Introduction to e-commerce
11/10/2012 at ITS Volterra Elia (Ancona)
Comenius Project New Ideas Factory
http://www.istitutovolterraelia.it/index.php?option=com_content&view=article&id=373&Itemid=342
The document discusses the topics of Web 2.0 including blogs, wikis, tags, and social networks. It provides an introduction and program for a course on Web 2.0 that will cover definitions of key concepts, examples like blogs and wikis, technical specifications, tagging and social bookmarking, and social networking sites. The course will also discuss theories related to Web 2.0 and evaluate students based on exercises and a final presentation.
CORA (COmmon Reference Architecture) ESSnet final meeting presentation
CORA was funded by Eurostat to start defining an architecture to improve software sharing
Introduction to e-commerce
11/10/2012 at ITS Volterra Elia (Ancona)
Comenius Project New Ideas Factory
http://www.istitutovolterraelia.it/index.php?option=com_content&view=article&id=373&Itemid=342
The document discusses the topics of Web 2.0 including blogs, wikis, tags, and social networks. It provides an introduction and program for a course on Web 2.0 that will cover definitions of key concepts, examples like blogs and wikis, technical specifications, tagging and social bookmarking, and social networking sites. The course will also discuss theories related to Web 2.0 and evaluate students based on exercises and a final presentation.
CORA (COmmon Reference Architecture) ESSnet final meeting presentation
CORA was funded by Eurostat to start defining an architecture to improve software sharing
Social networks , Job Searching and Research - 1Carlo Vaccari
This document provides an overview of social networks and their use for job searching and research. It discusses the evolution of the web to Web 2.0, with users playing a more active role as producers of content. Popular social networks like Facebook, Twitter, and LinkedIn are examined in terms of their functions and growth. The document also touches on risks of oversharing personal information on social networks and their potential benefits for professional networking and research.
Social network and job searching and SN for researchersCarlo Vaccari
This document discusses the use of social networks for job searching, research, and open access publishing. It provides information on popular professional social networks like LinkedIn and ResearchGate, noting their features for maintaining profiles, connecting with contacts, sharing publications and research, and finding job opportunities. Risks of oversharing personal information on social media for job searches are also addressed. The document advocates using social networks to establish expertise in one's field and facilitate collaboration between researchers.
IT tools for statistics, visualization, open dataCarlo Vaccari
This document discusses a twinning project between the EU and Turkey aimed at improving data quality in public accounts. It covers topics such as data warehousing, business intelligence, dashboards, OLAP tools, data visualization techniques including maps, charts and infographics. Open data practices and linked data are also discussed. Tools mentioned include Tableau, Google Public Data Explorer, and VIDI modules for the Drupal content management system.
The document provides an introduction to open government and open data. It discusses the origins and development of open data initiatives, including freedom of information laws, open source software movements, and more recent open government directives. Key aspects of open government discussed are transparency, participation, collaboration, and opening access to public sector information and government data.
The document describes the HLG Big Data project and sandbox. It discusses the formation of task teams to explore using big data for official statistics. The project aims to identify opportunities and issues with big data, analyze using it to produce official statistics, and facilitate knowledge sharing. A sandbox was created for researchers to experiment with tools and methods. Several task teams tested different data sources and analytics tools in the sandbox.
This document discusses engineering digitalization through task automation and reuse in the development lifecycle. It proposes a knowledge-centric approach to systems engineering using a knowledge management strategy. This includes defining a controlled vocabulary, relating terms through relationships and clusters, representing textual patterns for matching, and combining rules and tasks to infer information. This knowledge graph could then enable capabilities like requirements extraction, model population, quality checking, and reuse of system artifacts. The approach aims to automate tasks, link different artifact types, and leverage semantics and AI/ML to better understand and exploit knowledge embedded in systems artifacts.
This presentation was part of the Cloudify and XLAB Research Webinar about DevOps for Data Intensive Applications.
In this webinar we discussed how to leverage automation for your big data applications, using DICE tools based on the Cloudify Open Source Orchestration.
We want to make sure that developers use the time to develop their big data applications and not have to worry about deployment and operations, and have the shortest time to delivery possible.
We also cover using the DICE deployment tools for automated deployment of Spark, Storm, Cassandra or Hadoop.
Abstract. Enterprise adoption of AI/ML services has significantly accelerated in the last few years. However, the majority of ML models are still developed with the goal of solving a single task, e.g., predictiction, classification. In this talk, Debmalya Biswas will present the emerging paradigm of Compositional AI, also known as, Compositional Learning. Compositional AI envisions seamless composition of existing AI/ML services, to provide a new (composite) AI/ML service, capable of addressing complex multi-domain use-cases. In an enterprise context, this enables reuse, agility, and efficiency in development and maintenance efforts.
This document discusses model-driven architecture (MDA), an approach to system specification and interoperability based on the use of formal models. MDA uses platform-independent models that are translated to platform-specific models using formal rules. Core MDA standards like UML, MOF, XMI, and CWM define the infrastructure. The vision is for nearly seamless interoperability based on shared metadata and formal model translations, with a long-term goal of adaptive object models that can dynamically interpret models at runtime.
The document provides an overview of information flow processing (IFP) and compares different approaches to complex event processing (CEP). It introduces a functional model for IFP that describes common components like a receiver, decider, producer, and rules. It discusses key aspects that impact expressiveness, such as the selection policy, consumption policy, and ability to handle bursts of input data. The goal is to define modeling frameworks that can accommodate different CEP proposals and technologies.
Introduction to Microsoft SQL Server 2008 R2 Analysis ServiceQuang Nguyễn Bá
The document discusses SQL Server 2008 R2 Analysis Services and provides an overview of its key components including OLAP, multidimensional data analysis using dimensions and hierarchies, and how it utilizes a dimensional data warehouse with fact and dimension tables to store and retrieve data for analysis. It also explains how Analysis Services provides scalable and extensible solutions for analytics and delivers pervasive business insights.
Sodius provides model-driven interoperability solutions to enable data exchange between modeling tools used in systems engineering projects. It has collaborated with Cassidian since 2009 on projects such as developing a solution to migrate architecture models between the MEGA and System Architect tools. Cassidian is working on an Integrated Project Support Environment named IPSE to provide a suite of collaborative system engineering tools integrated using Sodius' MDWorkbench platform.
The document discusses information management and defines it as capturing, storing, managing, preserving, and delivering information. It also discusses cloud platforms, services, types, and provides examples of enterprise services, architectures, methodologies and blueprints for implementing information management solutions.
This talk will provide overview of big data software engineering and software engineering for big data as the tow fields need integrated. The interplay between the two field of research applications of Data Science and Software Engineering will enhance future perspective for a safe, secure, and sustainable approaches to data science and application of data science for 50 years of software engineering data that exists.
Challenges and solutions in Cloud computing for the Future InternetSOFIProject
This document discusses two projects - REMICS and Cloud4Trends - that address challenges in cloud computing. REMICS develops a model-driven methodology for migrating legacy applications to cloud services and addresses interoperability issues. It focuses on providing a domain-specific language for abstracting cloud deployment complexity and solving behavioral and data interoperability. Cloud4Trends leverages cloud infrastructure for real-time trend detection in social media streams, providing a scalable solution for analyzing large-scale data. It detects variations and trends using a cloud computing service developed by the VENUS-C project.
Social networks , Job Searching and Research - 1Carlo Vaccari
This document provides an overview of social networks and their use for job searching and research. It discusses the evolution of the web to Web 2.0, with users playing a more active role as producers of content. Popular social networks like Facebook, Twitter, and LinkedIn are examined in terms of their functions and growth. The document also touches on risks of oversharing personal information on social networks and their potential benefits for professional networking and research.
Social network and job searching and SN for researchersCarlo Vaccari
This document discusses the use of social networks for job searching, research, and open access publishing. It provides information on popular professional social networks like LinkedIn and ResearchGate, noting their features for maintaining profiles, connecting with contacts, sharing publications and research, and finding job opportunities. Risks of oversharing personal information on social media for job searches are also addressed. The document advocates using social networks to establish expertise in one's field and facilitate collaboration between researchers.
IT tools for statistics, visualization, open dataCarlo Vaccari
This document discusses a twinning project between the EU and Turkey aimed at improving data quality in public accounts. It covers topics such as data warehousing, business intelligence, dashboards, OLAP tools, data visualization techniques including maps, charts and infographics. Open data practices and linked data are also discussed. Tools mentioned include Tableau, Google Public Data Explorer, and VIDI modules for the Drupal content management system.
The document provides an introduction to open government and open data. It discusses the origins and development of open data initiatives, including freedom of information laws, open source software movements, and more recent open government directives. Key aspects of open government discussed are transparency, participation, collaboration, and opening access to public sector information and government data.
The document describes the HLG Big Data project and sandbox. It discusses the formation of task teams to explore using big data for official statistics. The project aims to identify opportunities and issues with big data, analyze using it to produce official statistics, and facilitate knowledge sharing. A sandbox was created for researchers to experiment with tools and methods. Several task teams tested different data sources and analytics tools in the sandbox.
This document discusses engineering digitalization through task automation and reuse in the development lifecycle. It proposes a knowledge-centric approach to systems engineering using a knowledge management strategy. This includes defining a controlled vocabulary, relating terms through relationships and clusters, representing textual patterns for matching, and combining rules and tasks to infer information. This knowledge graph could then enable capabilities like requirements extraction, model population, quality checking, and reuse of system artifacts. The approach aims to automate tasks, link different artifact types, and leverage semantics and AI/ML to better understand and exploit knowledge embedded in systems artifacts.
This presentation was part of the Cloudify and XLAB Research Webinar about DevOps for Data Intensive Applications.
In this webinar we discussed how to leverage automation for your big data applications, using DICE tools based on the Cloudify Open Source Orchestration.
We want to make sure that developers use the time to develop their big data applications and not have to worry about deployment and operations, and have the shortest time to delivery possible.
We also cover using the DICE deployment tools for automated deployment of Spark, Storm, Cassandra or Hadoop.
Abstract. Enterprise adoption of AI/ML services has significantly accelerated in the last few years. However, the majority of ML models are still developed with the goal of solving a single task, e.g., predictiction, classification. In this talk, Debmalya Biswas will present the emerging paradigm of Compositional AI, also known as, Compositional Learning. Compositional AI envisions seamless composition of existing AI/ML services, to provide a new (composite) AI/ML service, capable of addressing complex multi-domain use-cases. In an enterprise context, this enables reuse, agility, and efficiency in development and maintenance efforts.
This document discusses model-driven architecture (MDA), an approach to system specification and interoperability based on the use of formal models. MDA uses platform-independent models that are translated to platform-specific models using formal rules. Core MDA standards like UML, MOF, XMI, and CWM define the infrastructure. The vision is for nearly seamless interoperability based on shared metadata and formal model translations, with a long-term goal of adaptive object models that can dynamically interpret models at runtime.
The document provides an overview of information flow processing (IFP) and compares different approaches to complex event processing (CEP). It introduces a functional model for IFP that describes common components like a receiver, decider, producer, and rules. It discusses key aspects that impact expressiveness, such as the selection policy, consumption policy, and ability to handle bursts of input data. The goal is to define modeling frameworks that can accommodate different CEP proposals and technologies.
Introduction to Microsoft SQL Server 2008 R2 Analysis ServiceQuang Nguyễn Bá
The document discusses SQL Server 2008 R2 Analysis Services and provides an overview of its key components including OLAP, multidimensional data analysis using dimensions and hierarchies, and how it utilizes a dimensional data warehouse with fact and dimension tables to store and retrieve data for analysis. It also explains how Analysis Services provides scalable and extensible solutions for analytics and delivers pervasive business insights.
Sodius provides model-driven interoperability solutions to enable data exchange between modeling tools used in systems engineering projects. It has collaborated with Cassidian since 2009 on projects such as developing a solution to migrate architecture models between the MEGA and System Architect tools. Cassidian is working on an Integrated Project Support Environment named IPSE to provide a suite of collaborative system engineering tools integrated using Sodius' MDWorkbench platform.
The document discusses information management and defines it as capturing, storing, managing, preserving, and delivering information. It also discusses cloud platforms, services, types, and provides examples of enterprise services, architectures, methodologies and blueprints for implementing information management solutions.
This talk will provide overview of big data software engineering and software engineering for big data as the tow fields need integrated. The interplay between the two field of research applications of Data Science and Software Engineering will enhance future perspective for a safe, secure, and sustainable approaches to data science and application of data science for 50 years of software engineering data that exists.
Challenges and solutions in Cloud computing for the Future InternetSOFIProject
This document discusses two projects - REMICS and Cloud4Trends - that address challenges in cloud computing. REMICS develops a model-driven methodology for migrating legacy applications to cloud services and addresses interoperability issues. It focuses on providing a domain-specific language for abstracting cloud deployment complexity and solving behavioral and data interoperability. Cloud4Trends leverages cloud infrastructure for real-time trend detection in social media streams, providing a scalable solution for analyzing large-scale data. It detects variations and trends using a cloud computing service developed by the VENUS-C project.
The document discusses software design and implementation. It describes the design phase as involving high-level architectural design to develop the overall structure of a software program, and low-level detailed design to develop specific algorithms and data structures. The implementation phase includes activities like constructing software components, testing, developing prototypes, training, and installing the system. Good design principles include modularity, low coupling between modules, and high cohesion within modules.
Government GraphSummit: And Then There Were 15 StandardsNeo4j
Todd Pihl PhD., Technical Project Mgr. & Mark Jensen, Director of Data Managements and Interoperability, National Institute of Health, Frederick National Labs for Cancer Research
Data repositories such as NCI’s Cancer Research Data Commons receive data that use a variety of data models and vocabularies. This presents a significant obstacle to finding and using the data outside of their original purpose. In this talk we’ll show how using Neo4j allows different data models to be represented and mapped to each other, giving data managers a new way to provide harmonized data to their users.
this presentation covers the following:
* Data warehouse-design strategies
* Data warehouse-modeling techniques
* the points of attention when building ETL-procedures for one of these Data warehouse-modeling techniques
Watch full webinar here: https://buff.ly/2XXbNB7
What started to evolve as the most agile and real-time enterprise data fabric, Data Virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
*What data virtualization really is
*How it differs from other enterprise data integration technologies
*Why data virtualization is finding enterprise wide deployment inside some of the largest organizations
The document discusses a collaboration between SODIUS and CASSIDIAN (EADS Defence & Security) to develop model-driven architecture solutions for supporting systems engineering. It describes a project to enable interchange of data between modeling tools used at CASSIDIAN. The proposed solution uses the NATO Architecture Framework metamodel as a pivot format, with UML diagrams to represent views. Connectors are used to import/export data from tools to the neutral format. A sample migration of models from one tool to another took one week and had mostly complete translation of diagrams and data.
Nuxeo Semantic ECM: from Scribo and Stanbol to valuable applicationsNuxeo
Work on integrating semantic technologies developed in several R&D projects is now progressing at full speed. Expect to see creative new uses of semantic technologies in Nuxeo open source content management products in 2011!
Running head MODEL-BASED SYSTEMS ENGINEERING IMPLEMENTATION 1.docxcowinhelen
Running head: MODEL-BASED SYSTEMS ENGINEERING IMPLEMENTATION 1
Research Project: Model-Based Systems Engineering Implementation
(Name and date withheld)
MODEL-BASED SYSTEMS ENGINEERING IMPLEMENTATION 2
Model-Based Systems Engineering (MBSE) Implementation
Section 1: Requirements Analysis
Section 1 tasks for the MBSE project will identify issues and requirements for
implementing an MBSE system for our Engineering and Systems Integration work.
Problem Definition
Our Engineering department focuses on a niche market of systems engineering, design,
integration, and ongoing maintenance and support of emergency communication and power
systems, predominantly housed in High-Altitude Electromagnetic Pulse (HEMP) protected
mobile environments. The complexity of the integrated voice, data, network, and audio/video
systems we work with, the specialized nature of the work, and the demanding project timelines
have put a strain on our resources and existing processes. We need to leverage common
requirements and design elements across projects and customers while remaining adaptive to
unique and changing customer needs. With people spread across multiple projects, it is harder to
capture changes on one system that should be implemented on others – especially since
requirements and design files are all in separate Word, Excel, Visio and other documents. We
would also like to expand our business to new customers with complex Systems-of-Systems
(SoS) environments that may require protections from HEMP events. To do that, we need to
streamline our processes and reduce redundant work to allow people to reasonably take on
additional projects and make new hires productive on project work more quickly – while
maintaining critical quality factors.
Issues requiring solution. The following list describes the primary issues requiring the
development of an MBSE system for Engineering.
1. Business growth is placing a strain on senior employees with specialized skills
and knowledge.
MODEL-BASED SYSTEMS ENGINEERING IMPLEMENTATION 3
2. System information is contained in a large, diverse set of files (Excel files, Word
documents, Visio diagrams, and CAD files) with no easy way to share technical information.
3. We can’t easily reuse or modify applicable requirements and design elements
between projects. This increases cost and effort of new work.
4. It 's hard to perform change management and assess impacts on a short timeline
across the systems’ lifecycle, again increasing workloads and quality risks.
5. We’re not able to quickly evaluate new customer requirements and designs against
existing systems efficiently, increasing the effort and response time on customer proposals.
6. There is an increasing demand from customers to see architectural views and
interconnecting systems that help them understand the proposed designs.
7. Consistently high workloads cause bottlenecks that slow ...
The document introduces an evolutionary event-driven architecture called the Enterprise Digital Transformation Platform (EDTP) for accelerating digital transformation. The EDTP is a 4-tier platform based on cloud, containers, microservices, events and streaming. It addresses challenges of data integration and decoupling through architectural concepts like event-driven design, microservices and templates. The EDTP provides full-stack deployment automation and microservice templating to accelerate development. Use cases from Toyota Financial Services are presented to demonstrate the EDTP's capabilities.
Data-Blitz is a processing platform that provides high throughput and availability for organizations lacking resources. It uses modern techniques like those used by LinkedIn, Twitter, and others. Data-Blitz allows building, testing, deploying, and managing big data applications at scale across various infrastructure with built-in security, monitoring, and DevOps tools.
This document provides an overview of MongoDB, including what NoSQL databases are, MongoDB features like querying, indexing, replication, load balancing and aggregation. It discusses how MongoDB stores data in documents and collections, can be used for file storage, and is used by many large companies. The document also covers installing and running MongoDB on a local system.
Rando Veizi: Data warehouse and Pentaho suiteCarlo Vaccari
The document provides an overview of installing and exploring tools within the Pentaho business intelligence suite. It describes downloading and configuring the Pentaho server, then explains how to start the BI platform and log into the user console. The Community Dashboard Editor (CDE) and Saiku tools are highlighted as options for creating dashboards and performing analytics within the suite. Data warehouses are also briefly discussed in the context of their relationship with the Pentaho tools for reporting, analysis, and data integration capabilities.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
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.
2. Outline
Introduction and history
CORE objectives
CORE where we are
Architecture implementation
Information model
CORE and SDMX
CORE and GSIM
MSIS Meeting - Luxembourg May 23-25 2011 2
3. CORA ESSnet
Financed by Eurostat under 2009
Statistical Workprogramme
Countries involved: it (coordinator),
ch, dk, lv, nl, no, se
Duration: October 2009 - October
2010
MSIS Meeting - Luxembourg May 23-25 2011 3
4. CORA Technical
Architecture
CORA Model: two dimensions
Functional dimension
Construction dimension
Functional dimension
Adoption of GSBPM 4.0
9 subprocesses of level 2
1
2 3 4 5 6 7 8 9
Specify
Design Build Collect Process Analyse Disseminate Archive Evaluate
Needs
MSIS Meeting - Luxembourg May 23-25 2011 4
5. Construction Dimension:
Layers
A domain of interest documented by
Figures
statistical products
Time Series Statistical series over time
Integrated or simple statistical product for a
Statistic given time
Population A population at a given time
Unit A statistical unit at a given time
Variable A statistical variable at a given time
A logical representation of the value of a
Value
variable
MSIS Meeting - Luxembourg May 23-25 2011 5
6. CORA Model Grid
Statistical processes compliant to CORA model are
intended to be designed by statisticians
MSIS Meeting - Luxembourg May 23-25 2011 6
7. After CORA…CORE!
COmmon Reference Environment (CORE),
financed by Eurostat under 2010
Statistical Workprogramme
Countries involved: it (coordinator), fr, nl,
no, pt, se
Duration: December 2010 - January 2012
MSIS Meeting - Luxembourg May 23-25 2011 7
8. CORE Principal
Outcomes
Environment for the definition and
execution of statistical processes
Definition of a process in terms of
services selected from an available
repository
Execution of the composed workflow
MSIS Meeting - Luxembourg May 23-25 2011 8
9. CORE Outcomes:
Design
CORA model → CORA information
model
Design of CORE services and
processes
MSIS Meeting - Luxembourg May 23-25 2011 9
10. CORE Outcomes:
Implementation
Selection of available middleware solutions for
process execution
Realization of an environment able to permit the
execution of processes:
Interfaces (GUIs) for defining CORE processes for
statistical users
Integration APIs
Repository of integration layers
MSIS Meeting - Luxembourg May 23-25 2011 10
11. CORE Outcomes:
Testing
Realization of processes starting from
services implementing some GSBPM phase
Evaluation of costs related to integration
Prototype implementation (to be
engineered)
MSIS Meeting - Luxembourg May 23-25 2011 11
12. CORE Architecture (1)
GUIs to support modelling of CORE processes
according to the CORA grid
Modeling & control flow constructs
Drag & drop facilities for process design
Global schema
Implementation: we are evaluating the usage of
an open process editor tool (Oryx -
http://bpt.hpi.uni-potsdam.de/Oryx/WebHome )
MSIS Meeting - Luxembourg May 23-25 2011 12
13. CORE Architecture (2)
Process Runtime
Controlled execution of services
Implementation: integration of existing workflow
solutions, currently in evaluation phase
Service Runtime
Integration APIs (in-out data transformation)
Service execution
Implementation: CSV and SQL data
transformations are currently being implemented
Service Repository
Deployment of services
MSIS Meeting - Luxembourg May 23-25 2011 13
14. CORE Information Model (1)
First draft of CORE information model
Del. 2.1 released: requirements for the
model of the interface through which
statistical services will communicate
Information Model to be released,
currently in discussion phase
MSIS Meeting - Luxembourg May 23-25 2011 14
15. CORE Information Model (2)
Design Principles (in discussion):
Rectangular data sets (rows & columns)
Strong typing (data, rules, parameters)
Dataset kinds (eg micro/aggreg)
Free-style arguments (eg scripts tool
dependent)
Other (service arguments and infos)
MSIS Meeting - Luxembourg May 23-25 2011 15
16. CORE and SDMX
Both initiatives foster standardization
CORE
Focus on standardization of processes and data
exchanges (mainly) intra-NSI
SDMX
Focus on standardization of processes and data
exchanges (mainly) inter-NSIs (or between NSIs
and international organizations)
MSIS Meeting - Luxembourg May 23-25 2011 16
17. CORE and SDMX - 2
CORE
Focus on all phases of statistical processes
Both micro and macro data considered
SDMX
Focus (mainly) on dissemination phase
Mainly macro data considered
MSIS Meeting - Luxembourg May 23-25 2011 17
18. Information Model
Both propose an information model
CORE information model
Takes explicitly process dimension into account
through GSBPM
Data dimension
SDMX information model
Mainly focused on data dimension
MSIS Meeting - Luxembourg May 23-25 2011 18
19. CORA Information
Model
Service +belongs_to Layer
level
+contains
1
+implements +belongs_to
n
Constructor
prescript +has
+input Element
n
n
output.belongs_to.level =
input.belongs_to.level + 1 +output n
Construct Object
+represented_by
1
Figure Time series Statistic Population Unit Variable
MSIS Meeting - Luxembourg May 23-25 2011 19
20. SDMX Data & Metadata Information
Model
Data or Metadata
Structure
Definition
uses specific
data or
metadata can have child
structure categories
can be linked with
Data or Data or categories from multiple
category schemes
Metadata Metadata Category
Set conforms to business Flow
rules of the data or
metadata flow comprised
can get data of subject
from multiple or reporting
data providers categories
Data Provision Category
Provider Agreement Scheme
MSIS Meeting - Luxembourg May 23-25 2011 20
21. On Information Models
Different abstraction levels
CORE
“Higher” modelling level
E.g.: statistics as tabular data
SDMX
“Lower” modeling level
E.g.: aggregated data set with dimensions, attributes
and measures
MSIS Meeting - Luxembourg May 23-25 2011 21
22. Open Issues - 1
Can we use SDMX for micro and macro
data exchanges in a CORE process?
Need for mapping of information
models
MSIS Meeting - Luxembourg May 23-25 2011 22
23. On-Going Work - 1
CORE implementation scenario within
Istat
Main phases: Sample selection and
allocation
CORE wrapping of available SAS and
R procedures
MSIS Meeting - Luxembourg May 23-25 2011 23
24. On-Going Work - 2
Design and implementation of CORE
Integration APIs
Possible in/out SDMX translations
CORE TOOL
SDMX IAPI TOOL IAPI SDMX
MSIS Meeting - Luxembourg May 23-25 2011 24
25. Open Issues - 2
What about metadata?
CORE: Data and metadata managed in the
same way
SDMX:
Distinction between structural metadata and
reference metadata
Dedicated effort for metadata management
MSIS Meeting - Luxembourg May 23-25 2011 25
26. Collaboration between
CORE/SDMX ESSnets
CORE planned deliverable on “Feedbacks
on SDMX Usage in CORE”
Periodical meetings inside Istat between
coordinators of the two ESSnets
Exchanges of resources between the two
ESSnets
MSIS Meeting - Luxembourg May 23-25 2011 26
27. CORE and GSIM
GSIM: Generic Statistical Information Model
deliverable from OCMIMF Operationalising a
Common Metadata/Information Management
Framework activity inside Statistical Network
Ambiguity on the acronym: reference to
“generic statistical information model” in CORE
ESSnet proposal
In March started activity to clarify relationships
(thanks to J.P.Kent and A.Hamilton)
MSIS Meeting - Luxembourg May 23-25 2011 27
28. CORE and GSIM
First analysis and discussions: the deliverables
from the two initiatives are complementary in
intent and do not overlap in concept
Necessary to avoid gaps and/or duplications
and ensure the complementary relationship
MSIS Meeting - Luxembourg May 23-25 2011 28
29. CORE Information
Model
CORE will define a very generic information model
(CORE-IM) for the interface through which statistical
services will communicate with each other within
the framework of the CORA model
As a communication protocol, CORE-IM focuses on
the “postal envelope” used when passing
information between services, rather than focusing
in detail on the information being communicated (ie
what is inside)
MSIS Meeting - Luxembourg May 23-25 2011 29
30. CORE and GSIM
CORE-IM current hypothesis: to support a flag to
indicate if the information being communicated is
described within GSIM
→ without claiming to align the semantics of the
content (eg, “classification”), but only to alert a
consuming service which “understands” GSIM that
it can relate the content to GSIM
MSIS Meeting - Luxembourg May 23-25 2011 30
31. Complementary nature
CORE-IM supporting semantic interoperability at a
very high, abstract level (“here is an information
object, along with the ‘envelope’ information about
it”) where GSIM can provide greater semantic
precision to a subset of information objects
communicated using CORE
CORE supporting communication between services
→ substantial interoperability benefits
Information aligned with GSIM semantics
MSIS → further level of interoperability
Meeting - Luxembourg May 23-25 2011 31
32. Complementary nature
GSBPM reference model for statistical business
processes
GSIM reference model for information input to, used
by and produced by those processes
Models are independent → it's possible to use one
without the other
CORE-IM recognizes and uses GSBPM and (hopefully)
will do the same with regard to GSIM, giving them a
potential contact point
MSIS Meeting - Luxembourg May 23-25 2011 32
33. Coordination in
practice
Need to maximize the extent to which these
synergies are achieved in practice:
Members in common (no, se)
ABS leader for the OCMIMF and observer in CORE
CORE members external reviewers for GSIM
material
CORE WP2 “co-ordination input” from the OCMIMF
collaboration team in regard to deliverables
Half day session at METIS workshop (October)
presenting CORE and OCMIMF works to external
metadata specialists
Common documents in preparation
...
MSIS Meeting - Luxembourg May 23-25 2011 33