In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this installment, we will hear from Rafael Richards, Physician Informatician, Office of Informatics and Analytics in the Veterans Health Administration (VHA), about “Transformations for Integrating VA data with FHIR in RDF.”
The VistA EHR has its own data model and vocabularies for representing healthcare data. This webinar describes how SPARQL Inference Notation (SPIN) can be used to translate VistA data to the data represented used by FHIR, an emerging interchange standard.
Our speaker, Joshua Mandel, will provide a lightning tour of Fast Healthcare Interoperability Resources (FHIR), an emerging clinical data standard, with a focus on its resource-oriented approach, and a discussion of how FHIR intersects with the Semantic Web. We'll look at how FHIR represents links between entities; how FHIR represents concepts from standards-based vocabularies; and how a set of FHIR instance data can be represented in RDF.
In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...DATAVERSITY
Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.
Our speaker, Joshua Mandel, will provide a lightning tour of Fast Healthcare Interoperability Resources (FHIR), an emerging clinical data standard, with a focus on its resource-oriented approach, and a discussion of how FHIR intersects with the Semantic Web. We'll look at how FHIR represents links between entities; how FHIR represents concepts from standards-based vocabularies; and how a set of FHIR instance data can be represented in RDF.
In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...DATAVERSITY
Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.
Tutorial: Describing Datasets with the Health Care and Life Sciences Communit...Alasdair Gray
Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting HCLS community profile covers elements of description, identification, attribution, versioning, provenance, and content summarization. The HCLS community profile reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets. The goal of this tutorial is to explain elements of the HCLS community profile and to enable users to craft and validate descriptions for datasets of interest.
This webinar explains the service, covers what publishers need to participate and answers any questions you may have. This webinar was held on November 10, 2015.
Supporting Dataset Descriptions in the Life SciencesAlasdair Gray
Machine processable descriptions of datasets can help make data more FAIR; that is Findable, Accessible, Interoperable, and Reusable. However, there are a variety of metadata profiles for describing datasets, some specific to the life sciences and others more generic in their focus. Each profile has its own set of properties and requirements as to which must be provided and which are more optional. Developing a dataset description for a given dataset to conform to a specific metadata profile is a challenging process.
In this talk, I will give an overview of some of the dataset description specifications that are available. I will discuss the difficulties in writing a dataset description that conforms to a profile and the tooling that I've developed to support dataset publishers in creating metadata description and validating them against a chosen specification.
Seminar talk given at the EBI on 5 April 2017
New Initiatives - Geoffrey Bilder - London LIVE 2017Crossref
Presentation by Geoffrey Bilder at Crossref London LIVE, 26th September 2017. New initiatives at Crossref including organisational and grant identifiers.
The DataTags System: Sharing Sensitive Data with ConfidenceMerce Crosas
This talk was part of a session at the Research Data Alliance (RDA) 8th Plenary on Privacy Implications of Research Data Sets, during International Data Week 2016:
https://rd-alliance.org/rda-8th-plenary-joint-meeting-ig-domain-repositories-wg-rdaniso-privacy-implications-research-data
Slides in Merce Crosas site:
http://scholar.harvard.edu/mercecrosas/presentations/datatags-system-sharing-sensitive-data-confidence
Crossref DataCite joint data citation webinarCrossref
Webinar by DataCite and Crossref on how to cite data (for publishers and repositories) and how this information can be used to recognise and credit data creators.
Crossref Community Webinar - Asia Pacific 12-14-2016Crossref
Hello, we recently asked our members in Asia Pacific which subjects they’d most like to hear about, and you chose:
* DOI Display guidelines: Ed Pentz, Executive Director, will talk through our new recommendations and show examples of both good and not-so-good practices.
* New metadata deposit tool: Jennifer Lin, Product Director, will share details (and a sneak preview) of the new Crossref tool for publishers to manually register and update content
* How to distribute your references: Ed Pentz, Executive Director, will describe why and how publishers might share references using Crossref.
We look forward to talking.
Open Source Tools Facilitating Sharing/Protecting Privacy: Dataverse and Data...Merce Crosas
Presentation for the NFAIS Webinar series: Open Data Fostering Open Science: Meeting Researchers' Needs
http://www.nfais.org/index.php?option=com_mc&view=mc&mcid=72&eventId=508850&orgId=nfais
A presentation designed to inform researchers about how they can use ScienceOpen for advanced search and discovery and increasing their research impact.
Using Semantic Technology to Drive Agile Analytics - SLIDESDATAVERSITY
How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.
Tutorial: Describing Datasets with the Health Care and Life Sciences Communit...Alasdair Gray
Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting HCLS community profile covers elements of description, identification, attribution, versioning, provenance, and content summarization. The HCLS community profile reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets. The goal of this tutorial is to explain elements of the HCLS community profile and to enable users to craft and validate descriptions for datasets of interest.
This webinar explains the service, covers what publishers need to participate and answers any questions you may have. This webinar was held on November 10, 2015.
Supporting Dataset Descriptions in the Life SciencesAlasdair Gray
Machine processable descriptions of datasets can help make data more FAIR; that is Findable, Accessible, Interoperable, and Reusable. However, there are a variety of metadata profiles for describing datasets, some specific to the life sciences and others more generic in their focus. Each profile has its own set of properties and requirements as to which must be provided and which are more optional. Developing a dataset description for a given dataset to conform to a specific metadata profile is a challenging process.
In this talk, I will give an overview of some of the dataset description specifications that are available. I will discuss the difficulties in writing a dataset description that conforms to a profile and the tooling that I've developed to support dataset publishers in creating metadata description and validating them against a chosen specification.
Seminar talk given at the EBI on 5 April 2017
New Initiatives - Geoffrey Bilder - London LIVE 2017Crossref
Presentation by Geoffrey Bilder at Crossref London LIVE, 26th September 2017. New initiatives at Crossref including organisational and grant identifiers.
The DataTags System: Sharing Sensitive Data with ConfidenceMerce Crosas
This talk was part of a session at the Research Data Alliance (RDA) 8th Plenary on Privacy Implications of Research Data Sets, during International Data Week 2016:
https://rd-alliance.org/rda-8th-plenary-joint-meeting-ig-domain-repositories-wg-rdaniso-privacy-implications-research-data
Slides in Merce Crosas site:
http://scholar.harvard.edu/mercecrosas/presentations/datatags-system-sharing-sensitive-data-confidence
Crossref DataCite joint data citation webinarCrossref
Webinar by DataCite and Crossref on how to cite data (for publishers and repositories) and how this information can be used to recognise and credit data creators.
Crossref Community Webinar - Asia Pacific 12-14-2016Crossref
Hello, we recently asked our members in Asia Pacific which subjects they’d most like to hear about, and you chose:
* DOI Display guidelines: Ed Pentz, Executive Director, will talk through our new recommendations and show examples of both good and not-so-good practices.
* New metadata deposit tool: Jennifer Lin, Product Director, will share details (and a sneak preview) of the new Crossref tool for publishers to manually register and update content
* How to distribute your references: Ed Pentz, Executive Director, will describe why and how publishers might share references using Crossref.
We look forward to talking.
Open Source Tools Facilitating Sharing/Protecting Privacy: Dataverse and Data...Merce Crosas
Presentation for the NFAIS Webinar series: Open Data Fostering Open Science: Meeting Researchers' Needs
http://www.nfais.org/index.php?option=com_mc&view=mc&mcid=72&eventId=508850&orgId=nfais
A presentation designed to inform researchers about how they can use ScienceOpen for advanced search and discovery and increasing their research impact.
Using Semantic Technology to Drive Agile Analytics - SLIDESDATAVERSITY
How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...DATAVERSITY
In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
Enterprise Data World: Data Governance - The Four Critical Success FactorsDATAVERSITY
Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible?
This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation.
Some of the topics discussed in this webinar include:
The Four Critical Success Factors for developing and implementing a DG program
Common Program Barriers that may be hampering your ability to drive a successful program
How to identify which barriers might be plaguing your program efforts
Key Program Components to help ensure a successful DG program
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data GardenDATAVERSITY
Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.
The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage.
With that being said, we will:
- Discuss data architecture’s guiding principles and best practices
- Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy
- Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)
RWDG Webinar: The New Non-Invasive Data Governance FrameworkDATAVERSITY
Non-Invasive Data Governance is summarized as the practice of formalizing accountability for data and the application of governance to process. Non-Invasive Data Governance describes how data governance is applied to the organization rather than being forced into the environment. A NIDG framework will be introduced in this webinar.
In this month’s installment of the RWDG webinar series, Bob Seiner will present a new data governance framework that addresses the core components of data governance for each level of the organization. The resulting framework can be used for all approaches to data governance.
In this webinar Bob will discuss:
- The five core components of a data governance effort
- The five levels where the core components will be addressed
- Detailed explanation of each component for each level
- A diagram to complete the framework for your organization
- A framework comparison across approaches
EDW Webinar: Managing Change for Successful Data GovernanceDATAVERSITY
Having trouble making your information management (IM)/data governance (DG) changes stick? How many times have you gone through this process?
Successful data governance means changes to your information management culture. Changing that culture means that you are asking people to think and behave differently about how data is created, accessed and used. If the results are to be sustainable, successful IM/DG change requires an organized and systematic way to manage those changes.
In preparation for their EDW15 tutorial, Kelle O’Neal and Pam Thomas will discuss the most significant obstacles to successful IM/DG change, and the key factors to working through those obstacles to achieve business benefit.
Enterprise Data World Webinar: How to Get Your MDM Program Up & RunningDATAVERSITY
How to get your MDM program up & running”
This session will deliver a Master Data Management primer to introduce:
Master vs Reference data
Multi vs Single domain MDM solutions
A MDM reference architecture and
MDM implementation architectures
This will be illustrated with a real world example from describing how to identify & justify the appropriate data subjects areas that are right for mastering and how to align an MDM initiative with in-flight business initiatives and make the business case.
Smart Data Webinar: Artificial General Intelligence - When Can I Get It?DATAVERSITY
Artificial General Intelligence (AGI) - or strong AI - refers to a domain-independent, machine-based system that approaches or exceeds human performance on any and all cognitive tasks. Estimates for the arrival of true AGI solutions range from last week (as in, we have one!) to decades, to infinity and beyond. As the general study of cybernetic systems and modern AI and cognitive computing capture the imagination of civic and business leaders, and fans of science fiction, it is important to be able to distinguish between progress and smoke & mirrors.
This webinar will present an overview of approaches to AGI, examples of promising research and commercial AGI activities, and show participants how to critically evaluate academic and vendor claims.
LDM Webinar: Data Modeling & Business IntelligenceDATAVERSITY
Business Intelligence (BI) is a valuable way to use information to show the overall health and performance of the organization. At its core is quality, well-structured data that allows for successful reporting and analytics. A data model helps provide both the business definitions as well as the structural optimization needed for successful BI implementations.
Join this webinar to see how a data model underpins business intelligence and analytics in today’s organization.
Enterprise Data World Webinar: Mastering & Referencing Data for the EnterpriseDATAVERSITY
Developing and implementing a master record and reference data through a best practice approach and lessons learned for your organization’s data business needs. The ability to leverage the immense data available across an organization has become paramount for continued growth and success. Companies need accessible and reliable information to make more informed and effective business decisions across channels while continuing to provide quality service to their customers. Many companies recognize the need to develop a Master Data Program, as part of an overall Data Strategy initiative, to consistently manage the quality, data interoperability, accessibility, and availability of core data (e.g., customer, product). Determining where to start, finding business opportunities, defining what master data management means in your organization, and addressing the cultural and political realities are all critical to make your master data program successful and valuable. This seminar will present real world approaches used for successfully implementing a Master Data Domain and program from several organization cases including Walgreens.
Focus on Your Analysis, Not Your SQL CodeDATAVERSITY
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions.
Join us to learn how self-service data analytics allows analysts to:
- Utilize a drag-and-drop workflow for data and analytic processes without writing code
- Minimize data movement and ensure data integrity through in-database capabilities
- Easily work across relational and non-relational databases to deliver faster business results
Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...DATAVERSITY
Google “citizen data scientist” today and you will see about 1M results. That number is data. It may be interesting, but it is meaningless without context. Sometimes it appears that we are drowning in data from systems and sensors but starving for insights. We definitely produce more of the former than the latter, which has created demand for more powerful tools to simplify the process and lower the skills requirement for analysis. As vendors build systems to meet this demand, we hear about the coming ”democratization” of big data as more people at varying levels within organizations are empowered to find meaning and improve their own performance with data-driven insights. This is a good thing, but it does require caution.
To paraphrase Col Jessup in A Few Good Men: You want answers? You can’t handle the data.
In this webinar, we will survey emerging approaches to simplifying analysis, and discuss the benefits, dangers, and skills required for individuals and organizations to thrive in the brave new world of analytics everywhere, for everyone.
Linked Vitals: A Linked Data Approach to Semantic InteroperabilityDATAVERSITY
This presentation was given at the Semantic Technology & Business Conference in San Jose, California on August 20, 2014 by Dr. Rafael M. Richards MD, MS. Dr. Richards is Physician Informaticist from the Office of Informatics and Analytics at the Veterans Health Administration, U.S. Department of Veterans Affairs.
SmartData Webinar Slides: The Yosemite Project for Healthcare Information int...DATAVERSITY
Healthcare data originates in a wide variety of data formats, data models and vocabularies, making information interoperability a major challenge. Although many standards exist, and each one strives for a level of interoperability within its scope, in the aggregate these standards form an uncoordinated patchwork that thwarts interoperability. Furthermore, even when standards are used, translation between data formats, data models and vocabularies is still needed, for a variety of reasons.
The Yosemite Project describes an ambitious roadmap for achieving semantic interoperability of all structured healthcare information. Based on RDF as the best available candidate for a universal information representation, this roadmap addresses both the need to 'standardize the standards' and the opportunity to crowdsource data translations that are still required for information interoperability.
The following brief details the use of linked data to connect various high quality data sets produced by the U.S. Environmental Protection Agency. Linked data is an open standards way to publish and consume data. Using a linked data approach and the REST API, developers, scientists, and the public can more easily find, access and re-use authoritative data published by the EPA.
3 Round Stones Briefing to U.S. EPA's Chief Data Scientist on Open DataBernadette Hyland-Wood
The following is technical brief to U.S. EPA's Chief Data Scientist on open data information architecture, the use of Linked Data and the EPA Linked Data Management Service. The briefing was held in February 2016 and was educational in nature.
You almost need to be a super sleuth to decode the acronyms in clinical metadata. Our confidential (not really) dossier of some of the important acronyms in clinical data standards will debrief you on the case.
Linked Data for the Masses: The approach and the SoftwareIMC Technologies
Title: Linked Data for the Masses: The approach and the Software
@ EELLAK (GFOSS) Conference 2010
Athens, Greece
15/05/2010
Creator: George Anadiotis (R&D Director)
Complete book Database management systems Handbook 3rd edition by Muhammad Sharif
#DBMS
#RDBMS
#DATABASE MANAGEMENT SYSTEMS HANDBOOK
#DATABASE COMPLETE BOOK HANDBOOK
DATABASE SYSTEMS BY MUHAMMAD SHARIF
DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
Complete book Database management systems Handbook 3rd edition by Muhammad Sharif
#DBMS
#RDBMS
#DATABASE MANAGEMENT SYSTEMS HANDBOOK
#DATABASE COMPLETE BOOK HANDBOOK
DATABASE SYSTEMS BY MUHAMMAD SHARIF
DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
Full book Database system Handbook 3rd edition by Muhammad Sharif
I'm DBA in SKMCHRC and I have did this book by title: Database systems handbook.
Its other names are: Database management systems, Database systems basic conecpts
Database services and Relational Database management systems handbook:
Author name is Muhammad Sharif.
#Database_systems_handbook
#Database_Management_Systems
#Relational Database_management systems
#DBMS
#RDBMS
Complete Full book Database system Handbook 3rd edition by Muhammad Sharif
I'm DBA in SKMCHRC and I have did this book by title: Database systems handbook.
Its other names are: Database management systems, Database systems basic conecpts
Database services and Relational Database management systems handbook:
Author name is Muhammad Sharif.
#Database_systems_handbook
#Database_Management_Systems
#Relational Database_management systems
#DBMS
#RDBMS
Complete book Database management systems Handbook 3rd edition by Muhammad Sharif
#DBMS
#RDBMS
#DATABASE MANAGEMENT SYSTEMS HANDBOOK
#DATABASE COMPLETE BOOK HANDBOOK
DATABASE SYSTEMS BY MUHAMMAD SHARIF
DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
TITLE: DATABASE SYSTEMS HANDBOOK
Muhammad Sharif (Database systems handbook)database administrator SKMCHRC Lahore, Pakistan
I'm writing this book. I'm Muhammad Sharif write a Database systems handbook about dbms, rdbms database management system abrivations.
I have core knowledge of database systems and its structure and database system administration too.
I thanks to all my reader who ack.
Thanks
I'm Muhammad Sharif Software engineer, SKMCHRC Lahore, Database systems handbook is written by Muhammad Sharif is pure RDBMS having all core knowledge of databases and its related subjects.
Muhammad Sharif Database systems handbook
This Database management system DBMS is written by Muhammad Sharif Software Engineer SKMCHRC Lahore
It include RDBMS and File system contents and Database system to advance Databases like DBA Concepts.
Similar to Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR in RDF (20)
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen?
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
Would you share your bank account information on social media? How about shouting your social security number on the New York City subway? We didn’t think so either – that’s why data governance is consistently top of mind.
In this webinar, we’ll discuss the common Cloud data governance best practices – and how to apply them today. Join us to uncover Google Cloud’s investment in data governance and learn practical and doable methods around key management and confidential computing. Hear real customer experiences and leave with insights that you can share with your team. Let’s get solving.
Topics that you will hear addressed in this webinar:
- Understanding the basics of Cloud Incident Response (IR) and anticipated data governance trends
- Best practices for key management and apply data governance to your day-to-day
- The next wave of Confidential Computing and how to get started, including a demo
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:
- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
Deep Leg Vein Thrombosis (DVT): Meaning, Causes, Symptoms, Treatment, and Mor...The Lifesciences Magazine
Deep Leg Vein Thrombosis occurs when a blood clot forms in one or more of the deep veins in the legs. These clots can impede blood flow, leading to severe complications.
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
How many patients does case series should have In comparison to case reports.pdfpubrica101
Pubrica’s team of researchers and writers create scientific and medical research articles, which may be important resources for authors and practitioners. Pubrica medical writers assist you in creating and revising the introduction by alerting the reader to gaps in the chosen study subject. Our professionals understand the order in which the hypothesis topic is followed by the broad subject, the issue, and the backdrop.
https://pubrica.com/academy/case-study-or-series/how-many-patients-does-case-series-should-have-in-comparison-to-case-reports/
CHAPTER 1 SEMESTER V PREVENTIVE-PEDIATRICS.pdfSachin Sharma
This content provides an overview of preventive pediatrics. It defines preventive pediatrics as preventing disease and promoting children's physical, mental, and social well-being to achieve positive health. It discusses antenatal, postnatal, and social preventive pediatrics. It also covers various child health programs like immunization, breastfeeding, ICDS, and the roles of organizations like WHO, UNICEF, and nurses in preventive pediatrics.
The Importance of Community Nursing Care.pdfAD Healthcare
NDIS and Community 24/7 Nursing Care is a specific type of support that may be provided under the NDIS for individuals with complex medical needs who require ongoing nursing care in a community setting, such as their home or a supported accommodation facility.
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
This conference will delve into the intricate intersections between mental health, legal frameworks, and the prison system in Bolivia. It aims to provide a comprehensive overview of the current challenges faced by mental health professionals working within the legislative and correctional landscapes. Topics of discussion will include the prevalence and impact of mental health issues among the incarcerated population, the effectiveness of existing mental health policies and legislation, and potential reforms to enhance the mental health support system within prisons.
Antibiotic Stewardship by Anushri Srivastava.pptxAnushriSrivastav
Stewardship is the act of taking good care of something.
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
WHO launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) in 2015 to fill knowledge gaps and inform strategies at all levels.
ACCORDING TO apic.org,
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
ACCORDING TO pewtrusts.org,
Antibiotic stewardship refers to efforts in doctors’ offices, hospitals, long term care facilities, and other health care settings to ensure that antibiotics are used only when necessary and appropriate
According to WHO,
Antimicrobial stewardship is a systematic approach to educate and support health care professionals to follow evidence-based guidelines for prescribing and administering antimicrobials
In 1996, John McGowan and Dale Gerding first applied the term antimicrobial stewardship, where they suggested a causal association between antimicrobial agent use and resistance. They also focused on the urgency of large-scale controlled trials of antimicrobial-use regulation employing sophisticated epidemiologic methods, molecular typing, and precise resistance mechanism analysis.
Antimicrobial Stewardship(AMS) refers to the optimal selection, dosing, and duration of antimicrobial treatment resulting in the best clinical outcome with minimal side effects to the patients and minimal impact on subsequent resistance.
According to the 2019 report, in the US, more than 2.8 million antibiotic-resistant infections occur each year, and more than 35000 people die. In addition to this, it also mentioned that 223,900 cases of Clostridoides difficile occurred in 2017, of which 12800 people died. The report did not include viruses or parasites
VISION
Being proactive
Supporting optimal animal and human health
Exploring ways to reduce overall use of antimicrobials
Using the drugs that prevent and treat disease by killing microscopic organisms in a responsible way
GOAL
to prevent the generation and spread of antimicrobial resistance (AMR). Doing so will preserve the effectiveness of these drugs in animals and humans for years to come.
being to preserve human and animal health and the effectiveness of antimicrobial medications.
to implement a multidisciplinary approach in assembling a stewardship team to include an infectious disease physician, a clinical pharmacist with infectious diseases training, infection preventionist, and a close collaboration with the staff in the clinical microbiology laboratory
to prevent antimicrobial overuse, misuse and abuse.
to minimize the developme
Defecation
Normal defecation begins with movement in the left colon, moving stool toward the anus. When stool reaches the rectum, the distention causes relaxation of the internal sphincter and an awareness of the need to defecate. At the time of defecation, the external sphincter relaxes, and abdominal muscles contract, increasing intrarectal pressure and forcing the stool out
The Valsalva maneuver exerts pressure to expel faeces through a voluntary contraction of the abdominal muscles while maintaining forced expiration against a closed airway. Patients with cardiovascular disease, glaucoma, increased intracranial pressure, or a new surgical wound are at greater risk for cardiac dysrhythmias and elevated blood pressure with the Valsalva maneuver and need to avoid straining to pass the stool.
Normal defecation is painless, resulting in passage of soft, formed stool
CONSTIPATION
Constipation is a symptom, not a disease. Improper diet, reduced fluid intake, lack of exercise, and certain medications can cause constipation. For example, patients receiving opiates for pain after surgery often require a stool softener or laxative to prevent constipation. The signs of constipation include infrequent bowel movements (less than every 3 days), difficulty passing stools, excessive straining, inability to defecate at will, and hard feaces
IMPACTION
Fecal impaction results from unrelieved constipation. It is a collection of hardened feces wedged in the rectum that a person cannot expel. In cases of severe impaction the mass extends up into the sigmoid colon.
DIARRHEA
Diarrhea is an increase in the number of stools and the passage of liquid, unformed feces. It is associated with disorders affecting digestion, absorption, and secretion in the GI tract. Intestinal contents pass through the small and large intestine too quickly to allow for the usual absorption of fluid and nutrients. Irritation within the colon results in increased mucus secretion. As a result, feces become watery, and the patient is unable to control the urge to defecate. Normally an anal bag is safe and effective in long-term treatment of patients with fecal incontinence at home, in hospice, or in the hospital. Fecal incontinence is expensive and a potentially dangerous condition in terms of contamination and risk of skin ulceration
HEMORRHOIDS
Hemorrhoids are dilated, engorged veins in the lining of the rectum. They are either external or internal.
FLATULENCE
As gas accumulates in the lumen of the intestines, the bowel wall stretches and distends (flatulence). It is a common cause of abdominal fullness, pain, and cramping. Normally intestinal gas escapes through the mouth (belching) or the anus (passing of flatus)
FECAL INCONTINENCE
Fecal incontinence is the inability to control passage of feces and gas from the anus. Incontinence harms a patient’s body image
PREPARATION AND GIVING OF LAXATIVESACCORDING TO POTTER AND PERRY,
An enema is the instillation of a solution into the rectum and sig
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR in RDF
1. Rafael Richards MD MS 2014
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Linked Vitals
A Linked Data Translation Approach
to Semantic Interoperability
November 12, 2014
Dataversity Webinar
Rafael M Richards MD MS
Physician Informaticist
Veterans Health Administratioan
U.S. Department of Veterans Affairs
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Problem Statement: General
How does one semantically integrate data such as vital
signs between different patient information systems?
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Problem Statement: Specific
How does one integrate vital sign data between VA VISTA electronic
health record (EHR) system and a potential exchange partner using
the HL7 FHIR standard?
Language barriers to exchange
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Approach: Linked Data Foundation
One step towards minimizing data friction between systems is to
provide common model-neutral expression language such as RDF.
A common exchange language
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Summary of Linked Data Translation
Rule-based mapping
Model alignment
Vocabulary alignment
Common syntax within
model-neutral medium
(Linked Data)
Syntactic
translation
Fileman
Semantic
translation
Source
Data
Integrated
Data
Different Syntax
Different Models
Different Vocabularies
Common Syntax
Common Model
Common Vocabulary
Common Meaning
Syntax A
Model A
Vocabulary A
Syntax B
Model B
Vocabulary B
Neutral
Model
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VISTA: Overview
• Veterans Information Systems and Technology Architecture
• Information system of all VA hospitals
• Foundation of several public healthcare systems
– VA (VISTA): 1200+ care sites
– DoD(CHCS): 900+ care sites
– IHS (RPMS): 500+ care sites
– NY State: 24 hospitals
• Most familiar EHR in U.S.
– Over 60% of U.S.-trained physicians have used VISTA
• Open source
– Deployed in many other settings in U.S. and internationally
– Many developments by open source community
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M
VISTA is an integrated patient-centric
EHR.
The data architecture of VISTA consists
of over150 applications for clinical care
integrated within a single common
multidimensional database (M DB).
In VISTA both business logic
(Applications) and data (Database) are
managed with within the M data engine,
which provides the tight integration of
applications to each other and to shared
data.
The data flow and integration
agreements between VISTA applications
(outer ring) is visualized as blue lines.
One Patient.
One Database.
All Apps.
All Data.
Integrated.
VISTA: A Patient-Centric EHR
9. Fileman: FM hierarchical-graph store
Rafael Richards MD MS 2014
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VISTA Data Model
VISTA is based on a hybrid NoSQL database. Unlike some NoSQL stores, VISTA is
schema-driven, not schema-less.
Inside every VISTA is File Manager (Fileman), a hybrid hierarchal-graph data store,
which is overlaid on top of the M multidimensional store. A comprehensive
definition of the types of data stored in every VA FileMan represents the VA's
Enterprise Data Model.
With an exposed data model, VISTA’s native schema be rendered in a standard
definition format and analyzed for use and improvement. A schema-flexible
information model representation language that is fully machine-processable such as
RDF provides such capability.
M
M: Multidimensional NoSQL data engine
M
10. Rafael Richards MD MS 2014
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VISTA’s native data model is
comprised of hierarchical
files and subfiles, each
which addresses a specific
M Global storage.
10
VISTA Data Model
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VISTA Query: Fileman Query Language
FMQL is the Fileman Query Language
that leverages the native hierarchical-graph
model of VISTA. This provides
real-time web-based query access to
the entirety of VistA’s data.
This exposes the native hierarchical
data model of Fileman in web
standard forms including HTML,
JSON, and RDF.
HTML: Hypertext markup language (visual document markup)
JSON: Javascript object notation (data serialization / packaging)
RDF: Resource description framework (linked data / semantics)
JSON-LD: JSON-like serialization of Linked Data (RDF)
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VISTA Query: HTML output
Fileman query of VistA for vital signs with output in HTML.
HTML output:
Human-readable
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VISTA Query: RDF output
Fileman query of VistA for vital signs with output in RDF.
RDF output:
Machine readable
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Linked Data: What is it?
The World Wide Web Consortium (W3C) standard for
semantic information integration for the Internet of Data.
HTML (hypertext markup language)
For humans to exchange information
RDF (resource description framework)
For computers to exchange information
Linked Documents
(Document Web)
Linked Data
(Semantic Web)
enables
enables
“The Semantic Web [Linked Data] provides a common framework that
allows data to be shared and reused across application, enterprise, and
community boundaries.”
Tim Berners-Lee, MIT Professor and Inventor of the World Wide Web
(HTML and RDF protocols)
15. Linking media, geographic, publications, government, and life sciences….
Rafael Richards MD MS 2014
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Linked Data
This represents over 300 linked data
sources and databases, comprising
billions of data elements and
millions of semantic links.
Each on of these circles represents
a data source, which is semantically
linked to other data sources,
creating one virtual federated
queryable web of data.
Wikipedia is one of the resources
converted to Linked Data, and is
called DBpedia (center circle).
15
Linked Data and the Internet of Data
Why not link
healthcare?
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VISTA Vitals in RDF
239 instances in the sample dataset
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FHIR: Native model
• FHIR - Observation
• XML model in XML Schema
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FHIR in RDF
Automated transformation from FHIR XML Schema - RDF
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RDF Translation Rules options
There are many options for RDF translation. For this case study we will use
the SPARQL Inferencing Notation (SPIN) because it is a W3C standard.
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SPIN: SPARQL rules language
http://spinrdf.org/spin-architecture.html
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SPINMap: Data mapping rules engine
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SPINMap: Data mapping rules engine
Motivation:
– Simplifies mappings between different models
Key Features:
– Creates executable transformations
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SPINMap: Field mapping with rules
Easier to create deep nested structures in the target
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SPINMap: Rules for LOINC terminology
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SPINMap Output: Linked Vitals
Same As
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Summary of Translation Approach
Rule-based mapping
Model alignment
Vocabulary alignment
Common syntax within
model-flexible medium
(Linked Data)
Syntactic
alignment
Fileman
Semantic
alignment
Source
Data
Integrated
Data
Different Syntax
Different Models
Different Vocabularies
Common Syntax
Common Model
Common Vocabulary
Common Meaning
Syntax A
Model A
Vocabulary A
Syntax B
Model B
Vocabulary B
Neutral
Model
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Linked Vitals: A step towards Linked Health
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In the works..
Web-based automation
of semantic alignment
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VISTA-FHIR web-based translation
The VISTA– FHIR prototype is a web-based application built with TopBraid and Semantic
Web Page technology. The application demonstrates semantic data integration of VistA
records and FHIR records.
The control bar shows the steps in the demonstration
Sub-steps are shown as
buttons. An “Explain” button is
provided for each sub-step.
The number of vital signs
records are shown across all
patients in the dataset