About OPCRD

Optimum Patient Care Research Database (OPCRD) is a real-world, longitudinal, research database that provides anonymised data to support scientific, medical, public health and exploratory research. OPCRD is established, funded and maintained by Optimum Patient Care Limited (OPC) – which is a not-for-profit social enterprise that has been providing quality improvement programmes and research support services to general practices across the UK since 2005.

Key Features of OPCRD

OPCRD has been purposefully designed to facilitate real-world data collection and address the growing demand for observational and pragmatic medical research, both in the UK and internationally. Data held in OPCRD is representative of routine clinical care and thus enables the study of ‘real-world’ effectiveness and health care utilisation patterns for chronic health conditions.

OPCRD unique qualities which set it apart from other research data resources: • De-identified electronic medical records of more than 24.9 million patients • OPCRD covers all major UK primary care clinical systems • OPCRD covers approximately 35% of the UK population • One of the biggest primary care research networks in the world, with over 1,175 practices • Linked patient reported outcomes for over 68,000 patients including Covid-19 patient reported data • Linkage to secondary care data sources including Hospital Episode Statistics (HES)

Data Available in OPCRD

OPCRD has received data contributions from over 1,175 practices and currently holds de-identified research ready data for over 24.9 million patients or data subjects. This includes longitudinal primary care patient data and any data relevant to the management of patients in primary care, and thus covers all conditions. The data is derived from both electronic health records (EHR) data and patient reported data from patient questionnaires delivered as part of quality improvement. OPCRD currently holds over 68,000 patient reported questionnaire data on Covid-19, asthma, COPD and rare diseases.

Approvals and Governance

OPCRD has NHS research ethics committee (REC) approval to provide anonymised data for scientific and medical research since 2010, with its most recent approval in 2020 (NHS HRA REC ref: 20/EM/0148). OPCRD is governed by the Anonymised Data Ethics and Protocols Transparency committee (ADEPT). All research conducted using anonymised data from OPCRD must gain prior approval from ADEPT. Proceeds from OPCRD data access fees and detailed feasibility assessments are re-invested into OPC services for the continued free provision of patient quality improvement programmes for contributing practices and patients.

For more information on OPCRD please visit: https://opcrd.co.uk/

Comprehensive aggregated access to over 50 million medical research records focusing on women's health, sourced from PubMed, Cochrane, Europe PMC, CrossRef, and ClinicalTrials.gov with real-time quality indicators

The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

A database containing details of water-related researchers located in Irish academic institutions

2011 Census data for England and Wales, linked to Mortality Data, Hospital Episode Statistics (HES) data, and GP Extraction Service (GPES) data for Pandemic Planning and Research Data.

Background: There have been some reports on the coexistence of psoriasis and atopic dermatitis; however, the longitudinal relationship between these two diseases remains unclear. Objective: This study aimed to investigate the bidirectional association between psoriasis and atopic dermatitis. Methods: This cohort study recruited patients from the National Health Insurance Research Database in Taiwan. We included 8,206 patients with psoriasis and 32,824 matched controls to assess the risk of atopic dermatitis and 25,743 patients with atopic dermatitis and 102,972 matched controls to assess the risk of psoriasis. Cox regression model was used for the analyses. Results: After adjusting for potential confounders, patients with psoriasis had a higher risk of atopic dermatitis (adjusted hazard ratio [aHR] 13.01; 95% CI 10.23–16.56) than the controls. Patients with atopic dermatitis had a higher risk of psoriasis (aHR 10.37; 95% CI 6.85–15.69) than the controls. Stratified analyses revealed similar results in both sexes and all age groups. Conclusion: Our study demonstrated a bidirectional association between psoriasis and atopic dermatitis, suggesting that psoriasis and atopic dermatitis are not mutually exclusive and may share some biological mechanisms.

The dataset presents a timeline and database of sustainability-related, innovative, and inclusive participation and engagement practices in Europe since the early days of digitalisation. The data reported here was assembled from Democratic Innovations collected from publicly accessible sources (Partecipedia, OECD's database of Representative Deliberate Processes and Institutions, Knowledge Network on Climate Assemblies (KNOCA), G1000, and the International Observatory on Participatory Democracy), with a specific focus on their contribution to social and environmental sustainability. By mapping the dynamics of implementation of Democratic Innovations across Europe, the dataset provides valuable insights into the potential for these innovations to foster more inclusive and resilient societies in line with social and environmental development goals. Each of the cases collected here was categorised on specific criteria, like geographical distribution, scales of governance, policy areas, citizen involvement, and digitalization.

INCITE-DEM is funded by the European Union (INCITE-DEM, GA nº 101094258). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the European Research Executive Agency (REA). Neither the European Union nor the granting authority (REA) can be held responsible for them

This is a source of data about funding, projects and outputs related to research on extreme weather events. It was co-ordinated by the New Zealand Research Information System team to enable the sharing of ideas across the science and innovation sector during New Zealand’s response to the extreme weather events of 2023 including Cyclone Gabrielle.

A CSV, xlsx and Accdb file containing an inventory list with all public records of Gandhara Palettes with associated data such as recorded provenance based on publications and museum catalogues, general descriptions of the material involved in each palette's construction, as well as periodization based on said publications. In addition, phasing is provided to enable for comparative analysis of various descriptions. In addition, links to museum catalogues are povided, as are citations and descriptions of the data itself. All data was collected from relevant bibliography such as excavation reports, previously compiled lists and museum catalogues to provide a new and updated list of the palettes, alongside important contextual information for future studies.

Updated in May 2023 with added information on the regional and local provenance of the palettes at hand. It also contains further qualitative information in terms of the fragmentation of the palettes, as well as possible religious and mythological interpretations. The chronology has been streamlined and re-organized to make it more usable for statistical analysis, as well as providing a column describing the nature of compartments as well as additional information on the nature of the scenes (whether they show a narrative or an event).

The third update (Jan 2024) has added new entries from existing literature, as well as their descriptions and citations. In addition, updates on the citations where they are found have been updated, and these citations have been fixed to make navigation in the database easier.

TOLNet_LaRC_Data is the lidar data collected by the Langley Mobile Ozone Lidar (LMOL) at NASA Langley Research Center (LaRC) as part of the Tropospheric Ozone Lidar Network (TOLNet). Data collection for this product is ongoing.In the troposphere, ozone is considered a pollutant and is important to understand due to its harmful effects on human health and vegetation. Tropospheric ozone is also significant for its impact on climate as a greenhouse gas. Operating since 2011, TOLNet is an interagency collaboration between NASA, NOAA, and the EPA designed to perform studies of air quality and atmospheric modeling as well as validation and interpretation of satellite observations. TOLNet is currently comprised of seven Differential Absorption Lidars (DIAL). Each of the lidars are unique, and some have had a long history of ozone observations prior to joining the network. Five lidars are mobile systems that can be deployed at remote locations to support field campaigns. This includes the Langley Mobile Ozone Lidar (LMOL) at NASA Langley Research Center (LaRC), the Tropospheric Ozone (TROPOZ) lidar at the Goddard Space Flight Center (GSFC), the Tunable Optical Profile for Aerosol and oZone (TOPAZ) lidar at the NOAA Chemical Sciences Laboratory (CSL) in Boulder, Colorado, the Autonomous Mobile Ozone LIDAR instrument for Tropospheric Experiments (AMOLITE) lidar at Environment and Climate Change Canada (ECCC) in Toronto, Canada, and the Rocket-city O3 Quality Evaluation in the Troposphere (RO3QET) lidar at the University of Alabama in Huntsville, Alabama. The remaining lidars, the Table Mountain Facility (TMF) tropospheric ozone lidar system located at the NASA Jet Propulsion Laboratory (JPL), and City College of New York (CCNY) New York Tropospheric Ozone Lidar System (NYTOLS) are fixed systems.TOLNet seeks to address three science objectives. The primary objective of the network is to provide high spatio-temporal measurements of ozone from near the surface to the top of the troposphere. Detailed observations of ozone structure allow science teams and the modeling community to better understand ozone in the lower-atmosphere and to assess the accuracy and vertical resolution with which geosynchronous instruments could retrieve the observed laminar ozone structures. Another objective of TOLNet is to identify an ozone lidar instrument design that would be suitable to address the needs of NASA, NOAA, and EPA air quality scientists who express a desire for these ozone profiles. The third objective of TOLNET is to perform basic scientific research into the processes create and destroy the ubiquitously observed ozone laminae and other ozone features in the troposphere. To help fulfill these objectives, lidars that are a part of TOLNet have been deployed to support nearly ten campaigns thus far. This includes campaigns such as the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission, the Korea United States Air Quality Study (KORUS-AQ), the Tracking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign, the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ), the Long Island Sound Tropospheric Ozone Study (LISTOS), and the Ozone Water–Land Environmental Transition Study (OWLETS).

Road traffic accidents remain to be a leading cause of death worldwide with roughly 1.3 million fatalities annually. To develop new safety approaches according to real-world challenges, accurate information is needed. Therefore, road safety experts are constantly looking for real-world data to answer the open challenges and ultimately reach “Vision Zero”.The Global Safety Database (GSD) offers access to an one of its kind up-to-date repository of road traffic accident statistics and databases on a meta-data level for road safety analyses.One main objective is the compilation of international data sources, for which a data management system has been developed. In addition to the inventory of road accident data sources, a questionnaire created by road safety experts is used to check the applicability of data sources for specific questions. Therefore, an automated and dynamic matching process enables comparing variables representing the questions with the existing data source content in the GSD. The results are stored in a result matrix which indicates the proportion of variables that correspond to the variables necessary to answer the research question for each data source investigated. In order to identify similarities and differences in road safety within the countries, a clustering methodology is developed to point out the possibilities and limitations of projecting information from the initial countries to other areas. The assessment of the representativeness of the individual data sources is the basis for the clustering. From a general perspective, the GSD is an essential tool pushing forward the worldwide harmonisation of traffic accident statistics and databases. Knowledge about the real-world accident scenery by bringing important databases together empowers the data-driven development which is eventually a key bringing us one step closer to a road system without casualties, the achievement of the Vision Zero.

The National Bioscience Database Center (NBDC) intends to integrate all databases for life sciences in Japan, by linking each database with expediency to maximize convenience and make the entire system more user-friendly. We aim to focus our attention on the needs of the users of these databases who have all too often been neglected in the past, rather than the needs of the people tasked with the creation of databases. It is important to note that we will continue to honor the independent integrity of each database that will contribute to our endeavor, as we are fully aware that each database was originally crafted for specific purposes and divergent goals. Services: * Database Catalog - A catalog of life science related databases constructed in Japan that are also available in English. Information such as URL, status of the database site (active vs. inactive), database provider, type of data and subjects of the study are contained for each database record. * Life Science Database Cross Search - A service for simultaneous searching across scattered life-science databases, ranging from molecular data to patents and literature. * Life Science Database Archive - maintains and stores the datasets generated by life scientists in Japan in a long-term and stable state as national public goods. The Archive makes it easier for many people to search datasets by metadata in a unified format, and to access and download the datasets with clear terms of use. * Taxonomy Icon - A collection of icons (illustrations) of biological species that is free to use and distribute. There are more than 200 icons of various species including Bacteria, Fungi, Protista, Plantae and Animalia. * GenLibi (Gene Linker to bibliography) - an integrated database of human, mouse and rat genes that includes automatically integrated gene, protein, polymorphism, pathway, phenotype, ortholog/protein sequence information, and manually curated gene function and gene-related or co-occurred Disease/Phenotype and bibliography information. * Allie - A search service for abbreviations and long forms utilized in life sciences. It provides a solution to the issue that many abbreviations are used in the literature, and polysemous or synonymous abbreviations appear frequently, making it difficult to read and understand scientific papers that are not relevant to the reader's expertise. * inMeXes - A search service for English expressions (multiple words) that appear no less than 10 times in PubMed/MEDLINE titles or abstracts. In addition, you can easily access the sentences where the expression was used or other related information by clicking one of the search results. * HOWDY - (Human Organized Whole genome Database) is a database system for retrieving human genome information from 14 public databases by using official symbols and aliases. The information is daily updated by extracting data automatically from the genetic databases and shown with all data having the identifiers in common and linking to one another. * MDeR (the MetaData Element Repository in life sciences) - a web-based tool designed to let you search, compare and view Data Elements. MDeR is based on the ISO/IEC 11179 Part3 (Registry metamodel and basic attributes). * Human Genome Variation Database - A database for accumulating all kinds of human genome variations detected by various experimental techniques. * MEDALS - A portal site that provides information about databases, analysis tools, and the relevant projects, that were conducted with the financial support from the Ministry of Economy, Trade and Industry of Japan.

Comprehensive collection of peer-reviewed scientific studies and clinical research supporting the efficacy, safety, and mechanisms of action of NerveFlow. This dataset includes published research from reputable medical journals and institutions.

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

R&D Database provides Vehicle Crash Test data, Biomechanics Test Data, and Component Test Data to support NHTSA's motor vehicle and traffic safety goals.

The ARS Culture Collection is one of the largest public collections of microorganisms in the world, containing approximately 93,000 strains of bacteria and fungi. The collection is split into subcollections of molds, prokaryotes, and yeasts. In addition, the online catalog is searchable by genus, species, subvar type, and subspecies.The collection is housed within the Mycotoxin Prevention and Applied Microbiology Research Unit at the National Center for Agricultural Utilization Research in Peoria, Illinois. The scientists and staff of the ARS Culture Collection conduct and facilitate microbiological research that advances agricultural production, food safety, public health, and economic development. These goals are pursued through in-house research that improves understanding and utilization of microbiological diversity and through efforts to enhance the value and accessibility of microbial accessions in the Agricultural Research Service Culture Collection.Resources in this dataset:Resource Title: The ARS Culture (NRRL) Collection Online Catalog.File Name: Web Page, url: https://nrrl.ncaur.usda.gov/ Online catalog and database server for the ARS Culture Collection (NRRL).

The Stanley Online Genomics Database uses samples from the Stanley Medical Research Institute (SMRI) Brain Bank. These samples were processed and run on gene expression arrays by a variety of researchers in collaboration with the SMRI. These researchers have performed analyses on their respective studies using a range of analytic approaches. All of the genomic data have been aggregated in this online database, and a consistent set of analyses have been applied to each study. Additionally, a comprehensive set of cross-study analyses have been performed. A thorough collection of gene expression summaries are provided, inclusive of patient demographics, disease subclasses, regulated biological pathways, and functional classifications. Raw data is also available to download. The database is derived from two sets of brain samples, the Stanley Array collection and the Stanley Consortium collection. The Stanley Array collection contains 105 patients, and the Stanley Consortium collection contains 60 patients. Multiple genomic studies have been conducted using these brain samples. From these studies, twelve were selected for inclusion in the database on the basis of number of patients studied, genomic platform used, and data quality. The Consortium collection studies have fewer patients but more diversity in brain regions and array platforms, while the Array collection studies are more homogenous. There are tradeoffs, the Consortium results will be more variable, but findings may be more broadly representative. The collections contain brain samples from subjects in four main groups: Bipolar Schizophrenia, Depression, and Controls Brain regions used in the studies include: Broadman Area 6, Broadman Area 8/9, Broadman Area 10, Broadman Area 46, Cerebellum The 12 studies encompass a range of microarray platforms: Affymetrix HG-U95Av2, Affymetrix HG-U133A, Affymetrix HG-U133 2.0+, Codelink Human 20K, Agilent Human I, Custom cDNA Publications based on any of the clinical or genomic data should credit the Stanley Medical Research Institute, as well as any individual SMRI collaborators whose data is being used. Publications which make use of analytic results/methods in the database should additionally cite Dr. Michael Elashoff. Registration is required to access the data.

R&D Database provides Vehicle Crash Test data, Biomechanics Test Data, and Component Test Data to support NHTSA's motor vehicle and traffic safety goals.

Neutron scattering data from NCNR's thermal and cold neutron scattering instruments.