Presentation given by Krysztof Janowicz and Pascal Hitzler in the afternoon Architecture Forum Session on Day 1, June 24, at the EarthCube All-Hands Meeting.
“Semantic Technologies for Smart Services” diannepatricia
Rudi Studer, Full Professor in Applied Informatics at the Karlsruhe Institute of Technology (KIT), Institute AIFB, presentation “Semantic Technologies for Smart Services” as part of the Cognitive Systems Institute Speaker Series, December 15, 2016.
A presentation based on a published paper "The Ambiguity of Data Science Team Roles and the Need for a Data Science Workforce Framework" by Jeffrey S. Saltz and Nancy W. Grady.
Fair webinar, Ted slater: progress towards commercial fair data products and ...Pistoia Alliance
Elsevier is a global information analytics business that helps institutions and professional’s
advance healthcare and open science to improve performance for the benefit of humanity.
In this webinar, we discuss how Elsevier is increasingly leveraging the FAIR Guiding Principles to improve its products and services to better serve the scientific community.
“Semantic Technologies for Smart Services” diannepatricia
Rudi Studer, Full Professor in Applied Informatics at the Karlsruhe Institute of Technology (KIT), Institute AIFB, presentation “Semantic Technologies for Smart Services” as part of the Cognitive Systems Institute Speaker Series, December 15, 2016.
A presentation based on a published paper "The Ambiguity of Data Science Team Roles and the Need for a Data Science Workforce Framework" by Jeffrey S. Saltz and Nancy W. Grady.
Fair webinar, Ted slater: progress towards commercial fair data products and ...Pistoia Alliance
Elsevier is a global information analytics business that helps institutions and professional’s
advance healthcare and open science to improve performance for the benefit of humanity.
In this webinar, we discuss how Elsevier is increasingly leveraging the FAIR Guiding Principles to improve its products and services to better serve the scientific community.
It seems that AI is also becoming a buzzword, like design thinking. Everyone is talking about AI or wants to have AI, and sees all the ideas and benefits – that’s fine, but how do you get started? But what’s different now? Three innovations have finally put AI on the fast track: Big Data, with the internet and sensors everywhere; massive computing power, especially through the Cloud; and the development of breakthrough algorithms, so computers can be trained to accomplish more sophisticated tasks on their own with deep learning. If you use new technology, you need to explore and know what’s possible. With design thinking, it aids to outline the steps and define the ways in which you’re going to create the solution. Starting with mapping the customer journey, defining who will be using that service enhanced with intelligent technology, or who will benefit and gain value from it. We discuss how these two worlds are coming together, and how you get started to transform your venture with Artificial Intelligence using Design Thinking.
Speaker: Claudio Mirti, Principal Solution Specialist – Data & AI, Microsoft
PA webinar on benefits & costs of FAIR implementation in life sciences Pistoia Alliance
The slides from the Pistoia Alliance Debates Webinar where a panel of experts from technology support providers and the biopharma industry, who have been invited to share their views on the "Benefits and costs of FAIR Implementation for life science industry".
Knowledge graphs ilaria maresi the hyve 23apr2020Pistoia Alliance
Data for drug discovery and healthcare is often trapped in silos which hampers effective interpretation and reuse. To remedy this, such data needs to be linked both internally and to external sources to make a FAIR data landscape which can power semantic models and knowledge graphs.
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Can we use data to train Machine Learning models, perform statistical analysis, yet without putting private data on risk? There are tools and techniques such as Federated Learning, Differential Privacy or Homomorphic Encryption enabling safer work on the data.
Introduction to research data management. Presented by Natasha Simons at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management, Melbourne 31st may 2018
How to get there from here- Research data Managment training. presented by Sue Cook, CSIRO, at the C3DIS post conference workshop; Managed data – trusted research: an introduction to Research Data Management in Melbourne 31st May 2018
FAIR - Working Data - It's not just about FAIR publishing. Presented by John Morrissey from CSIRO at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management 31 may 2018 in Melbourne
The Rensselaer Institute for Data Exploration and Applications is addressing new modes of data exploration and integration to enhance the work of campus researchers (and beyond). This talk outlines the "data exploration" technologies being explored
OCWC Global 2009 Solving The OER Discovery Problem The DiscoverEd PrototypeAhrash Bissell
Brief presentation describing one perspective on the challenge of improving the "discoverability" of (open) educational resources, and details regarding our prototype (DiscoverEd) which may help us in this effort.
The webinar explores some of the current opportunities for AI within Life Science and look ahead to what we can expect to see over the coming years. These are the accompanying slides.
It seems that AI is also becoming a buzzword, like design thinking. Everyone is talking about AI or wants to have AI, and sees all the ideas and benefits – that’s fine, but how do you get started? But what’s different now? Three innovations have finally put AI on the fast track: Big Data, with the internet and sensors everywhere; massive computing power, especially through the Cloud; and the development of breakthrough algorithms, so computers can be trained to accomplish more sophisticated tasks on their own with deep learning. If you use new technology, you need to explore and know what’s possible. With design thinking, it aids to outline the steps and define the ways in which you’re going to create the solution. Starting with mapping the customer journey, defining who will be using that service enhanced with intelligent technology, or who will benefit and gain value from it. We discuss how these two worlds are coming together, and how you get started to transform your venture with Artificial Intelligence using Design Thinking.
Speaker: Claudio Mirti, Principal Solution Specialist – Data & AI, Microsoft
PA webinar on benefits & costs of FAIR implementation in life sciences Pistoia Alliance
The slides from the Pistoia Alliance Debates Webinar where a panel of experts from technology support providers and the biopharma industry, who have been invited to share their views on the "Benefits and costs of FAIR Implementation for life science industry".
Knowledge graphs ilaria maresi the hyve 23apr2020Pistoia Alliance
Data for drug discovery and healthcare is often trapped in silos which hampers effective interpretation and reuse. To remedy this, such data needs to be linked both internally and to external sources to make a FAIR data landscape which can power semantic models and knowledge graphs.
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Can we use data to train Machine Learning models, perform statistical analysis, yet without putting private data on risk? There are tools and techniques such as Federated Learning, Differential Privacy or Homomorphic Encryption enabling safer work on the data.
Introduction to research data management. Presented by Natasha Simons at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management, Melbourne 31st may 2018
How to get there from here- Research data Managment training. presented by Sue Cook, CSIRO, at the C3DIS post conference workshop; Managed data – trusted research: an introduction to Research Data Management in Melbourne 31st May 2018
FAIR - Working Data - It's not just about FAIR publishing. Presented by John Morrissey from CSIRO at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management 31 may 2018 in Melbourne
The Rensselaer Institute for Data Exploration and Applications is addressing new modes of data exploration and integration to enhance the work of campus researchers (and beyond). This talk outlines the "data exploration" technologies being explored
OCWC Global 2009 Solving The OER Discovery Problem The DiscoverEd PrototypeAhrash Bissell
Brief presentation describing one perspective on the challenge of improving the "discoverability" of (open) educational resources, and details regarding our prototype (DiscoverEd) which may help us in this effort.
The webinar explores some of the current opportunities for AI within Life Science and look ahead to what we can expect to see over the coming years. These are the accompanying slides.
AHM 2014: Session 1 "Governance and Chartering EarthCube"EarthCube
Lee Allison, PI of the EarthCube Test Enterprise Governance Project, provides an introduction to the Draft Governance Charter, which was developed by the EarthCube community, and further refined with more community feedback. The presentation covers all aspects of the Draft Charter and how we will be 'tackling the tough issues' throughout the meeting and coming year to continue to develop EarthCube governance.
EarthCube All Hands Meeting Outcomes: Architecture Forum EarthCube
The EarthCube All-Hands Meeting, held in Washington, DC June 24-26, had a large emphasis community discussion about coming to convergence on architecture for EarthCube.
This presentation, given at the EarthCube Townhall at ESIP Summer Meeting (July 8-11) outlines the outcomes of the Architecture discussions and how the technology projects and teams are using these outcomes to move forward with EarthCube.
Ontologies for Emergency & Disaster Management Stephane Fellah
Ogc meeting march 2014
OGC OWS-10 Cross-Community Interoperability
Ontologies for Emergency & Disaster Management
(The application of geospatial linked data)
Building Data Ecosystems for Accelerated Discoveryadamkraut
Large federated data ecosystems require diverse teams that can design, build, and integrate a broad range of services to support scientific workflows. Our collaborative team operates at the intersection of science, technology, and data to assess, implement, and teach the key capabilities and capacities modern healthcare and life science needs. Learn the data management techniques, tools, platforms, and frameworks that are proven to be effective at solving complex problems at scale.
Resource Description Framework Approach to Data Publication and FederationPistoia Alliance
Bob Stanley, CEO, IO Informatics, explains the utility to RDF as a standard way of defining and redefining data that could have utility in managing life science information.
Linked Data and Semantic Technologies can support a next generation of science. This talk shows examples of discovery, access, integration, analysis, and shows directions towards prediction and vision.
The current status of Linked Open Data (LOD) shows evidence of many datasets available on the Web in RDF. In the meantime, there are still many challenges to overcome by organizations in their journey of publishing five stars datasets on the Web. Those challenges are not only technical, but are also organizational. At this moment where connectionist AI is gaining a wave of popularity with many applications, LOD needs to go beyond the guarantee of FAIR principles. One direction is to build a sustainable LOD ecosystem with FAIR-S principles. In parallel, LOD should serve as a catalyzer for solving societal issues (LOD for Social Good) and personal empowerment through data (Social Linked Data).
Decentralised identifiers and knowledge graphs vty
Building an Operating System for Open Science: data integration challenges, Dataverse data repository and knowledge graphs. Lecture by Slava Tykhonov, DANS-KNAW, for the Journées Scientifiques de Rochebrune 2023 (JSR'23).
Building a Logical Data Fabric using Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3FF1ubd
In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.
In this session, you will learn how your organization can apply a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization can reduce time to value. Hence, increasing the overall business value of your data assets.
KEY TAKEAWAYS:
- How a Logical Data Fabric is the right approach to assist organizations to unify their data.
- The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
- How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.
Analytic Platforms in the Real World with 451Research and Calpont_July 2012Calpont Corporation
Matt Aslett, 451 Research, and Bob Wilkinson, VP Engineering for Calpont, discuss the emergence of the analytic platform, its place the new ecosystem for Big Data, considerations for selection, and applied use cases of Calpont’s analytic platform, InfiniDB, in Telco and Mobile Advertising.
Bridging the gap between the semantic web and big data: answering SPARQL que...IJECEIAES
Nowadays, the database field has gotten much more diverse, and as a result, a variety of non-relational (NoSQL) databases have been created, including JSON-document databases and key-value stores, as well as extensible markup language (XML) and graph databases. Due to the emergence of a new generation of data services, some of the problems associated with big data have been resolved. In addition, in the haste to address the challenges of big data, NoSQL abandoned several core databases features that make them extremely efficient and functional, for instance the global view, which enables users to access data regardless of how it is logically structured or physically stored in its sources. In this article, we propose a method that allows us to query non-relational databases based on the ontology-based access data (OBDA) framework by delegating SPARQL protocol and resource description framework (RDF) query language (SPARQL) queries from ontology to the NoSQL database. We applied the method on a popular database called Couchbase and we discussed the result obtained.
Development of a Web based Shopping Cart using the Mongo DB Database for Huma...AI Publications
The databases in use today are of SQL-type. This has its drawbacks such as unnecessary complex queries, rigid schema, non-asynchronous persistence and they are definitely not object oriented. Moreover, SQL-shopping cart is expensive by requiring more programs to function. Therefore, the development of a modern shopping cart using MongoDB will eradicate these set backs. The main aim of this study is to design and execute a modern e-commerce shopping cart using MongoDB database. The method used here is the agile development methodology. Stages involved here include: Brainstorm, Design, development stage, Quality Assurance, deployment and Cycle. The User interface is written with HTML, CSS and JavaScript. The HTML (Hyper Text markup language) is used to create the web pages involved, including the forms through which the user supplies input to the system. Each item in the web page is well labeled to optimize user friendliness. The CSS (cascading Style Sheet) is used to create a mobile-friendly, responsive interface to enable mobile devices to seamlessly use the system.The developed shopping cart will save time and effort for programmers rather than using SQL tools with all the labors with it.
EarthCube Community Webinar held Tuesday, Dec. 9th at 11:00 PST/2:00 EST for a virtual kick-off of the new 'Demonstration Phase' of EarthCube, including statements from your Leadership Council members and an update from NSF Program Officer, Eva Zanzerkia.
EarthCube Governance Intro for Solar Terrestrial End-user WorkshopEarthCube
Presentation by the EarthCube Test Enterprise Governance project for the Solar Terrestrial Research End-User Workshop, Newark, New Jersey, August 14, 2014.
AHM 2014: Integrated Data Management System for Critical Zone ObservatoriesEarthCube
Presentation by Anthony Aufdenkampe during the Addressing Data Heterogeneity, Semantic Building Bloack & CI Perspective Session on Day 2, June 25 at the EarthCube All-Hands Meeting
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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/
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.
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/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
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
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
AHM 2014: OceanLink, Smart Data versus Smart Applications
1. Why
OceanLink: Smart Data Versus Smart
Applications
Krzysztof Janowicz
STKO Lab University of California, Santa Barbara, USA
Pascal Hitzler
DaSe Lab Wright State University, Datyon, USA
EarthCube All-Hands Meeting
EarthCube Architecture Forum
June 2014
Smart Data Versus Smart Applications Janowicz and Hitzler
2. Why
What kind of architecture specification do you have?
OceanLink relies on the Semantic Web and Linkd Data; strictly
speaking this is not an architecture.
Data component: Data is translated into RDF (Resource Description
Framework), semantically lifted, and published as 5-star Linked Data.
Schema component: OceanLink wants to foster discoverability and
interoperability without restricting heterogeneity and thus does not
use classical static data models. Instead, it relies on Ontology Design
Patterns (ODP) and data-driven, application-centric ontologies that
use these patterns.
Service component: OceanLink data is made discoverable and
queryable via a SPARQL Endpoint. Inferencing is supported via the
used ODPs and standard Semantic Web reasoning services. A user
interface for data seeking and exploration is provided via a faceted
browsing interface.
Smart Data Versus Smart Applications Janowicz and Hitzler
3. Why
How is it being used?
In OceanLink Semantic Web technologies & ontologies are used to
Ease the publication of data (so far BCO-DMO and R2R)
Improve the retrieval of data beyond keyword search
Deploy ODP to be used by other EarthCube repositories
Establish links between repositories (planned)
Compress data based on background ontologies (planned)
Support simple inferencing based on the ODP
Smart Data Versus Smart Applications Janowicz and Hitzler
4. Why
Why is it valuable?
Two key insights and paradigm shifts
1 Enable the creation of smart data in contrast to smart applications.
Instead of developing increasingly complex software, the business
logic should be moved to the (meta)data. Smart data will make all
future applications more usable, flexible, and robust, while smarter
applications fail to improve data along the same dimensions.
2 Cultural, conceptual, and infrastructural heterogeneities must be
respected in order to maintain different perspectives and differing
priorities and thus foster inclusivity in the EarthCube endeavor.
Heterogeneity is a resource and should not be resolved.
The Semantic Web and Linked Data were developed with those ideas and
Web-scalability in mind. Longevity is ensured via an early, open, and rigid
standardization process by the W3C.
Smart Data Versus Smart Applications Janowicz and Hitzler
5. Why
What worked, and what did not?
Worked
Creation of ontology design patterns
Creation of Linked Data
Faceted browsing interface
Did not work
Too early to tell
Some data types/formats will be difficult to transfer to Linked Data
Smart Data Versus Smart Applications Janowicz and Hitzler