationship but not customizable relationships Supports unlimited user-defined notes and categories Various output report display formats Import/export ASCII text and CSV, but not XML
33. Thesaurus Management Software SoutronTHESAURUS Soutron Ltd. (United Kingdom) www.soutron.com Markets in the U.S. through partnership with InMagic Stand-alone or integrates with SoutronGLOBAL or SoutronSOLO library management systems, or with InMagic Presto social knowledge management software Supports standard thesaurus and user-defined relationships Supports term merging Imports from XML; exports to XML or CSV
34. Thesaurus Management Software Mondeca ITM T3 (Intelligent Topic Manager: Thesaurus, Taxonomies, Terminologies) Mondeca S.A. (Paris, France) www.mondeca.com Since 2008, addition to Intelligent Topic Manager set of products for knowledge management, semantic portals, and e-catalogs web-based collaborative application conforms to both SKOS vocabularies and OWL-standard ontologies connectors to text mining, classification, and search tools Imports/exports XML, RDF, and SKOS
35. Thesaurus Management Software PoolParty punkt. netServices GmbH (Vienna, Austria) http://poolparty.punkt.at A new thesaurus tool built on W3C Semantic Web Standards: SKOS, RDF, OWL, SPARQL Installed server or web-hosted options Can link domain-specific thesauri to Linked Open Data Wordpress plugin to build glossaries for blogs Imports ZThes XML, CSV Integrated text extraction and semi-automatic tagging to enable semantic search
37. Other Software with Taxonomy/thesaurus Creation & Editing Components Metadata or cataloging software, especially for archives and libraries Adlib Information Systems, www.adlibsoft.com Content management and document management systems Open Text Collections Server Webtop Thesaurus Manager, www.opentext.com Records management systems a.k.a. from Synercon Management Consulting, www.a-k-a.com.au Auto-categorization and enterprise search software
38. Auto-categorization and Text Mining Auto-categorization Algorithms, statistics, and training documents – utilize a large set a sample documents per taxonomy term to “train” the system to learn to index Rules base – generate and edit or write “rules” for each term based on co-existing words, proximity, Boolean logic, etc. Text mining Extracts relevant terms from texts to generate a candidate taxonomy or supplement an existing taxonomy
39. Auto-categorization/Search Software Auto-categorization, text mining, and search systems that utilize taxonomies handle these taxonomies in different ways: With pre-installed taxonomies that cannot be edited With pre-installed taxonomies that the user may edit and extend through the user interface Automatically generate a taxonomy that can be edited Support the import of taxonomies but do not support the editing of those taxonomies Support the import of taxonomies and then the editing of those taxonomies Various combinations of above
40. Auto-categorization/Search Software Software that can import and use taxonomies but lacking user-interface features to edit those taxonomies includes: Microsoft SharePoint IBM Classification Module Fast Endeca Temis Vivisimo Mindbreeze Exalead PerfectSearch They collaborate with other vendors that develop taxonomies and/or have taxonomy editing capabilities.
41. Auto-categorization/Search Software Examples of tools with some taxonomy management capabilities: Inxight SmartDiscovery Analysis Server www.inxightfedsys.com Autonomy Collaborative Classifier www.autonomy.com Autonomy Interwoven MetaTagger www.interwoven.com Lexalytics Classifier www.lexalytics.com Conceptsearching www.conceptsearching.com
42. Auto-categorization/Search Software Examples of auto-categorization tools with full thesaurus management capabilities: Data Harmony MAIstro www.dataharmony.com/products/maistro.html Smartlogic Semaphore Classification Server www.smartlogic.com Wordmap Intelligent Text Classifier www.wordmap.com SAS Enterprise Content Categorization(formerly Teragram TK240) www.sas.com/text-analytics Nstein Text Mining Engine (part of Open Text) www.nstein.com
43. Auto-categorization Software combined with Thesaurus Management Data Harmony MAIstro (combines Data Harmony Thesaurus Master and Machine-Aided Indexer) Automatically creates a basic rule for every term and its variants in the Thesaurus Master’s thesaurus Rules may be edited and additional rules can be manually written statistics module tracks the editor’s term choices and compares them with M.A.I. term suggestions, sorting them as hits, misses, and noise to guide and prioritize the editor’s fine-tuning of rules Can be used for machine-aided indexing or fully automated indexing Connectors to Sharepoint and search engines
44. Auto-categorization Software combined with Thesaurus Management Smartlogic Semaphore Classification Server (connects with Semaphore Ontology Manager) Creates classification rulebases directly from a taxonomy/thesaurus/ontology, and applies these rules to content as it is received to automatically classify content. Rules are based on the term, its equivalencies, and broader/ narrower/related terms Employs 20 different kinds of rules Rules have weights and scores Variants based on spelling, plurals, and stemming may also be considered. Manual rules can take precedence over generated rules.
45. Auto-categorization Software combined with Thesaurus Management Wordmap Intelligent Text Classifier (connects with Wordmap Taxonomy Manager for leveraging thesaurus) Auto-classification based on statistical method based of Support Vector Machine algorithms and machine learning with training documents Pre-packaged with statistical algorithms based on a generic taxonomy, the U.K.’s Integrated Public Services Vocabulary (IPSV), for which each of hundreds of terms have already been “trained” with representative documents Wordmap also offers Taxonomy Connectors for taxonomy-driven tagging and search within SharePoint and Endeca
46. Auto-categorization Software combined with Thesaurus Management SAS Enterprise Content Categorization (ECC) (Formerly Teragram TK240 Taxonomy Manager) Supports taxonomy building or connects with SAS Ontology Manager ECC supports equivalent, hierarchical & related relationships Ontology Manager supports customized relationships and attributes Utilizes both auto-categorization and entity/concept extraction Auto-categorization bases on rules Rules-writing supported with a graphical tree view of Boolean operators and commands User can define weighting of terms
47. Auto-categorization Software combined with Thesaurus Management Open Text Nstein Text Mining Engine (TME) Modules include concept extractor, entity extractor, auto-categorizer, automated abstract creation, sentiment analysis Taxonomy Manager module (not sold separately) supports creating & editing hierarchical, associative and equivalence relationships according to ANSI/NISO standard Auto-categorization technology based on use of training sets for taxonomy terms, combined with concept extraction technology Ships with pre-installed taxonomies already “trained” for auto-categorization
48. Concluding Remarks Some “taxonomy tools” are stronger in taxonomy/thesaurus/ontology management. Some “taxonomy tools” are stronger in auto-categorization. A few tools combine both, but vendor partnerships and connectors can also achieve high results.