SMART EMT's will utilize inter-disciplinary teams and real-time sensor data to improve transition of care between EMS and hospitals. This will be done through enhanced debriefing and analytics from simulation training to promote situational awareness. The project is a collaboration between George Mason University, Fairfax County agencies, and other partners to develop an integrated debriefing dashboard using technologies like beacons, wearables and learning analytics.
Transforming Research in Collaboration with Funding AgenciesAmazon Web Services
Funding agencies constitute one of the essential pillars for research and have been the backbone for innovation. Data-driven collaborative research is an integral part of many domains. In this session, leaders from the world's largest biomedical and science research agencies, the National Institutes of Health (NIH) and the National Science Foundation (NSF) discuss their programs, including NIH Data Commons and Harnessing the Data Revolution (HDR). The goal of the NIH Data Commons is to accelerate new biomedical discoveries by providing a cloud-based platform where investigators can store, share, access, and compute on digital objects generated from biomedical research. HDR is one of the 10 "Big Ideas" for future investment from the NSF for fundamental data science research. These collaborative initiatives will enable researchers to accelerate science and engineering through improved access to data, tooling, analytic resources in the cloud. These programs will revolutionize the way scientific data and resources are utilized by the research communities.
Information Retrieval and User-centric Recommender System EvaluationAlan Said
Poster describing the ERCIM-funded project on IR- and user-centric recommender system evaluation currently being undertaken in the Information Access group at CWI.
Presented at UMAP 2013.
Automated data collection tools and mature database technology lead to tremendous amounts of data stored in databases, data warehouses and other information repositories.
Why Data Mining?
What Is Data Mining?
Data Mining: On What Kind of Data?
Data Classification
What is Sentiment Classification?
Importance of Sentiment classification
Twitter for Sentiment Classification
Problem Statement
Goal of this Classifications
Method to be used
Conclusion
Overview of Library & Systematic Review (LASYR) Infrastructure for Blockchain and Emerging Technologies project at IEEE Healthcare: Blockchain & AI event - 07 April 2021
How much is that data in the window : Healthcare data valuationSean Manion PhD
Presentation on healthcare data valuation, data confidence fabrics, layers of trust in healthcare, and health data marketplaces as part of the Health Data Valuation event, Session 10 of the IEEE Healthcare: Blockchain & AI Virtual Series on 25 August 2021
Transforming Research in Collaboration with Funding AgenciesAmazon Web Services
Funding agencies constitute one of the essential pillars for research and have been the backbone for innovation. Data-driven collaborative research is an integral part of many domains. In this session, leaders from the world's largest biomedical and science research agencies, the National Institutes of Health (NIH) and the National Science Foundation (NSF) discuss their programs, including NIH Data Commons and Harnessing the Data Revolution (HDR). The goal of the NIH Data Commons is to accelerate new biomedical discoveries by providing a cloud-based platform where investigators can store, share, access, and compute on digital objects generated from biomedical research. HDR is one of the 10 "Big Ideas" for future investment from the NSF for fundamental data science research. These collaborative initiatives will enable researchers to accelerate science and engineering through improved access to data, tooling, analytic resources in the cloud. These programs will revolutionize the way scientific data and resources are utilized by the research communities.
Information Retrieval and User-centric Recommender System EvaluationAlan Said
Poster describing the ERCIM-funded project on IR- and user-centric recommender system evaluation currently being undertaken in the Information Access group at CWI.
Presented at UMAP 2013.
Automated data collection tools and mature database technology lead to tremendous amounts of data stored in databases, data warehouses and other information repositories.
Why Data Mining?
What Is Data Mining?
Data Mining: On What Kind of Data?
Data Classification
What is Sentiment Classification?
Importance of Sentiment classification
Twitter for Sentiment Classification
Problem Statement
Goal of this Classifications
Method to be used
Conclusion
Overview of Library & Systematic Review (LASYR) Infrastructure for Blockchain and Emerging Technologies project at IEEE Healthcare: Blockchain & AI event - 07 April 2021
How much is that data in the window : Healthcare data valuationSean Manion PhD
Presentation on healthcare data valuation, data confidence fabrics, layers of trust in healthcare, and health data marketplaces as part of the Health Data Valuation event, Session 10 of the IEEE Healthcare: Blockchain & AI Virtual Series on 25 August 2021
Report out: SMART Emergency Medical TeamsUS-Ignite
SMART Emergency Medical Teams will help inter-disciplinary
teams improve quality of transition-of-care, promote
situational awareness, and the efficacy of simulation
debriefing.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
Emerging technologies provide opportunities for the humanitarian responders’ community to enhance the effectiveness of their response to crisissituations. A part of this development can be contributed to a new type of information supply chains -driven by collaboration with digital, online communities- enabling organizations to make better informed decisions. However, how exactly and to what extend this collaboration impacts the decision making process is unknown. To improve these new information exchanges and the corresponding systems, an evaluation method is needed to assess the performance of these processes and systems. This paper builds on existing evaluation methods for information systems and design principles to propose such an impact evaluation framework. The proposed framework has been applied in a case study to demonstrate its potential to identify areas for further improvement in the (online) collaboration between information suppliers and users.
A Big Picture in Research Data ManagementCarole Goble
A personal view of the big picture in Research Data Management, given at GFBio - de.NBI Summer School 2018 Riding the Data Life Cycle! Braunschweig Integrated Centre of Systems Biology (BRICS), 03 - 07 September 2018
Building an Intelligent Biobank to Power Research Decision-MakingDenodo
This presentation belongs to the workshop: "Building an Intelligent Biobank to Power Research Decision-Making", from ISBER 2015 Annual Meeting by Lori A. Ball (Chief Operating Officer, President of Integrated Client Solutions at BioStorage Technologies, Inc), Brian Brunner (Senior Manager, Clinical Practice at LabAnswer) and Suresh Chandrasekaran (Senior Vice President at Denodo).
The workshop cover three different topic areas:
- Research sample intelligence: the growing need for Global Data Integration (Biobank Sample and Data Stakeholders).
- Building a research data integration plan and cloud sourcing strategy (data integration).
- How data virtualization works and the value it delivers (a data virtualization introduction, solution portfolio and current customers in Life Sciences industry).
The biomedical R&D environment is increasingly dependent on data meta-analysis and bioinformatics to support research advancements. The integration of biorepository sample inventory data with biomarker and clinical research information has become a priority to R&D organizations. Therefore, a flexible IT system for managing sample collections, integrating sample data with clinical data and providing a data virtualization platform will enable the advancement of research studies. This workshop provides an overview of how sample data integration, virtualization and analytics can lead to more streamlined and unified sample intelligence to support global biobanking for future research.
This presentation was provided by Tim McGeary of Duke University during the NISO virtual conference, Open Data Projects, held on Wednesday, June 13, 2018.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
Advanced Analytics and Data Science ExpertiseSoftServe
An overview of SoftServe's Data Science service line.
- Data Science Group
- Data Science Offerings for Business
- Machine Learning Overview
- AI & Deep Learning Case Studies
- Big Data & Analytics Case Studies
Visit our website to learn more: http://www.softserveinc.com/en-us/
Challenges in Clinical Research: Aridhia Disrupts Technology Approach to Rese...VMware Tanzu
Join Jeff Kelly, Pivotal’s Big Data Strategist and Chris Roche, Aridhia’s CEO, to learn how Big Data and data science are being applied to clinical research. Learn…
• Why research-oriented healthcare delivery organizations and academic medical centers need an ACRIS
• How improving collaboration and productivity accelerates the discovery of insights and increases competitiveness
• Why robust data security is critical to modernizing engagement between academia, industry and healthcare
• How to reduce research costs while improving commercialization opportunities
• Why enabling transparent analysis and reproducibility of research are key to scientific progress
• Best practices to get started on your digital transformation and Big Data journey
Report out: SMART Emergency Medical TeamsUS-Ignite
SMART Emergency Medical Teams will help inter-disciplinary
teams improve quality of transition-of-care, promote
situational awareness, and the efficacy of simulation
debriefing.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
Emerging technologies provide opportunities for the humanitarian responders’ community to enhance the effectiveness of their response to crisissituations. A part of this development can be contributed to a new type of information supply chains -driven by collaboration with digital, online communities- enabling organizations to make better informed decisions. However, how exactly and to what extend this collaboration impacts the decision making process is unknown. To improve these new information exchanges and the corresponding systems, an evaluation method is needed to assess the performance of these processes and systems. This paper builds on existing evaluation methods for information systems and design principles to propose such an impact evaluation framework. The proposed framework has been applied in a case study to demonstrate its potential to identify areas for further improvement in the (online) collaboration between information suppliers and users.
A Big Picture in Research Data ManagementCarole Goble
A personal view of the big picture in Research Data Management, given at GFBio - de.NBI Summer School 2018 Riding the Data Life Cycle! Braunschweig Integrated Centre of Systems Biology (BRICS), 03 - 07 September 2018
Building an Intelligent Biobank to Power Research Decision-MakingDenodo
This presentation belongs to the workshop: "Building an Intelligent Biobank to Power Research Decision-Making", from ISBER 2015 Annual Meeting by Lori A. Ball (Chief Operating Officer, President of Integrated Client Solutions at BioStorage Technologies, Inc), Brian Brunner (Senior Manager, Clinical Practice at LabAnswer) and Suresh Chandrasekaran (Senior Vice President at Denodo).
The workshop cover three different topic areas:
- Research sample intelligence: the growing need for Global Data Integration (Biobank Sample and Data Stakeholders).
- Building a research data integration plan and cloud sourcing strategy (data integration).
- How data virtualization works and the value it delivers (a data virtualization introduction, solution portfolio and current customers in Life Sciences industry).
The biomedical R&D environment is increasingly dependent on data meta-analysis and bioinformatics to support research advancements. The integration of biorepository sample inventory data with biomarker and clinical research information has become a priority to R&D organizations. Therefore, a flexible IT system for managing sample collections, integrating sample data with clinical data and providing a data virtualization platform will enable the advancement of research studies. This workshop provides an overview of how sample data integration, virtualization and analytics can lead to more streamlined and unified sample intelligence to support global biobanking for future research.
This presentation was provided by Tim McGeary of Duke University during the NISO virtual conference, Open Data Projects, held on Wednesday, June 13, 2018.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
Advanced Analytics and Data Science ExpertiseSoftServe
An overview of SoftServe's Data Science service line.
- Data Science Group
- Data Science Offerings for Business
- Machine Learning Overview
- AI & Deep Learning Case Studies
- Big Data & Analytics Case Studies
Visit our website to learn more: http://www.softserveinc.com/en-us/
Challenges in Clinical Research: Aridhia Disrupts Technology Approach to Rese...VMware Tanzu
Join Jeff Kelly, Pivotal’s Big Data Strategist and Chris Roche, Aridhia’s CEO, to learn how Big Data and data science are being applied to clinical research. Learn…
• Why research-oriented healthcare delivery organizations and academic medical centers need an ACRIS
• How improving collaboration and productivity accelerates the discovery of insights and increases competitiveness
• Why robust data security is critical to modernizing engagement between academia, industry and healthcare
• How to reduce research costs while improving commercialization opportunities
• Why enabling transparent analysis and reproducibility of research are key to scientific progress
• Best practices to get started on your digital transformation and Big Data journey
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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!
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
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.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
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/
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.
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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
SMART Emergency Medical Teams
1. SMART EMT’s will help inter-disciplinary
teams improve transition-of-care quality,
promote situational awareness, and enhance
the efficacy of simulation debriefing.
Municipal sponsor: Fairfax County, VA USA
• Project Leads:
• Brenda Bannan PhD George Mason University
• Jeff Segall MA, MBA Inflow Interactive
• Key Partners:
• Fairfax Fire&Rescue, Inova, Emiurgic Analytics, GMU volunteers3/28/201
6
1
3. • Simulation-based team training in medical,
disaster recovery contexts
– Interaction among interdisciplinary roles/teams
• Enhanced debrief –visualization/analytics
• Collaborative reflection, situation awareness
and experiential learning
• Integrated real-time data collection
IoT sensors (beacons, wearables, RFID)
4. 2015 IoT Proximity Beacon Data
Data points indicate individual provider distance from
Sim-Man and trauma bay LRS collectors over time
Source: Bridget Lewis, GMU
3/28/2016 4
5. EMS Arrival - Transfer to ER
Median Beacon Distance to Sim Man
Ambulance Arrival - Minute 4
6. • xAPI is granular method to track social,
progress, teams, virtual media, real-world
learning experiences…
IoT sensors
• JSON via REST to a ‘LRS’ (learning record store)
– Activity streams: {Actor: Verb: Object}
• International open source spec ensures
interoperability
– Portable lifetime learning record
– Badging engine, competencies, game mechanics
11. • Reduce instructional design and
simulation prep time
– Managers and trainers focus on coaching teams
and individuals’ development needs
• Reduce cycle-time in the ‘golden hour’
– Transfer-of-care events
– Critical equipment and supplies
Helping medical professionals save lives
12. • Performance support tools, analytics to
enhance team debrief - in context
• Integrated real-time data collection
– IoT sensors (beacons, wearables, RFID)
• Standards-based schema for inter-operability
– xAPI, FHIR
Data-driven learning designs to
support medical and disaster
recovery simulations