Graphs Opening Medical Care Information - Dave Fauth @ GraphConnect NY 2013

Panel presentation on public access at the American Association of Publisher/Professional and Scholarly Division (AAP/PSP) Annual Meeting, February 2014

ORCID Presentation at the Japan Library Fair, Yokohama, 6 November 2014, by Lauel Haak, Executive Director, ORCID

MD Anderson Cancer Center implemented Hadoop to help manage and analyze big data as part of its big data program. The implementation included building Hadoop clusters to store and process structured and unstructured data from various sources. Lessons learned included that implementing Hadoop is complex and a journey, and to leverage existing strengths, collaborate openly, learn from experts, start with one cluster for multiple uses cases, and follow best practices. Next steps include expanding the Hadoop platform, ingesting more data types, identifying high value use cases, and developing and training people with new big data skills.

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

This document summarizes a presentation given by Laurel Haak on ORCID identifiers. ORCID aims to uniquely identify researchers and link them to their work, such as publications, datasets, and grants. It discusses how ORCID identifiers can be integrated into author workflows and research systems. Over 160 organizations from different sectors have joined ORCID as members. Usage of ORCID is growing internationally, with over 1 million identifiers issued. The presentation outlines how different stakeholders like universities, funders, and repositories can connect with ORCID to link researcher profiles with their systems and activities.

At Lake B2B we have been assisting marketers with medical mailing lists for years. With data from across countries, our list of Doctors is the outcome of years of research. Data present in the database therefore is accurate, verified and authentic, making it possible for marketers to rest assured of deliverables when using it. Marketers have according used the Doctors mailing addresses for generating business leads, adding new customers, reducing sales cycle time, up-selling and cross-selling products and more. So make a difference to your campaigns by using the right data at the right time. Get our Doctors mailing database now and get more from your marketing initiatives by adopting a strategic approach. Contact Us: http://www.lakeb2b.com/contact-us/ Call Us (Toll Free): 800-710-5516 Email Us: info@lakeb2b.com Website : http://www.lakeb2b.com/doctors-mailing-list-and-email-addresses/

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.

Talk delivered at YOW! Developer Conferences in Melbourne, Brisbane and Sydney Australia on 1-9 December 2016. Abstract: Governments collect a lot of data. Data on air quality, toxic chemicals, laws and regulations, public health, and the census are intended to be widely distributed. Some data is not for public consumption. This talk focuses on open government data — the information that is meant to be made available for benefit of policy makers, researchers, scientists, industry, community organisers, journalists and members of civil society. We’ll cover the evolution of Linked Data, which is now being used by Google, Apple, IBM Watson, federal governments worldwide, non-profits including CSIRO and OpenPHACTS, and thousands of others worldwide. Next we’ll delve into the evolution of the U.S. Environmental Protection Agency’s Open Data service that we implemented using Linked Data and an Open Source Data Platform. Highlights include how we connected to hundreds of billions of open data facts in the world’s largest, open chemical molecules database PubChem and DBpedia. WHO SHOULD ATTEND Data scientists, software engineers, data analysts, DBAs, technical leaders and anyone interested in utilising linked data and open government data.

The document provides an overview of the Crohn's Disease Disease and Therapy Review report. The report provides global incidence and prevalence numbers for Crohn's disease, information on diagnosis, an overview of treatments including dosing and costs. It also includes details on the market size and trends for Crohn's disease drugs and therapies. The Disease and Therapy Review series are produced by Timely Data Resources to provide concise summaries of diseases, treatments, and market opportunities.

7 November 2016 Find out more at http://ukorcidsupport.jisc.ac.uk/2016/10/join-us-for-our-next-orcid-webinar-on-7th-november-2016/

The Digitising Scotland project is having the vital records of Scotland transcribed from images of the original handwritten civil registers . Linking the resulting dataset of 24 million vital records covering the lives of 18 million people is a major challenge requiring improved record linkage techniques. Discussions within the multidisciplinary, widely distributed Digitising Scotland project team have been hampered by the teams in each of the institutions using their own identification scheme. To enable fruitful discussions within the Digitising Scotland team, we required a mechanism for uniquely identifying each individual represented on the certificates. From the identifier it should be possible to determine the type of certificate and the role each person played. We have devised a protocol to generate for any individual on the certificate a unique identifier, without using a computer, by exploiting the National Records of Scotland•À_s registration districts. Importantly, the approach does not rely on the handwritten content of the certificates which reduces the risk of the content being misread resulting in an incorrect identifier. The resulting identifier scheme has improved the internal discussions within the project. This paper discusses the rationale behind the chosen identifier scheme, and presents the format of the different identifiers. The work reported in the paper was supported by the British ESRC under grants ES/K00574X/1(Digitising Scotland) and ES/L007487/1 (Administrative Data Research Center - Scotland).

RDF, Knowledge Graphs, and ontologies enable companies to produce and consume graph data that is interoperable, sharable, and self-describing. GSK has set out to build the world’s largest medical knowledge graph to provide our scientists access to the world’s medical knowledge, also enable machine learning to infer links between facts. These inferred links are the heart of gene to disease mapping and is the future of discovering new treatments and vaccines. To power RDF sub-graphing, GSK has developed a set of open-source libraries codenamed “Project Bellman” that enable Sparql queries over partitioned RDF data in Apache Spark. These tools provide the ability to scale up to Sparql querying over trillions of RDF triples, provide point-in-time queries, and provide incremental data updates to downstream consumer applications. These tools are used by both GSK’s Ai/ML team to discover gene to disease mappings, and GSK’s scientists to query over the world’s medical knowledge.

The document discusses CrossRef's multiple resolution feature, which allows a single DOI to resolve to multiple URLs. It describes how a primary depositor can work with secondary depositors to set up multiple resolution for a DOI. The primary depositor notifies CrossRef and uses a flag to unlock the DOI for secondary depositors. Secondary depositors then submit their URL mappings which get added to the DOI resolution.

The document discusses ORCID, a system for providing researchers with unique identifiers. It notes that without identifiers, it is difficult to accurately connect researchers with their work. ORCID aims to address this by assigning each researcher a unique 16-digit number and ID and enabling the import and export of researcher profiles and publication data between different systems. The document outlines how ORCID is being integrated into publishing, funding, and other research workflows to link researcher profiles with their activities.

Overview of ORCID featuring auto-update, peer reviews and books. Presented by Alice Meadows at Crossref LIVE Seoul, 12 June 2017.

High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are of increasing interest in chemical forensics for the identification of emerging contaminants and chemical signatures of interest. At the US Environmental Protection Agency, our research using HRMS for non-targeted and suspect screening analyses utilizes databases and cheminformatics approaches that are applicable to chemical forensics. The CompTox Chemicals Dashboard is an open chemistry resource and web-based application containing data for ~900,000 substances. Basic functionality for searching through the data is provided through identifier searches, such as systematic name, trade names and CAS Registry Numbers. Advanced Search capabilities supporting mass spectrometry include mass and formula-based searches, combined substructure-mass searches and searching experimental mass spectral data against predicted fragmentation spectra. A specific type of data mapping in the underpinning database, using “MS-Ready” structures, has proven to be a valuable approach for structure identification that links structures that can be identified via HRMS with related substances in the form of salts, and other multi-component mixtures that are available in commerce. These MS-Ready structures have been used as an input set for computational MS-fragmentation to provide a database against which to search experimental data for spectral matching. This presentation will provide an overview of how the CompTox Chemicals Dashboard supports structure identification and non-targeted analysis in chemical forensics. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

This document summarizes Rafael Richards' presentation on using linked data and semantic web technologies to enable semantic interoperability between health data systems like the VA's VISTA EHR and the HL7 FHIR standard. It describes the challenges of integrating data between different models and vocabularies. The approach taken was to map both VISTA and FHIR data to a common linked data model using rules, then apply semantic reasoning techniques to align the models and vocabularies. This allows the data from both systems to be queried and integrated while supporting independent evolution of the source models.

This talk covers a basic intro of graphs, NOSQL and graph databases, followed b a number of domain examples and case studies, and a section on how graph databases can be interesting in the domain of insurance companies.

This webinar covers tips and strategies for using data analytics to find fraud. The webinar was led by Maribeth Vander Weele, investigation expert, an Inspector General and founder of the Vander Weele Group LLC. To watch the webinar recording, visit: http://i-sight.com/webinar-finding-fraud-through-data-analytics/

Fraud is a crime and civil violation involving intentional deception for personal gain, costing the global healthcare system an estimated $415 billion annually. Data analytics can help detect fraud through identifying anomalies like duplicate claims, age/gender-specific procedures outliers, and physicians billing outside their specialty. Singapore suspended two dental clinics for continuously breaching rules through non-matching claims and procedures not performed. Data analytics provides a defense against fraud through monitoring for irregularities.

The presentation discusses how big data and population health management tools can help reduce healthcare costs and improve outcomes. It explains that big data allows for deeper analysis of existing data to make better business decisions. Advanced analytics can help identify opportunities to improve clinical quality and financial performance. With proper outreach and lifestyle changes, big data tools may enable fewer hospital visits.

Government enforcement actions against health care companies are increasing. The Department of Justice has recovered more than $2 billion in health care false claims cases in each of the last five years. In 2014, the DOJ recovery was $2.3 billion. Health care fraud is an issue for any company that deals in health care, as well as for private equity firms, lenders, and underwriters. Winston health care partners Tom Mills and Marion Goldberg led an informative eLunch on what you should be aware of if you are involved in health care. Topics included: • Current government focus • Recent enforcement actions • What you should be alerted to if you are a health care company • What to look for in the diligence process if you are investing, financing, or underwriting a health care company

Review of fraud detection and one example of graph analysis Mahdi Esmailoghli Amirkabir University of Technology(Tehran Polytechnic)

The document discusses using Neo4j and graph databases for fraud detection solutions. It describes how Neo4j allows for agile development, high productivity, and real-time response times when working with connected fraud data. The document outlines a fraud detection demo using Neo4j to load operational data, inject fraud cases, generate alerts, and export detected fraud data for investigation. It proposes using Neo4j as the foundation for a 360-degree fraud prevention solution integrated with other systems and data sources.

The document discusses how various types of graphs are used in medical contexts. Hospitals use pain scales to assess patient pain levels and treatment needs. Vital signs like heart rate and blood pressure are often graphed electronically. Line and curve graphs are commonly used to monitor things like sleep apnea, cholesterol levels, blood glucose levels, and disease outbreaks over time. Other graphs show concepts like body mass index, sleep patterns, and the glycemic index of foods. Reflexology uses charts to map pressure points on hands and feet to different body parts.

Linking and mapping PDMP data can provide several benefits but also faces challenges. Linking PDMP and clinical data allows for evaluating the impact of PDMP interventions on outcomes and prescribing decisions. However, obtaining permissions and data is difficult due to legal and resource barriers. Mapping PDMP data using GIS tools in Washington identified areas for targeting overdose prevention efforts by visualizing patterns in prescribing risks, treatment availability, and overdoses. Stakeholders used these maps to guide education and funding decisions. Sustaining these tools requires ongoing funding and expanding included data sources.

This document summarizes a presentation on linking and mapping prescription drug monitoring program (PDMP) data. It discusses the benefits of linking PDMP data to clinical data, including improving patient safety, evaluating prescribing decisions, and assessing the impact of PDMP interventions. It describes challenges with linking data, such as obtaining consent and negotiating data use agreements. It also discusses Washington State's MAPPING OPIOID AND OTHER DRUG ISSUES (MOODI) tool, which integrates PDMP data with other databases to map and target treatment and overdose prevention efforts at the community level.

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Flextracker presentation at http://2013.desarrollandoamerica.org/dal-en-argentina/ by Laercio Simoes www.flextracker.net

The document discusses how big data and analytics can optimize clinical trial efficiency. It notes that unstructured data makes up 80% of useful information and is growing faster than structured data. Traditional clinical trial protocols rely on limited data sources like medical histories and questionnaires, whereas expanded protocols could incorporate a wider range of data sources like other medical records. Graphical displays of contextual analyses and intuitive interfaces can provide insights at a glance. Actionable analytics derived from big data could drive clinical trial efficiency by defining measures, answering questions, and leading directly to meaningful actions.