The document discusses the need for ontologies and conceptual modeling in the financial derivatives industry. It notes that a 2010 law requires regulators to study using standardized computer-readable descriptions of derivatives. These descriptions could serve as legal definitions if together with standardized definitions. The document suggests that ontologies may help define and describe derivatives transactions and positions, and questions how financial institutions currently approach this. It asks about what ontologies are used, how they are maintained and extended to cover new products, and their scope and limitations.
The document discusses knowledge organization in cell biology and science education. It presents several working hypotheses about how understanding concepts and organizing them helps learning and transforms novices into experts. The importance of knowledge organization in curriculum development and conceptual change is explained. Different ways of representing knowledge like concept maps and semantic networks are described. The methodology section discusses classifying concepts, assigning semantic relations, comparing novice and expert knowledge structures, and developing a three-layer model for knowledge representation.
A Proposal to Refine Concept Maps for Effective Science LearningMeena Kharatmal
The document proposes refining the use of concept maps for effective science learning. It outlines problems with concept maps for learning and evaluation and suggests improvements. These include using a limited set of precise relation types instead of various linking words, and assessing conceptual change by comparing successive concept maps. The refined concept map example on "life in the ocean" uses hierarchy and five relation types for improved clarity and precision over traditional concept maps.
This document introduces the concept of refined concept maps (RCM) as a way to make traditional concept maps more rigorous and less ambiguous. RCM focuses on using a finite set of well-defined semantic relation names instead of loose linking words. This allows knowledge to be represented in a more formal and logically consistent way while still being accessible to novices. The document provides examples of converting traditional concept maps to RCM and discusses how RCM could serve as a bridge between informal and formal knowledge representation.
News Linked Data Summit - BBC News and Linked Datasilveroliver
The document discusses Linked Data at the BBC, including both publishing and consuming Linked Data. It mentions user experience, structure and navigation, and content repositories as they relate to Linked Data. The document also discusses populating an ontology with information about sports teams, venues, athletes, and events.
This document discusses how the value in the digital media landscape is shifting from content to data and personalized user experiences. As content becomes abundant and easily distributed online, companies need to focus on gathering unique customer data across multiple platforms and using that data to create tailored, multi-platform experiences for users. The document also notes challenges in monetizing digital media through advertising and paid content models and argues that combining scale and behavioral targeting across a network of owned brands and platforms can help companies overcome these challenges by serving advertiser needs more completely and creating unique inventory.
Transforming the User Experience of the BBCRichard Titus
The document discusses the BBC's efforts to modernize and expand its online presence to meet changing audience needs and habits. Key points include developing a more inviting and customizable homepage, expanding access across multiple platforms like mobile and IPTV, creating topic pages to better organize content, and leveraging semantic web technologies and user feedback to continuously improve search and discovery of BBC content.
The document discusses the BBC's efforts to implement semantic web and linked data technologies. It provides background on how the web has evolved from documents to data. It then outlines how the BBC is publishing structured data about programs, music, and other content using ontologies and linking to external data sources like MusicBrainz and Wikipedia. It aims to continue enhancing its linked data efforts across additional domains and work with identity providers to link user data.
Recognos is a semantic technology company established in 1999 with offices in California and Romania. They have 70 employees conducting research and development into semantic technologies. Their applications include finance, CRM, life sciences, and more. Semantic technology aims to teach machines human reasoning by representing knowledge as statements describing concepts, logic, and relationships. This allows for integrated querying across structured and unstructured data sources. Recognos can help companies like Netflix develop semantic applications such as integrated search across data sources and detecting similarities in film descriptions.
The document discusses knowledge organization in cell biology and science education. It presents several working hypotheses about how understanding concepts and organizing them helps learning and transforms novices into experts. The importance of knowledge organization in curriculum development and conceptual change is explained. Different ways of representing knowledge like concept maps and semantic networks are described. The methodology section discusses classifying concepts, assigning semantic relations, comparing novice and expert knowledge structures, and developing a three-layer model for knowledge representation.
A Proposal to Refine Concept Maps for Effective Science LearningMeena Kharatmal
The document proposes refining the use of concept maps for effective science learning. It outlines problems with concept maps for learning and evaluation and suggests improvements. These include using a limited set of precise relation types instead of various linking words, and assessing conceptual change by comparing successive concept maps. The refined concept map example on "life in the ocean" uses hierarchy and five relation types for improved clarity and precision over traditional concept maps.
This document introduces the concept of refined concept maps (RCM) as a way to make traditional concept maps more rigorous and less ambiguous. RCM focuses on using a finite set of well-defined semantic relation names instead of loose linking words. This allows knowledge to be represented in a more formal and logically consistent way while still being accessible to novices. The document provides examples of converting traditional concept maps to RCM and discusses how RCM could serve as a bridge between informal and formal knowledge representation.
News Linked Data Summit - BBC News and Linked Datasilveroliver
The document discusses Linked Data at the BBC, including both publishing and consuming Linked Data. It mentions user experience, structure and navigation, and content repositories as they relate to Linked Data. The document also discusses populating an ontology with information about sports teams, venues, athletes, and events.
This document discusses how the value in the digital media landscape is shifting from content to data and personalized user experiences. As content becomes abundant and easily distributed online, companies need to focus on gathering unique customer data across multiple platforms and using that data to create tailored, multi-platform experiences for users. The document also notes challenges in monetizing digital media through advertising and paid content models and argues that combining scale and behavioral targeting across a network of owned brands and platforms can help companies overcome these challenges by serving advertiser needs more completely and creating unique inventory.
Transforming the User Experience of the BBCRichard Titus
The document discusses the BBC's efforts to modernize and expand its online presence to meet changing audience needs and habits. Key points include developing a more inviting and customizable homepage, expanding access across multiple platforms like mobile and IPTV, creating topic pages to better organize content, and leveraging semantic web technologies and user feedback to continuously improve search and discovery of BBC content.
The document discusses the BBC's efforts to implement semantic web and linked data technologies. It provides background on how the web has evolved from documents to data. It then outlines how the BBC is publishing structured data about programs, music, and other content using ontologies and linking to external data sources like MusicBrainz and Wikipedia. It aims to continue enhancing its linked data efforts across additional domains and work with identity providers to link user data.
Recognos is a semantic technology company established in 1999 with offices in California and Romania. They have 70 employees conducting research and development into semantic technologies. Their applications include finance, CRM, life sciences, and more. Semantic technology aims to teach machines human reasoning by representing knowledge as statements describing concepts, logic, and relationships. This allows for integrated querying across structured and unstructured data sources. Recognos can help companies like Netflix develop semantic applications such as integrated search across data sources and detecting similarities in film descriptions.
This document summarizes the first meeting of the Knowledge Representation seminar at Kings College London in June 2010. It discusses ontologies from three perspectives:
1) The theoretical perspective defines ontologies and discusses different definitions.
2) The pragmatic perspective explains what ontologies are used for.
3) The design perspective outlines how to build ontologies and discusses components like logic, ontology, and computation.
The document also covers topics like the differences between ontologies and data models or knowledge bases, degrees of "ontological depth", upper vs. domain ontologies, examples of top-level ontologies, and realist vs. conceptualist perspectives on ontologies.
Modeling a Probabilistic Ontology for Maritime Domain AwarenessRommel Carvalho
The document describes developing a probabilistic ontology for maritime domain awareness. It aims to develop an ontology capable of reasoning with evidence from different domains to provide situational awareness. It discusses ontologies, probabilistic ontologies, and using the Probabilistic Web Ontology Language and other techniques. It also presents an uncertainty modeling process and incremental methodology for modeling the probabilistic ontology, including modeling cycles with goals, queries, evidence and assumptions.
Ontology quality, ontology design patterns, and competency questionsNicola Guarino
This document discusses ontology quality and the role of ontology design patterns (ODPs) in improving quality. It addresses three dimensions of ontology quality: correctness, precision, and accuracy. While ODPs aim to improve reusability, their simplicity may decrease interoperability if connections between patterns are overlooked. The original intent of competency questions was for more complex queries than simple lookups. Properly defining terms and examples/counter-examples for a target community helps improve an ontology's quality.
The document discusses ontology from philosophical and computer science perspectives. In philosophy, ontology is the science of being and investigates categories of things that exist. In computer science, an ontology is an explicit specification of a conceptualization - the objects, relations, and other entities that are presumed to exist in some area of interest. It defines the types, properties, and interrelationships of the entities. The document contrasts ontologies with other concepts like conceptual schemas, knowledge bases, and classifications. It also discusses challenges in ontology engineering like balancing domain independence with application dependencies.
PR-OWL 2.0 - Bridging the gap to OWL semanticsRommel Carvalho
The document discusses bridging the gap between PR-OWL and OWL semantics. It introduces probabilistic ontologies which include types of entities, properties, relationships, processes/events, statistical regularities, and uncertainty. It describes how the mapping between PR-OWL and OWL is currently incomplete and proposes solutions to better represent binary and n-ary relations between concepts.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
This document summarizes the first meeting of the Knowledge Representation seminar at Kings College London in June 2010. It discusses ontologies from three perspectives:
1) The theoretical perspective defines ontologies and discusses different definitions.
2) The pragmatic perspective explains what ontologies are used for.
3) The design perspective outlines how to build ontologies and discusses components like logic, ontology, and computation.
The document also covers topics like the differences between ontologies and data models or knowledge bases, degrees of "ontological depth", upper vs. domain ontologies, examples of top-level ontologies, and realist vs. conceptualist perspectives on ontologies.
Modeling a Probabilistic Ontology for Maritime Domain AwarenessRommel Carvalho
The document describes developing a probabilistic ontology for maritime domain awareness. It aims to develop an ontology capable of reasoning with evidence from different domains to provide situational awareness. It discusses ontologies, probabilistic ontologies, and using the Probabilistic Web Ontology Language and other techniques. It also presents an uncertainty modeling process and incremental methodology for modeling the probabilistic ontology, including modeling cycles with goals, queries, evidence and assumptions.
Ontology quality, ontology design patterns, and competency questionsNicola Guarino
This document discusses ontology quality and the role of ontology design patterns (ODPs) in improving quality. It addresses three dimensions of ontology quality: correctness, precision, and accuracy. While ODPs aim to improve reusability, their simplicity may decrease interoperability if connections between patterns are overlooked. The original intent of competency questions was for more complex queries than simple lookups. Properly defining terms and examples/counter-examples for a target community helps improve an ontology's quality.
The document discusses ontology from philosophical and computer science perspectives. In philosophy, ontology is the science of being and investigates categories of things that exist. In computer science, an ontology is an explicit specification of a conceptualization - the objects, relations, and other entities that are presumed to exist in some area of interest. It defines the types, properties, and interrelationships of the entities. The document contrasts ontologies with other concepts like conceptual schemas, knowledge bases, and classifications. It also discusses challenges in ontology engineering like balancing domain independence with application dependencies.
PR-OWL 2.0 - Bridging the gap to OWL semanticsRommel Carvalho
The document discusses bridging the gap between PR-OWL and OWL semantics. It introduces probabilistic ontologies which include types of entities, properties, relationships, processes/events, statistical regularities, and uncertainty. It describes how the mapping between PR-OWL and OWL is currently incomplete and proposes solutions to better represent binary and n-ary relations between concepts.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
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Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
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Creating a compelling user experience for any software, without the limitations of APIs.
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seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
Onto gov
1. Foundational Ontology,
Conceptual Modeling
and Data Semantics
Giancarlo Guizzardi
gguizzardi@acm.org
http://nemo.inf.ufes.br
Computer Science Department
Federal University of
GT OntoGOV (W3C Brazil), Espírito Santo (UFES),
São Paulo, Brazil Brazil
11. The Dodd-Frank Wall Street Reform and Consumer Protection Act
(``Dodd-Frank Act'‘) was enacted on July 21, 2010. The Dodd-Frank
Act, among other things, mandates that the Commodity Futures
Trading Commission (``CFTC'') and the Securities and Exchange
Commission (``SEC'') conduct a study on ``the feasibility of requiring
the derivatives industry to adopt standardized computer-readable
algorithmic descriptions which may be used to describe complex
and standardized financial derivatives.'' These algorithmic
descriptions should be designed to ``facilitate computerized
analysis of individual derivative contracts and to calculate net
exposures to complex derivatives.'' The study also must consider
the extent to which the algorithmic description, ``together with
standardized and extensible legal definitions, may serve as the
binding legal definition of derivative contracts.'‘
12. 7. Do you rely on a discrete set of computer-readable descriptions
(``ontologies'') to define and describe derivatives transactions and
positions? If yes, what computer language do you use?
8. If you use one or more ontologies to define derivatives
transactions and positions, are they proprietary or open to the
public? Are they used by your counterparties and others in the
derivatives industry?
9. How do you maintain and extend the ontologies that you use to
define derivatives data to cover new financial derivative products?
How frequently are new terms, concepts and definitions added?
10. What is the scope and variety of derivatives and their
positions covered by the ontologies that you use? What do they
describe well, and what are their limitations?
.
14. “What are ontologies and why we
need them?”
1. Reference Model of Consensus to support different types of
Semantic Interoperability Tasks
2. Explicit, declarative and machine processable artifact coding
a domain model to enable efficient automated reasoning
16. Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
17. ?
Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
18. Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
19. R
?
Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
20. R
R’
Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
21. Situations represented by Admissible state of affairs
the valid specifications of according to a
language L conceptualization C
22. State of affairs
represented
by the valid models
of Ontology O1 State of affairs represented by the valid models
of Ontology O2
Admissible state of affairs
according to the
conceptualization
underlying
O2
Admissible state of affairs
according to the conceptualization underlying
O1
23. State of affairs
represented
by the valid models
of Ontology O1 State of affairs represented by the valid models
of Ontology O2
Admissible state of affairs
according to the
conceptualization
underlying
O2
Admissible state of affairs
according to the conceptualization underlying
O1
FALSE AGREEMENT!
24. “one of the main reasons that so many
online market makers have foundered
[is that] the transactions they had
viewed as simple and routine actually
involved many subtle distinctions in
terminology and meaning”
(Harvard Business Review)
25. 1. We need to recognize that There
is not Silver Bullet! and start seing
ontology engineering from an
engineering perspective
26. A Software Engineering view…
Conceptual Modeling
Implementation1 Implementation2 Implementation3
28. …transported to Ontological Engineering
Ontology as a
Conceptual Model
Ontology as Ontology as Ontology as
Implementation1 Implementation2 Implementation3
(SHOIN/OWL-DL, (CASL) (Alloy, F-Logic…)
DLRUS)
29. …transported to Ontological Engineering
Ontology as a
Conceptual Model
DESIGN
Ontology as Ontology as Ontology as
Implementation1 Implementation2 Implementation3
(SHOIN/OWL-DL, (CASL) (Alloy, F-Logic…)
DLRUS)
34. The Ontological Level
sortal universal characterizing
Universal
Apple Red
color = red sort = apple
35. Formal Ontology
• To uncover and analyze the general categories and principles
that describe reality is the very business of philosophical
Formal Ontology
• Formal Ontology (Husserl): a discipline that deals with
formal ontological structures (e.g. theory of parts, theory of
wholes, types and instantiation, identity, dependence, unity)
which apply to all material domains in reality.
36. Foundational Ontology
• We name a foundational ontology the product of the
discipline of formal ontology in philosophy
• A foundational ontology is a formal framework of generic
(i.e. domain independent) real-world concepts that can be
used to talk about material domains.
37. represented by Conceptual
Foundational
Ontology Modeling
interpreted as Language
38. Cognitive represented by
Foundational UML
Ontology (UFO) interpreted as
39. 2. We need ontology
representations languages which
are based on Truly Ontological
Distinctions
40. Formal Relations
0 Weight Quality Dimension
w1 w2
heavier (Paul, John)?
Paul
John
41. Material Relations
1..* treated In 1..*
«role» «kind»
Patient Medical Unit
42. Material Relations
How are these cardinality constraints to be interpreted ?
In a treatment, a patient is treated by several medical
units, and a patient can participate in many
treatments
In a treatment, a patient is treated by several medical
units, but a patient can only participate in one
treatment
In a treatment, several patients can be treated by one
medical unit, and a medical unit can participate in
many treatments
In a treatment, a patient is treated by one medical unit,
and a patient can participate in many treatments
...
43. The problem is even worse in n-ary associations (with n >
2)
44.
45. Explicit Representation for Material Relations
«mediation» «relator» «mediation»
Treatment
1..* 1..*
1 1..*
«material»
/TreatedIn
Patient MedicalUnit
1..* 1..*
46. Material Relations
As seen before from a relator and mediation relation
we can derive several material relations
Asides from all the benefits previously mentioned,
perhaps the most important contribution of
explicitly considering relations is to force the
modeler to answer the fundamental question of
what is truthmaker of that relation
47. Material Relations
Yet another example:
Modeling that a graduate student have one or more
supervisors and a supervisor can supervise one or
more students
48. Material Relations
Yet another example:
Modeling that a graduate student have one or more
supervisors and a supervisor can supervise one or
more students
49.
50. Unified Foundational Ontology (UFO)
UFO-C (SOCIAL ASPECTS)
(Agents, Intentional States, Goals, Actions,
Norms, Social Commitments/Claims, Social Dependency Relations…)
UFO-A (STRUCTURAL ASPECTS) UFO-B (DYNAMIC ASPECTS)
(Objects, their types, their parts/wholes, (Events and their parts,
the roles they play, Relations between events,
their intrinsic and relational properties Object participation in events,
Property value spaces…) Temporal properties of entities, Time…)
51. 3. We need Patterns
- Design Patterns
- Analysis Patterns
- Transformation Patterns
- Patterns Languages
57. Roles with Disjoint Allowed Types
«roleMixin»
Customer
Person Organization
«role» «role»
PersonalCustomer CorporateCustomer
58. «roleMixin» «kind» «roleMixin» «kind»
Customer Social Being Participant Social Being
«kind» Organization «kind» SIG
Person Person
«role» «role» «role» «role»
PrivateCustomer CorporateCustomer IndividualParticipant CollectiveParticipant
59. Roles with Disjoint Admissible Types
1..*
F
«roleMixin» 1..*
A
D E
«role» «role»
B C
60. Quality, Quality Values and Quality
Dimensions
c::Color
c
v2
Color Quality Space
a w
a::Apple w::Weight
v1
0
Weight Quality Space
81. when δ < x then we consider the communication to be effective, i.e., we assume the
existence of single shared conceptualization
semantic distance (δ)
representation interpretation
M
82. δ
R
R’
Type
ObjectType
Sortal Type Mixin Type
Rigid Sortal Type Anti-Rigid Sortal Type Anti-Rigid MixinType
Kind Phase Role RoleMixin
85. Small δ, Small Ontology Big δ, Small Ontology
Well-Founded
Techniches
Matching &
Alignment
Techniches
Small δ, Big Ontology Big δ, BIg Ontology
86. Small δ, Small Ontology Big δ, Small Ontology
Some Flexibility
Well-Founded
Techniches
Matching &
Alignment
Techniches
Small δ, Big Ontology Big δ, BIg Ontology
87. Small δ, Small Ontology Big δ, Small Ontology
Some Flexibility
Well-Founded
Techniches
Matching &
Alignment
Techniches
Intractable!
Small δ, Big Ontology Big δ, BIg Ontology
88. State of affairs
represented
by the valid models
of Ontology O1 State of affairs represented by the valid models
of Ontology O2
Admissible state of affairs
according to the
conceptualization
underlying
O2
Admissible state of affairs
according to the conceptualization underlying FOUNDATIONAL
O1
ONTOLOGY