The document provides an introduction to the European Open Science Cloud (EOSC). It defines key concepts like open science, FAIR data, and explains what EOSC is - a federated infrastructure to support open sharing and reuse of research outputs across disciplines. It outlines EOSC's goals like enabling multidisciplinary discovery and connecting previously disconnected research resources and data silos. Examples of current EOSC services and resources available via the EOSC Portal are also briefly described.
European Open Science Cloud architecture future viewJisc
This online European Open Science Cloud (EOSC) event was held on 15 December 2021.
You’ll get information about:
- Developments in the EOSC Association
- The work of the new EOSC Advisory Groups and Task Forces
- What’s happening in some of the EOSC implementation projects
- Ways you can become involved in EOSC
An overview on FAIR Data and FAIR Data stewardship, and the roadmap for FAIR Data solutions coordinated by the Dutch Techcentre for Life Sciences. This presentation was given at the Netherlands eScience Center's "Essential skills in data-intensive research" course week.
CKAN is a powerful data management system that makes data accessible – by providing tools to streamline publishing, sharing, finding and using data. CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available.
Presented at the Open Science Fair, Athens 6-8 September 2017, at the FOSTER Plus "Fostering the practical implementation of Open Science in Horizon 2020 and beyond" workshop http://www.opensciencefair.eu/training/parallel-day-2-2/fostering-the-practical-implementation-of-open-science-in-horizon-2020-and-beyond
FOOPS!: An Ontology Pitfall Scanner for the FAIR principlesdgarijo
Slides presented at the DBpedia Day, at the Semantcis conference in 2021. FOOPS! (available at https://w3id.org/foops) is a validator based on the FAIR principles that will guide users when conforming their ontologies to them. For each principle, FOOPS! runs a series of tests and notifies errors, suggestions and ways to conform to the best practices.
European Open Science Cloud architecture future viewJisc
This online European Open Science Cloud (EOSC) event was held on 15 December 2021.
You’ll get information about:
- Developments in the EOSC Association
- The work of the new EOSC Advisory Groups and Task Forces
- What’s happening in some of the EOSC implementation projects
- Ways you can become involved in EOSC
An overview on FAIR Data and FAIR Data stewardship, and the roadmap for FAIR Data solutions coordinated by the Dutch Techcentre for Life Sciences. This presentation was given at the Netherlands eScience Center's "Essential skills in data-intensive research" course week.
CKAN is a powerful data management system that makes data accessible – by providing tools to streamline publishing, sharing, finding and using data. CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available.
Presented at the Open Science Fair, Athens 6-8 September 2017, at the FOSTER Plus "Fostering the practical implementation of Open Science in Horizon 2020 and beyond" workshop http://www.opensciencefair.eu/training/parallel-day-2-2/fostering-the-practical-implementation-of-open-science-in-horizon-2020-and-beyond
FOOPS!: An Ontology Pitfall Scanner for the FAIR principlesdgarijo
Slides presented at the DBpedia Day, at the Semantcis conference in 2021. FOOPS! (available at https://w3id.org/foops) is a validator based on the FAIR principles that will guide users when conforming their ontologies to them. For each principle, FOOPS! runs a series of tests and notifies errors, suggestions and ways to conform to the best practices.
FAIRy stories: the FAIR Data principles in theory and in practiceCarole Goble
https://ucsb.zoom.us/meeting/register/tZYod-ippz4pHtaJ0d3ERPIFy2QIvKqjwpXR
FAIRy stories: the FAIR Data principles in theory and in practice
The ‘FAIR Guiding Principles for scientific data management and stewardship’ [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the army of authors). Over the past 5 years FAIR has become a movement, a mantra and a methodology for scientific research and increasingly in the commercial and public sector. FAIR is now part of NIH, European Commission and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need”.
As a data infrastructure wrangler I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-lead approaches like Schema.org; work with big pharma on specialised FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.
In this talk I’ll use some of these projects to shine some light on the FAIR movement. Spoiler alert: although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role – not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”
[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
For a country like Finland, which is full of innovations and startups, Gaia-X is a gateway for reaching the next step of the data economy ladder. The potential of this groundbreaking initiative is enormous and far-reaching.
Gaia-X is the answer to a massive demand for safe, secure and sovereign data across Europe. By merging hundreds of different organisations in different domain and from across the globe in a single endeavour, Gaia-X combines challenging use cases with innovative solutions to bring the most value out of the European data economy.
Gaia-X project is accelerating rapidly with the launch of Gaia-X regional hubs. We are pleased to invite you to our Gaia-X for Finland – Hub launch event.
During the event, you will learn about the role of a Gaia-X as a game-changer for data-driven businesses, hear about the strategy and operational model of the Finnish Gaia-X Hub and get insights from companies already involved in Gaia-X.
The event page: https://www.sitra.fi/en/events/gaia-x_for_finland_hub_launch/
Presentations:
Jaana Sinipuro, Project Director, Sitra
Hubert Tardieu, Independent Board Member in charge of relationship with governments
Lars Albäck, CEO, Vastuu Group
FAIR Workflows and Research Objects get a Workout Carole Goble
So, you want to build a pan-national digital space for bioscience data and methods? That works with a bunch of pre-existing data repositories and processing platforms? So you can share FAIR workflows and move them between services? Package them up with data and other stuff (or just package up data for that matter)? How? WorkflowHub (https://workflowhub.eu) and RO-Crate Research Objects (https://www.researchobject.org/ro-crate) that’s how! A step towards FAIR Digital Objects gets a workout.
Presented at DataVerse Community Meeting 2021
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
Introduction to the cutting-edge end-user (software) development, RIA and semantic technologies to offer a next-generation end-user centred web application mashup platform through FIWARE WireCloud.
- Learn to understand what knowledge graphs are for
- Understand the structure of knowledge graphs (and how it relates to taxonomies and ontologies)
- Understand how knowledge graphs can be created using manual, semi-automatic, and fully automatic methods.
- Understand knowledge graphs as a basis for data integration in companies
- Understand knowledge graphs as tools for data governance and data quality management
- Implement and further develop knowledge graphs in companies
- Query and visualize knowledge graphs (including SPARQL and SHACL crash course)
- Use knowledge graphs and machine learning to enable information retrieval, text mining and document classification with the highest precision
- Develop digital assistants and question and answer systems based on semantic knowledge graphs
- Understand how knowledge graphs can be combined with text mining and machine learning techniques
- Apply knowledge graphs in practice: Case studies and demo applications
University of Liverpool Researcher KnowHow session presented by Judith Carr.
At the end of this session you will know what the FAIR data principles are, what is required and be in a position to think how these would relate to your research practice.
La Oficina del Dato y los espacios de datosDatos.gob.es
Presentación realizada con motivo de la semana de la Administración Abierta 2022. Descubre cuáles es la misión de la Oficina del Dato y cómo puede intervenir para favorecer la compartición de datos como medio para impulsar la economía del dato.
FAIRy stories: the FAIR Data principles in theory and in practiceCarole Goble
https://ucsb.zoom.us/meeting/register/tZYod-ippz4pHtaJ0d3ERPIFy2QIvKqjwpXR
FAIRy stories: the FAIR Data principles in theory and in practice
The ‘FAIR Guiding Principles for scientific data management and stewardship’ [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the army of authors). Over the past 5 years FAIR has become a movement, a mantra and a methodology for scientific research and increasingly in the commercial and public sector. FAIR is now part of NIH, European Commission and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need”.
As a data infrastructure wrangler I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-lead approaches like Schema.org; work with big pharma on specialised FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.
In this talk I’ll use some of these projects to shine some light on the FAIR movement. Spoiler alert: although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role – not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”
[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
For a country like Finland, which is full of innovations and startups, Gaia-X is a gateway for reaching the next step of the data economy ladder. The potential of this groundbreaking initiative is enormous and far-reaching.
Gaia-X is the answer to a massive demand for safe, secure and sovereign data across Europe. By merging hundreds of different organisations in different domain and from across the globe in a single endeavour, Gaia-X combines challenging use cases with innovative solutions to bring the most value out of the European data economy.
Gaia-X project is accelerating rapidly with the launch of Gaia-X regional hubs. We are pleased to invite you to our Gaia-X for Finland – Hub launch event.
During the event, you will learn about the role of a Gaia-X as a game-changer for data-driven businesses, hear about the strategy and operational model of the Finnish Gaia-X Hub and get insights from companies already involved in Gaia-X.
The event page: https://www.sitra.fi/en/events/gaia-x_for_finland_hub_launch/
Presentations:
Jaana Sinipuro, Project Director, Sitra
Hubert Tardieu, Independent Board Member in charge of relationship with governments
Lars Albäck, CEO, Vastuu Group
FAIR Workflows and Research Objects get a Workout Carole Goble
So, you want to build a pan-national digital space for bioscience data and methods? That works with a bunch of pre-existing data repositories and processing platforms? So you can share FAIR workflows and move them between services? Package them up with data and other stuff (or just package up data for that matter)? How? WorkflowHub (https://workflowhub.eu) and RO-Crate Research Objects (https://www.researchobject.org/ro-crate) that’s how! A step towards FAIR Digital Objects gets a workout.
Presented at DataVerse Community Meeting 2021
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
Introduction to the cutting-edge end-user (software) development, RIA and semantic technologies to offer a next-generation end-user centred web application mashup platform through FIWARE WireCloud.
- Learn to understand what knowledge graphs are for
- Understand the structure of knowledge graphs (and how it relates to taxonomies and ontologies)
- Understand how knowledge graphs can be created using manual, semi-automatic, and fully automatic methods.
- Understand knowledge graphs as a basis for data integration in companies
- Understand knowledge graphs as tools for data governance and data quality management
- Implement and further develop knowledge graphs in companies
- Query and visualize knowledge graphs (including SPARQL and SHACL crash course)
- Use knowledge graphs and machine learning to enable information retrieval, text mining and document classification with the highest precision
- Develop digital assistants and question and answer systems based on semantic knowledge graphs
- Understand how knowledge graphs can be combined with text mining and machine learning techniques
- Apply knowledge graphs in practice: Case studies and demo applications
University of Liverpool Researcher KnowHow session presented by Judith Carr.
At the end of this session you will know what the FAIR data principles are, what is required and be in a position to think how these would relate to your research practice.
La Oficina del Dato y los espacios de datosDatos.gob.es
Presentación realizada con motivo de la semana de la Administración Abierta 2022. Descubre cuáles es la misión de la Oficina del Dato y cómo puede intervenir para favorecer la compartición de datos como medio para impulsar la economía del dato.
Data Science: History repeated? – The heritage of the Free and Open Source GI...Peter Löwe
Data Science is described as the process of knowledge extraction from large data sets by means of scientific
methods. The discipline draws heavily from techniques and theories from many fields, which are jointly used to
furthermore develop information retrieval on structured or unstructured very large datasets. While the term Data
Science was already coined in 1960, the current perception of this field places is still in the first section of the hype cycle according to Gartner, being well en route from the technology trigger stage to the peak of inflated
expectations.
In our view the future development of Data Science could benefit from the analysis of experiences from
related evolutionary processes. One predecessor is the area of Geographic Information Systems (GIS). The
intrinsic scope of GIS is the integration and storage of spatial information from often heterogeneous sources, data
analysis, sharing of reconstructed or aggregated results in visual form or via data transfer. GIS is successfully
applied to process and analyse spatially referenced content in a wide and still expanding range of science
areas, spanning from human and social sciences like archeology, politics and architecture to environmental and
geoscientific applications, even including planetology.
This paper presents proven patterns for innovation and organisation derived from the evolution of GIS,
which can be ported to Data Science. Within the GIS landscape, three strategic interacting tiers can be denoted: i) Standardisation, ii) applications based on closed-source software, without the option of access to and analysis of the implemented algorithms, and iii) Free and Open Source Software (FOSS) based on freely accessible program code enabling analysis, education and ,improvement by everyone. This paper focuses on patterns gained from the synthesis of three decades of FOSS development. We identified best-practices which evolved from long term FOSS projects, describe the role of community-driven global umbrella organisations such as OSGeo, as well as the standardization of innovative services. The main driver is the acknowledgement of a meritocratic attitude.
These patterns follow evolutionary processes of establishing and maintaining a web-based democratic culture
spawning new kinds of communication and projects. This culture transcends the established compartmentation and
stratification of science by creating mutual benefits for the participants, irrespective of their respective research
interest and standing. Adopting these best practices will enable
Gergely Sipos (EGI): Exploiting scientific data in the international context ...Gergely Sipos
Keynote presentation given at "The Emerging Technology Forum – Data Creates Universe - Scientific Data Innovation Conference" of the "Pujiang Innovation Forum 2021" event.
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...Carole Goble
https://datascience.nih.gov/news/march-data-sharing-and-reuse-seminar 11 March 2022
Starting in 2023, the US National Institutes of Health (NIH) will require institutes and researchers receiving funding to include a Data Management Plan (DMP) in their grant applications, including the making their data publicly available. Similar mandates are already in place in Europe, for example a DMP is mandatory in Horizon Europe projects involving data.
Policy is one thing - practice is quite another. How do we provide the necessary information, guidance and advice for our bioscientists, researchers, data stewards and project managers? There are numerous repositories and standards. Which is best? What are the challenges at each step of the data lifecycle? How should different types of data? What tools are available? Research Data Management advice is often too general to be useful and specific information is fragmented and hard to find.
ELIXIR, the pan-national European Research Infrastructure for Life Science data, aims to enable research projects to operate “FAIR data first”. ELIXIR supports researchers across their whole RDM lifecycle, navigating the complexity of a data ecosystem that bridges from local cyberinfrastructures to pan-national archives and across bio-domains.
The ELIXIR RDMkit (https://rdmkit.elixir-europe.org (link is external)) is a toolkit built by the biosciences community, for the biosciences community to provide the RDM information they need. It is a framework for advice and best practice for RDM and acts as a hub of RDM information, with links to tool registries, training materials, standards, and databases, and to services that offer deeper knowledge for DMP planning and FAIR-ification practices.
Launched in March 2021, over 120 contributors have provided nearly 100 pages of content and links to more than 300 tools. Content covers the data lifecycle and specialized domains in biology, national considerations and examples of “tool assemblies” developed to support RDM. It has been accessed by over 123 countries, and the top of the access list is … the United States.
The RDMkit is already a recommended resource of the European Commission. The platform, editorial, and contributor methods helped build a specialized sister toolkit for infectious diseases as part of the recently launched BY-COVID project. The toolkit’s platform is the simplest we could manage - built on plain GitHub - and the whole development and contribution approach tailored to be as lightweight and sustainable as possible.
In this talk, Carole and Frederik will present the RDMkit; aims and context, content, community management, how folks can contribute, and our future plans and potential prospects for trans-Atlantic cooperation.
Data policy must be partnered with data practice. Our researchers need to be the best informed in order to meet these new data management and data sharing mandates.
Presentation investigating the state of FAIR practice and what is needed to turn FAIR data into reality given at the Danish FAIR conference in Copenhagen on 20th November 2018. https://vidensportal.deic.dk/en/Programme/FAIR_Toolbox_Nov2018 The presentation reflect on recent FAIR studies and international initiatives and outlines the recommendations emerging from the European Commission's FAIR Data Expert Group report - http://tinyurl.com/FAIR-EG
The Ascent of Open Science and the European Open Science CloudTiziana Ferrari
Open science is becoming more and more part of the daily practice in conducting science. Around the world, researchers are increasingly aware of the value and importance of open science. As scientific research becomes highly data-driven and dependent on computing, scientists are conscious of the growing need to share data, software and infrastructure to reduce wasteful duplication and increase economies of scale. In an ideal world, every step of the research process would be public and transparent – the full methodology and all the tools used, as well as the data, would be accessible to the public and all groups without restriction, enabling reproducibility and refinement by other scientists.
This presentation will show case a number of success stories indicating how federated digital infrastructure, that have been sustained by the member states and the European Commission, have become an indispensable tool to enable collaboration ad sharing.
The European Open Science Cloud was launched by the European Commission in 2016 aiming to (1) increase the ability to exploit research data across scientific disciplines and between the public and private sector, (2) interconnect existing and new digital infrastructures in Europe and (3) support open science.
The presentation showcases how open data, open data analytics and open e-Infrastructures like EGI (https://www.egi.eu/) have been key enables of scientific discoveries from the discovery of gravitational waves with LIGO-VIRGO to drug design with the molecular modelling tools of WeNMR.
EOSC-hub (https://www.eosc-hub.eu/) - the first and the largest of the EOSC implementation projects of the H2020 funding programme, has succeeded in delivering some of the building blocks like the EOSC portal and Marketplace, tools and processes for federating data and services providers, harmonized policies, a federated AAI infrastructure, Competence Centres to support research infrastructures in their complex digital needs, interoperability guidelines and the Early Adopter Programme to provide expert support and service capacity to research projects.
The European Open Science Cloud: just what is it?Carole Goble
Presented at Jisc and CNI leaders conference 2018, 2 July 2018, Oxford, UK (https://www.jisc.ac.uk/events/jisc-and-cni-leaders-conference-02-jul-2018). The European Open Science Cloud. What exactly is it? In principle it is conceived as a virtual environment with open and seamless services for storage, management, analysis and re-use of research data, across borders and scientific disciplines. How? By federating existing scientific data infrastructures, currently dispersed across disciplines and Member States. In practice, what it is depends on the stakeholder. To European Research Infrastructures it’s a coordinated mission to organise and exchange their data, metadata, software and services to be FAIR – Findable, Accessible, Interoperable, Reusable – and to use e-Infrastructures, either EU or commercial. To EU e-Infrastructures offering data storage and cloud services, it’s a funding mission to integrate their services, policies and organisational structures, and to be used by the Research Infrastructures. To agencies it’s a means to promote Open Science, standardisation, cross-disciplinary research and coordinated investment with a dream of a “one stop shop” for researchers. And for Libraries?
Cloud Computing Needs for Earth Observation Data Analysis: EGI and EOSC-hubBjörn Backeberg
This presentation was given during the Japan Geosciences Union 2019. Session details can be found at http://www.jpgu.org/meeting_e2019/SessionList_en/detail/M-GI31.htm
NORFest 2023 Lightning Talks Session Three dri_ireland
Lightning Talk Session 3: Enabling FAIR Research Data and Other Outputs
The Irish ORCID Consortium
presented by Catherine Ferris, IReL;
Exploring Large-Scale Open Data: The Curatr Platform
presented by Derek Greene, University College Dublin;
A Workflow for Research Data Management (RDM): Aligning the Management of Research Data
presented by Gail Birkbeck, University College Dublin;
Making Cultural Heritage Data FAIR: Developing Recommendations for the WorldFAIR Project at the Digital Repository of Ireland
presented by Joan Murphy, Digital Repository of Ireland.
European Open Science Cloud: Concept, status and opportunitiesEOSC-hub project
European Open Science Cloud: Concept, status and opportunities.
Presentation given by Gergely Sipos at the International Symposium on Grids and Clouds 2019 event in Taiwan.
Keynote presentation given at the Data Fellows 2023 workshop in Berlin on 22-23 June. Presentation gives examples of good communication to explain data management concepts and how to use games and other forms of interactivity in training events
Presentation given at the DMPonline 10 year anniversary week, reflecting on lessons learned developing the business model. See https://www.dcc.ac.uk/events/dmponline-10th-year-anniversary-celebration-week and #10yearsDMPonline
Keynote presentation given at the 10th anniversary of the 4TU.researchdata repository https://data.4tu.nl/info/en/news-events/training-events/news-item/4turesearchdatas-role-in-fostering-open-science-10th-anniversary-celebration-29-sep-2020-1530-1730-c/
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
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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
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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
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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.
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/
1. www.geant.org
www.geant.org
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Click to edit Master title style
• Click to edit Master text styles
• Second level
• Third level
• Fourth level
• Fifth level
06/04/2022 1
Introduction to EOSC
www.geant.org
Sarah Jones
EOSC Engagement Manager
sarah.jones@geant.org
Twitter: @sarahroams
Module 5 – Future Perspectives in Research
18th March 2020
5. www.geant.org
www.geant.org
“science carried out and communicated in a manner which
allows others to contribute, collaborate and add to the research
effort, with all kinds of data, results and protocols made freely
available at different stages of the research process.”
Research Information Network, Open Science case studies
www.rin.ac.uk/our-work/data-management-and-curation/
open-science-case-studies
Defining Open Science
5 |
6. www.geant.org
www.geant.org
• FAIR ≠ Open
• FAIR ensures data can be found, understood and reused
• Data can be shared under restrictions & still be FAIR
"As open as possible, as closed as necessary"
And what is FAIR?
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Image CC-BY-SA by SangyaPundir Image CC-BY by European Commission FAIR data expert group
7. www.geant.org
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• EC and Member States committed to FAIR and Open
• Pursue this in research policy and grant conditions
• Lots of investment in infrastructure to support data sharing
• Ultimately supports the science ecosystem and ensures
greater return on investment
FAIR and Open both central to EOSC
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10. www.geant.org
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• A web of FAIR data and services
• Federation of eInfra and Research
Infrastructures (RIs)
• Environment in which data can be
brought together with services to
perform analyses and address
societal challenges
The EOSC platform
12. www.geant.org
www.geant.org
FAIR is central to principles in EOSC
• Is the glue that connects data & services
• Requirement for FAIR to support reuse
• Use community standards
• Share all types of output (openly)
13. www.geant.org
www.geant.org
Align with European Partnerships & data spaces
The nine European Common
Data Spaces: Hybrid Public
and Private Data
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9. Skills data
space
7. Agricultural
data space
8. Data spaces
for public
administrations
6. Energy
data space
5. Financial
data space
1. Industrial
(manufacturing)
data
4. Health
data
space
2. Green Deal
data space
3. Mobility
data space
National
Private and
Public data
EOSC
15. Main aims of EOSC Future
• The realisation of EOSC-Core and EOSC Exchange
with interoperable data and resources
• The integration of data and resources from the
science clusters into the EOSC Platform
• The direct involvement of users in the co-design
and implementation of the EOSC Portal
• Briging together eInfra and RIs to achieve this
https://eoscfuture.eu
16. www.geant.org
www.geant.org
• CSA run by EOSC Association
• Will operate a stakeholder forum
• Run project coordination events
• Host consultations on the SRIA updates
• National country day workshops
• Researcher engagement activities
• Annual EOSC Symposium
• ….
EOSC Focus project (forthcoming)
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18. Long history of political agreements and activity
Lots of groundwork since 2015
• Council Conclusions
• Expert Group reports
• EC documents
• Major investment in EOSC
related projects to develop the
infrastructure and platform
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www.geant.org
• The shared vision between the EC, MS&AC and a large community
• The decision of the governing bodies to institute a Co-programmed
Partnership as the best instrument to collectively achieve this vision
Where does the current governance come from?
19
20. www.geant.org
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Executive and Governance Boards
from 2018-2020
Changing governance of EOSC
https://eoscsecretariat.eu/eosc-governance/eosc-executive-board
EOSC Association and European
Partnership from 2020 onwards
https://www.eosc.eu
21. www.geant.org
www.geant.org
• Three-party collaboration
• Partnership MOU between EC and
EOSC Association
• Representation of Member States &
Associated Countries involved in
Horizon Europe in Steering Board
• EOSC Association represents
stakeholder community at large via
its membership
Governance model 2021-27
21
EOSC
Association
Steering
Board
European
Commission
Joining the EOSC Association
=
Joining the EOSC Partnership!
22. EOSC Association membership
22
• 234 organisations of which 161 are full members and 73 observers
• Mostly research performing and service providers
• Good geographic coverage, strongest in Western Europe
25. www.geant.org
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• Currently the primary resource for
navigating EOSC
• https://eosc-portal.eu
• Includes a virtual tour for new users
• Catalogue and marketplace is how
you discover, access and compose
resources
EOSC Portal
27. Access to free storage, compute and support services
C-SCALE will federate compute
and data resources from the
Copernicus DIAS, the national
Collaborative Ground
Segments and the European
Open Science Cloud (EOSC)
towards a European open
source Big (Copernicus) Data
Analytics platform:
- Storage services: up to 12 PB
- Cloud services: up to
17,728,500 CPU hours
- HPC/HTC services: up to
3,100,000 CPU hours
- GPU services: up to 6,000
GPU hours
DICE makes available a set of
data management services (and
associated resources) for
researchers and research
communities from any scientific
domain including:
- Data archives (up to 25 PB)
- Policies based data archives (up
to 17 PB)
- Personal and project
workspaces (up to 5 PB)
- Data repository services for
data sharing (up to 8 PB)
- Data discovery services (with
PID and DOI services and
metadata harvesting)
EGI-ACE will deliver the EOSC
Compute Platform and will
contribute to the EOSC Data
Commons. Services offered
include: compute and storage
resources, compute platform
services, data management
services and related user support
and training.
The total capacity that EGI-ACE
makes available through the call
between 2021-2023 is:
- 80,000,000 CPU hours
- 250,000 GPU hours
- 20 PB storage
support to Argos DMP service by
drafting discipline specific DMPs,
Horizon Europe DMP support
set your own community
research gateway
(connect.openaire.eu) and
Zenodo communities
access open science metrics for
your projects, institution,
community
service to anonymise your data
and comply with GDPR
support and mentoring on
Horizon Europe open access
mandates
Provides three core services for
Research Lifecycle Management:
- ROHub: tool to facilitate the
exchange of information across the
scientific community.
- Text Enrichment and Mining:
service which automatically extracts
valuable information and metadata
from bibliographic sources and
other text documents
- Datacube technology for Earth
Observation (EO) data
management: efficient access to
extensive collections of multi-
temporal and multi-dimensional EO
imagery, also allowing
interoperability among the different
information layers.
https://marketplace.eosc-portal.eu
29. Improved cross-catalogue discovery
(mock-up – forthcoming work)
As more community
catalogues are integrated
into EOSC, greater search
and discovery functionality
will be provided
30. www.geant.org
www.geant.org
EOSC Future is using AI techniques to make recommendations to users:
• relevant projects, data, publications, training materials
• potential collaborators (people, task forces, communities)
Recommendations based on
• viewing history
• order history
• general popularity
• popularity among users with
a similar background/interests
Recommendations for users
31. www.geant.org
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• Federated identity management – ease of single sign on
• Access to a greater number of services
• Funding provided to pay for compute e.g. EGI-ACE, DICE
• Discovery of related data from other disciplines / sectors
• Greater ability to collaborate and address key research
questions
Benefits of EOSC for researchers
31