This document summarizes Yandex's use and development of semantic markup. It discusses how Yandex uses semantic markup to enhance search algorithms and snippets. It provides statistics showing that 24% of internet documents contain some semantic markup. It also gives an overview of the development of schema.org and how Yandex has contributed, including actions for JSON-LD and future work on schemas for civic services, reservations, and events.
What is Connected Data as a concept? Who is interested in Connected Data? What problems does Connected Data solve? What skills are used in Connected Data?
Connected Data as of July 2017 has been running for over a year with very successful conference and 9 meetups held to date on a range of topics. These have included Knowledge Representation, Semantics, Linked Data, Graph Databases, Ontology development and use cases and industry verticals including recommendations, telecoms and finance. Yet the group has never had a particularly formal terms of reference or description defining what Connected Data actually means. Some would say this is something of a irony for a group so focused on semantics, schemas, definitions & structure!
This is an attempt (with some humour and something of journey included in it) to achieve something resembling a definition and terms of reference for the group.
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
This XML Prague 2015 Pre-conference presentations shows practical usage of linked data sources. These sources can help to: enrich content with entities, add link to external data sources, use the enriched content in question answering, machine translation or other scenarios. The aim is to show the practical application of linked data sources in XML tooling. The presentation is an update and provides outcomes of the related session held at XML Prague 2014.
Introduction to GraphX | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2IYeuvF
This CloudxLab Introduction to GraphX tutorial helps you to understand GraphX in detail. Below are the topics covered in this tutorial:
1) Introduction to GraphX
2) What is Graph?
3) Examples of Graph Computation
4) Pagerank using GraphX
A modern resource view for tabular data.
This talks shows a modern drop-in replacement for the current default Recline.js based table view in CKAN, which is well beyond a normal table viewer.
What is Connected Data as a concept? Who is interested in Connected Data? What problems does Connected Data solve? What skills are used in Connected Data?
Connected Data as of July 2017 has been running for over a year with very successful conference and 9 meetups held to date on a range of topics. These have included Knowledge Representation, Semantics, Linked Data, Graph Databases, Ontology development and use cases and industry verticals including recommendations, telecoms and finance. Yet the group has never had a particularly formal terms of reference or description defining what Connected Data actually means. Some would say this is something of a irony for a group so focused on semantics, schemas, definitions & structure!
This is an attempt (with some humour and something of journey included in it) to achieve something resembling a definition and terms of reference for the group.
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
This XML Prague 2015 Pre-conference presentations shows practical usage of linked data sources. These sources can help to: enrich content with entities, add link to external data sources, use the enriched content in question answering, machine translation or other scenarios. The aim is to show the practical application of linked data sources in XML tooling. The presentation is an update and provides outcomes of the related session held at XML Prague 2014.
Introduction to GraphX | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2IYeuvF
This CloudxLab Introduction to GraphX tutorial helps you to understand GraphX in detail. Below are the topics covered in this tutorial:
1) Introduction to GraphX
2) What is Graph?
3) Examples of Graph Computation
4) Pagerank using GraphX
A modern resource view for tabular data.
This talks shows a modern drop-in replacement for the current default Recline.js based table view in CKAN, which is well beyond a normal table viewer.
Slides of my talk on distributed deep learning concepts and platforms, from the "Deep Learning for Poets" workshop at Tehran Polytechnic on December 19th, 2018.
Big Data has been around long enough that there are some common issues that occur whenever an organization tries to implement and integrate it into their ecosystem. This presentation covers some of those pitfalls, which also impact traditional data warehouses/business intelligence ecosystems
In search of database nirvana - The challenges of delivering Hybrid Transacti...Rohit Jain
Companies are looking for a single database engine that can address all their varied needs—from transactional to analytical workloads, against structured, semi-structured, and unstructured data, leveraging graph, document, text search, column, key value, wide column, and relational data stores; on a single platform without the latency of data transformation and replication. They are looking for the ultimate database nirvana.
The term hybrid transactional/analytical processing (HTAP), coined by Gartner, perhaps comes closest to describing this concept. 451 Research uses the terms convergence or converged data platform. The terms multi-model or unified are also used. But can such a nirvana be achieved? Some database vendors claim to have already achieved this nirvana. In this talk we will discuss the following challenges on the path to this nirvana, for you to assess how accurate these claims are:
· What is needed for a single query engine to support all workloads?
· What does it take for that single query engine to support multiple storage engines, each serving a different need?
· Can a single query engine support all data models?
· Can it provide enterprise-caliber capabilities?
Attendees looking to assess query and storage engines would benefit from understanding what the key considerations are when picking an engine to run their targeted workloads. Also, developers working on such engines can better understand capabilities they need to provide in order to run workloads that span the HTAP spectrum.
ROI in Linking Content to CRM by Applying the Linked Data StackMartin Voigt
Today, decision makers in enterprises have to rely more and more on a variety of data sets that are internally but also externally available in heterogeneous formats. Therefore, intelligent processes are required to build an integrated knowledge-base. Unfortunately, the adoption of the Linked Data lifecycle within enterprises, which targets the extraction, interlinking, publishing and analytics of distributed data, lags behind the public domain due to missing frameworks that are efficiently to deploy and ease to use. In this paper, we present our adoption of the lifecycle through our generic, enterprise-ready Linked Data workbench. To judge its benefits, we describe its application within a real-world Customer Relationship Management scenario. It shows (1) that sales employee could significantly reduce their workload and (2) that the integration of sophisticated Linked Data tools come with an obvious positive Return on Investment.
Advanced Analytics and Machine Learning with Data VirtualizationDenodo
Watch here: https://bit.ly/3719Bi7
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this webinar and learn:
-How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
-About the success McCormick has had as a result of seasoning the Machine Learning and Blockchain Landscape with data virtualization
People like graphs. In nowadays they use facebook social graph search to find ex-girlfriend/boyfriends of their sweet hearts, or to search for a new love. Moreover - companies use graphs to evaluate the internal communication effectiveness or to design the enterprise network scheme. In all those tasks the simple questions arise - what type of data storage should be used to solve the problem in the most effective and easy? Graph databases!
The Power of Semantic Technologies to Explore Linked Open DataOntotext
Atanas Kiryakov's, Ontotext’s CEO, presentation at the first edition of Graphorum (http://graphorum2017.dataversity.net/) – a new forum that taps into the growing interest in Graph Databases and Technologies. Graphorum is co-located with the Smart Data Conference, organized by the digital publishing platform Dataversity.
The presentation demonstrates the capabilities of Ontotext’s own approach to contributing to the discipline of more intelligent information gathering and analysis by:
- graphically explorinh the connectivity patterns in big datasets;
- building new links between identical entities residing in different data silos;
- getting insights of what type of queries can be run against various linked data sets;
- reliably filtering information based on relationships, e.g., between people and organizations, in the news;
- demonstrating the conversion of tabular data into RDF.
Learn more at http://ontotext.com/.
Enterprise systems are increasingly complex, often requiring data and software components to be accessed and maintained by different company departments. This complexity often becomes an organization’s biggest challenge as changing data fields and adding new applications rapidly grow to meet business demands for increased customer insights.
These slides are from a Webinar discussing how using SHACL and JSON-LD with AllegroGraph helps our customers simplify the complexity of enterprise systems through the ability to loosely combine independent elements, while allowing the overall system to function smoothly.
In this Webinar we will demonstrate how AllegroGraph’s SHACL validation engine confirms whether JSON-LD data is conforming to the desired requirements. We will describe how SHACL provides a way for a Data Graph to specify the Shapes Graph that should be used for validation and describes how a given shape is linked to targets in the data.
The recording is at youtube.com/allegrograph
Kasabi, an online data market based on linked data principles, offers data publishers an easy way to publish, link and monetise data, while giving developers of data-centric applications access to this data in different formats and through a number of different interfaces.
Knowledge Discovery tools using Linked Data techniques - {resentation for the Linked Data 4 Knowledge Discovery Workshop at ECML/PKDD2015 conference - http://events.kmi.open.ac.uk/ld4kd2015/ -
Slides of my talk on distributed deep learning concepts and platforms, from the "Deep Learning for Poets" workshop at Tehran Polytechnic on December 19th, 2018.
Big Data has been around long enough that there are some common issues that occur whenever an organization tries to implement and integrate it into their ecosystem. This presentation covers some of those pitfalls, which also impact traditional data warehouses/business intelligence ecosystems
In search of database nirvana - The challenges of delivering Hybrid Transacti...Rohit Jain
Companies are looking for a single database engine that can address all their varied needs—from transactional to analytical workloads, against structured, semi-structured, and unstructured data, leveraging graph, document, text search, column, key value, wide column, and relational data stores; on a single platform without the latency of data transformation and replication. They are looking for the ultimate database nirvana.
The term hybrid transactional/analytical processing (HTAP), coined by Gartner, perhaps comes closest to describing this concept. 451 Research uses the terms convergence or converged data platform. The terms multi-model or unified are also used. But can such a nirvana be achieved? Some database vendors claim to have already achieved this nirvana. In this talk we will discuss the following challenges on the path to this nirvana, for you to assess how accurate these claims are:
· What is needed for a single query engine to support all workloads?
· What does it take for that single query engine to support multiple storage engines, each serving a different need?
· Can a single query engine support all data models?
· Can it provide enterprise-caliber capabilities?
Attendees looking to assess query and storage engines would benefit from understanding what the key considerations are when picking an engine to run their targeted workloads. Also, developers working on such engines can better understand capabilities they need to provide in order to run workloads that span the HTAP spectrum.
ROI in Linking Content to CRM by Applying the Linked Data StackMartin Voigt
Today, decision makers in enterprises have to rely more and more on a variety of data sets that are internally but also externally available in heterogeneous formats. Therefore, intelligent processes are required to build an integrated knowledge-base. Unfortunately, the adoption of the Linked Data lifecycle within enterprises, which targets the extraction, interlinking, publishing and analytics of distributed data, lags behind the public domain due to missing frameworks that are efficiently to deploy and ease to use. In this paper, we present our adoption of the lifecycle through our generic, enterprise-ready Linked Data workbench. To judge its benefits, we describe its application within a real-world Customer Relationship Management scenario. It shows (1) that sales employee could significantly reduce their workload and (2) that the integration of sophisticated Linked Data tools come with an obvious positive Return on Investment.
Advanced Analytics and Machine Learning with Data VirtualizationDenodo
Watch here: https://bit.ly/3719Bi7
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this webinar and learn:
-How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
-About the success McCormick has had as a result of seasoning the Machine Learning and Blockchain Landscape with data virtualization
People like graphs. In nowadays they use facebook social graph search to find ex-girlfriend/boyfriends of their sweet hearts, or to search for a new love. Moreover - companies use graphs to evaluate the internal communication effectiveness or to design the enterprise network scheme. In all those tasks the simple questions arise - what type of data storage should be used to solve the problem in the most effective and easy? Graph databases!
The Power of Semantic Technologies to Explore Linked Open DataOntotext
Atanas Kiryakov's, Ontotext’s CEO, presentation at the first edition of Graphorum (http://graphorum2017.dataversity.net/) – a new forum that taps into the growing interest in Graph Databases and Technologies. Graphorum is co-located with the Smart Data Conference, organized by the digital publishing platform Dataversity.
The presentation demonstrates the capabilities of Ontotext’s own approach to contributing to the discipline of more intelligent information gathering and analysis by:
- graphically explorinh the connectivity patterns in big datasets;
- building new links between identical entities residing in different data silos;
- getting insights of what type of queries can be run against various linked data sets;
- reliably filtering information based on relationships, e.g., between people and organizations, in the news;
- demonstrating the conversion of tabular data into RDF.
Learn more at http://ontotext.com/.
Enterprise systems are increasingly complex, often requiring data and software components to be accessed and maintained by different company departments. This complexity often becomes an organization’s biggest challenge as changing data fields and adding new applications rapidly grow to meet business demands for increased customer insights.
These slides are from a Webinar discussing how using SHACL and JSON-LD with AllegroGraph helps our customers simplify the complexity of enterprise systems through the ability to loosely combine independent elements, while allowing the overall system to function smoothly.
In this Webinar we will demonstrate how AllegroGraph’s SHACL validation engine confirms whether JSON-LD data is conforming to the desired requirements. We will describe how SHACL provides a way for a Data Graph to specify the Shapes Graph that should be used for validation and describes how a given shape is linked to targets in the data.
The recording is at youtube.com/allegrograph
Kasabi, an online data market based on linked data principles, offers data publishers an easy way to publish, link and monetise data, while giving developers of data-centric applications access to this data in different formats and through a number of different interfaces.
Knowledge Discovery tools using Linked Data techniques - {resentation for the Linked Data 4 Knowledge Discovery Workshop at ECML/PKDD2015 conference - http://events.kmi.open.ac.uk/ld4kd2015/ -
Доклад на третью Вебмастерскую. В докладе рассказано о новом инструменте для проверки семантической микроразметки и о том, как он может помочь при работе с сайтом. Кроме того, вы узнаете о новых способах использования микроразметки и о том, какие изменения произошли в старых партнёрских программах на её основе. Также презентация содержит ответы на вопросы, которые часто возникают у вебмастеров.
G.D.C.&A. AND C.H.M. ARE UNIQUE STUDY PROGRAMMES OFFERED BY THE GOVERNMENT OF MAHARASHTRA WITH AN OBJECT TO MAKE AVAILABLE QUALIFIED PROFESSIONALS IN THE EVER GROWING CO-OPERATIVE SECTOR IN MAHARASHTRA. AFTER PASSING EXAMINATION OF THESE VALUABLE STUDY PROGRAMMES, SO MANY CAREER OPPORTUNITIES ARE AVAILABLE IN CO-OPERATIVE SECTOR IN MAHARASHTRA STATE.
97th Constitutional Amendment Act, 2011 for Co-operative SectorAdv Bornak B R
97th Constitutional Amendment Act, 2011 has been proved as
the honest effort by our Parliament to bring revolutionary changes in co-operative sector in our country.
G.D.C.&A. and C.H.M.- JOB & CAREER ORIENTED GOVERNMENT COURSES.Adv Bornak B R
GDC&A and CHM are Government Courses to provide opportunities of Job and Career as professionals and consultants in Co-operative Housing, Credit, Consumers etc. societies, Co-operative Banks and Government services.
We’ve all seen Google results that feature detailed contact and location information, recipe details and reviews, browsable discographies and more when we’re looking for information. These kind of rich search results give users instant access to the most actionable and shareable content on your website, creating a great user experience before they even get to your site. What kind of dark arts are site owners using to create this kind of detailed, rich information that search engines gobble up and use to create meaningful, easy to digest search results for their audiences? The answer lies in structured data formats.
Attendees will leave this talk with a basic understanding of what structured data is, the formats available, and what types of structured data benefit a site the most when it comes to SEO. We’ll also look at what tools are available to most efficiently use these principles within Drupal.
At Data-centric Architecture Forum 2020 Thomas Cook, our Sales Director of AnzoGraph DB, gave his presentation "Knowledge Graph for Machine Learning and Data Science". These are his slides.
Talk about schema.org at ISWC2012. Covering what is schema.org, how it is used in Yandex (russian Google) and future plans.
Speakers: Peter Mika (Yahoo!), Alex Shubin (Yandex)
Webinar: Enterprise Data Management in the Era of MongoDB and Data LakesMongoDB
With so much talk of how Big Data is revolutionizing the world and how a data lake with Hadoop and/or Spark will solve all your data problems, it is hard to tell what is hype, reality, or somewhere in-between.
In working with dozens of enterprises in varying stages of their enterprise data management (EDM) strategy, MongoDB enterprise architect, Matt Kalan, sees the same challenges and misunderstandings arise again and again.
In this session, he will explain common challenges in data management, what capabilities are necessary, and what the future state of architecture looks like. MongoDB is uniquely capable of filling common gaps in the data lake strategy.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
After this presentation you will know how to:
- sell Drupal 8 to business on large enterprise
- plan migration of code and content
- technically migrate a lot of custom code and data
- automate migration process
- test migration and regression
- overcome migration challenges, based on a JYSK case
https://drupalcampkyiv.org/node/55
LDM Slides: Data Modeling for XML and JSONDATAVERSITY
Data modeling has traditionally focused on relational database systems. But in the age of the internet, technologies such as XML and JSON have evolved to provide structure and definition to “data in motion”. Have data modeling technologies evolved to support these technologies? Can we use traditional approaches to model data in XML and JSON? Or are new tools and methodologies required? Join this webinar to discuss:
- XML & JSON vs. Relational Database Modeling
- Techniques & Tools for Data Modeling for XML
- Techniques & Tools for Data Modeling for JSON
- Use Cases & Opportunities for XML and JSON Data Modeling
Thomas Delerm and Adrien Di Mascio from Logibal will explain the interest of web semantics in modern web applications for the best use of your data.
They’ll give the recipes that make Jahia an appropriate CMS for the semantic and linked data web, a.k.a "web 3.0"
"Semantic Integration Is What You Do Before The Deep Learning". dev.bg Machine Learning seminar, 13 May 2019.
It's well known that 80\% of the effort of a data scientist is spent on data preparation. Semantic integration is arguably the best way to spend this effort more efficiently and to reuse it between tasks, projects and organizations. Knowledge Graphs (KG) and Linked Open Data (LOD) have become very popular recently. They are used by Google, Amazon, Bing, Samsung, Springer Nature, Microsoft Academic, AirBnb… and any large enterprise that would like to have a holistic (360 degree) view of its business. The Semantic Web (web 3.0) is a way to build a Giant Global Graph, just like the normal web is a Global Web of Documents. IEEE already talks about Big Data Semantics. We review the topic of KGs and their applicability to Machine Learning.
A two day training session for colleagues at Aimia, to introduce them to R. Topics covered included basics of R, I/O with R, data analysis and manipulation, and visualisation.
Similar to The main trends in the use and development (20)
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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
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.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Hi, my name is Yuliya. I am working for Yandex at Semantic Web Project. Today I intend to discuss The Main Trends in the Use and Development of Semantic Markup
Firstly I want to talk about the reasons for using semantic markup in Yandex. Then we'll talk a little bit about the basic terms. Finally in general discuss the development of semantic markup an example schema.org
So, why do we need all this stuff?
There is a huge pile of raw data in the Internet. But it's not enough for give an answer to our users. To give them good answer we need knowledge rather than raw data.
We can extract knowledge automatically (using machine learning, language technologies or specialized parsers). And we can get knowledge about content of web pages directly from the webmasters. Both methods have their advantages and disadvantages.
Self data mining allows us not be dependent on webmasters. Furthermore, this method is more is technological. But sometimes we need special parser for each web site. An important disadvantage of this method is the lack of webmasters the opportunity to influence our knowledge of their site.
On the other side the receipt of data from the webmasters also have advantages and disadvantages. It is good that we get information about the contents of pages from the people who really know what is written on it. In addition, we need to make less effort to use those knowledge in search. But from the other hand many people is not so honest as I'd wish to. And they may try to fraud the system. And, of course, not all webmasters want to make an effort to give us any information.
In view of the above at the end of 2009 we started to use in our services the additional information sent by webmasters.
How we can collect information from webmasters? First of all by using special tools. Second, by using XML-files special formats. And other files. Even excel. Another variance does not involve something other than HTML code of pages. Semantic markup is included directly in page's source code.
Let's talk about semantic markup.
I want to say some words about syntax and vocabulary, tell about usage of semantic markup and bring some statistics.
Semantic markup consist of syntax and vocabulary. First is about how we put information into pages. Second is about what information we give.
There are for main syntax of semantic markup: RDFa, Microformats, Microdata and the newest - JSON-LD. And then there are some dictionaries that can be used with these syntaxes. The oldest one is DublinCore. Originally it was created in 1995. In Russia there is even a Standard, describing the Dublin Core. It is very simple and contains only 15 elements. Do not be surprised that microformats are listed as a vocabulary.This is because there are mixed form and meaning. GoodRelations is a specialized vocabulary that describes the goods and services. Open Graph Protocol is an initiative of Facebook. It is a simple way to convey the most important information about content of page. Schema.org is the most promising dictionary, supported by Google, Bing, Yahoo, and by Yandex.
Some history. A long long time ago far far away in the Galaxy... wait! It's another story. We begun using semantic markup in late 2009. We start makin rich snippet and services based on semantic markup. In the next year W3C announced HTML5 and microdata. And we started usage this method in our products. We even wrote a dictionary of data about encyclopedias. Than Facebook has announced The Open Graph Protocol. The following year was created schema.org. And the world has changed. We came up with new ways to use this markup. As well as changes in the schema.org. The first Yandex proposal in schema.org was PeopleAudience. Now it is accepted and published, but it takes a lot of time to do this. From the outside it seems that there is nothing easier than to add a few new properties. But you should predict what people think and what they might think. How will webmasters and consumers use this data. Isn't it too difficult? Do you want to specify the gender of the target audience? Be ready to think about that it might offend people belonging to one sex but identify themselves with the other. Do you want to specify the age of the target audience of the content? It's might to offend adults who love to read children's books. To date, we have actions and JSON-LD syntax . And we use it in Yandex.Islands.
According to our base 24% documents in the internet contains some semantic markup. A lot or a little? Of course, this is far from 100%, but over the past three years, the number has risen to more than twice.
Here you can see our statistics of semantic markup distribution. The most popular vocabulary is The Open Graph Protocol. Next is schema.org. And those small bar is GoodRelations.
How can this data be used? The major consumer is Search Engines. It uses this data for creation rich snippets and reception content from webmasters to some services. For example, Yandex creates rich snippets for recipes, dictionary articles, movies, chords, etc. And uses information extracted from microdata in Video, Auto, Images and other services. But not only search engines consume semantic markup. Other internet companies also can do this. For example, pinterest uses OG and Schema.org for creating Rich Pins. Facebook, Google , twitter and other social network can create rich snippets for shared links.
Schema.org does not stand still. There two level of changing: 1) Public feedback and discussion. The most important point from publick discussion goes to work group 2) Work group consist of delegate from 4 search engines (Yandex, Google, Bing and Yahoo). They decide wether to make changes or not.
If you have some idea, problem or question you can send it to Public-vocabs@w3.org You also can read this mail list and reply to the questions and help to solves someone's problems.
If the idea has sense it will work through the working group. First of all we explore the idea. What the idea is? Where we sould place this change? How often is this use case? What are the challenges we face? Than we should discuss this idea. When all are agreed formulated idea sends to Public-vocabs@w3.org. Next step is collecting feedback from community. If there is a significant comments we need to repeat the cycle. It seems that no idea will never be accepted. But it is not true. And here are some new updates.
Actions - it's like a verb in the vocabulary
GoodRelations - this is about integration between schema.org and GoodRelations
Integration with vocabulary for learning resources metadata
Health and Medical vocabulary - this is about including Health and Medical vocabulary
JSON-LD - it's about using schema.org in new syntax.
And there are some future work
Potential actions - how describe an action that will happened in future