This file contains a national set of names and contact information for doctors, hospitals, clinics, and other facilities (known collectively as sources) from which medical evidence of record (MER) may be requested to support a claimant's disability application.

No description is available. Visit https://dataone.org/datasets/urn%3Auuid%3Afc37b5f2-f69b-497e-bb85-048a19e9950a for complete metadata about this dataset.

Type and description of the study variables, data sources, and reference period.

Reference Data Management Platform Market Outlook

According to our latest research, the global Reference Data Management Platform market size reached USD 4.2 billion in 2024, reflecting robust growth in recent years. The market is projected to expand at a CAGR of 13.1% from 2025 to 2033, reaching an estimated USD 12.5 billion by the end of the forecast period. This impressive trajectory is primarily driven by the increasing need for accurate and consistent data across complex enterprise environments, regulatory compliance requirements, and the accelerating adoption of digital transformation initiatives worldwide.

One of the primary growth factors fueling the Reference Data Management Platform market is the exponential rise in data volumes generated by organizations, particularly in highly regulated sectors such as BFSI, healthcare, and telecommunications. As enterprises expand their digital footprints, the demand for unified, accurate, and consistent reference data becomes critical for ensuring operational efficiency and informed decision-making. The proliferation of data sources and the growing complexity of IT environments have underscored the importance of robust reference data management solutions, which help organizations maintain data integrity, reduce redundancies, and minimize operational risks. Moreover, the increasing reliance on analytics and business intelligence tools further amplifies the necessity for high-quality, standardized reference data, thereby driving market growth.

Another significant growth driver is the tightening regulatory landscape, especially within sectors such as finance and healthcare. Regulatory bodies across regions are imposing stringent data governance and compliance mandates, compelling organizations to invest in advanced reference data management platforms. These platforms enable enterprises to establish comprehensive data governance frameworks, streamline compliance processes, and ensure adherence to industry standards such as GDPR, HIPAA, and Basel III. The growing emphasis on data transparency, auditability, and traceability is prompting organizations to adopt solutions that offer centralized control, automated data validation, and real-time monitoring. As a result, vendors are increasingly focusing on enhancing the compliance and governance capabilities of their offerings to cater to evolving regulatory requirements.

The rapid adoption of cloud-based solutions and the increasing trend towards digital transformation are also playing a pivotal role in shaping the Reference Data Management Platform market. Cloud deployment offers organizations the flexibility to scale operations, reduce infrastructure costs, and ensure seamless data access across geographically dispersed locations. The shift towards remote and hybrid work models has further accelerated the adoption of cloud-native reference data management platforms, enabling enterprises to maintain business continuity and agility. Additionally, advancements in artificial intelligence and machine learning are being integrated into these platforms to automate data classification, enhance data quality, and provide predictive insights, thereby unlocking new growth opportunities for market participants.

Regionally, North America continues to dominate the Reference Data Management Platform market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of major technology providers, early adoption of advanced data management solutions, and stringent regulatory frameworks in the United States and Canada are key factors contributing to the region's leadership. Europe is witnessing significant growth, driven by the increasing focus on data privacy and compliance, particularly in the financial services sector. Meanwhile, the Asia Pacific region is emerging as a lucrative market, supported by rapid digitalization, expanding IT infrastructure, and growing awareness about the benefits of effective data management practices among enterprises in countries such as China, India, and Japan.

Structured Data Management Software plays a crucial role in the efficient handling and organization of reference data across various industries. As organizations increasingly rely on data-driven strategies, the need for structured data management becomes paramount. This so

The reference data contains 65 referenced and cited literature sources from the writing process, including the title, author(s), source and other bibliographic information for each reference.The image data contains two images embedded within the body text of the paper.

The reference desk is the common challenge for all of us. We will be taking some great moments of the past year on the reference desk (yours included) and look at tools, referrals, and colleagial education that will make your life easier.

Guide to Publicly Available Demographic Data This data source guide is a reference tool describing data important to workforce professionals. We created the guide because multiple federal and state organizations provide data relevant to workforce professionals; and skillful data use requires understanding: the sources of data how often it is collected, for what years it is available, and a link to the data release dates the geographic level of analysis (state, county, etc.) the variables included in the data how to access and use the data

This data set shows all the sources recorded in the source register of North Rhine-Westphalia - independently managed by five institutions - or their sampling points based on the state's water stationing map (gsk3c). The attribute table provides information about the number, the location and the data holders of all within one Source surface represented objects and identifies the reference source. Sources from GeoBasis NRW - i.e. from the state survey - are always reference sources. All objects recorded within a radius of 10 m around the reference source are brought together under a source NRW_ID. Overlapping radii are combined to form a larger coherent headwaters. If there is no reference source from Geobasis NRW in an area, the source closest to the centroid represents the reference source.

For the purpose of transparency, this release includes 2 statistics referenced in SPI-M: The role of children in transmission (16 April 2020) on the wider impacts of educational closures:

• data on serious incident notifications for child deaths and serious harm
• Department for Education (DfE) estimates of the proportion of children of critical workers living in households where all adults are critical workers

Table of values used to parameterize and evaluate the Ft Carson NetZero integrated Model with published reference sources for each value. This dataset is associated with the following publication: Procter, A., O. Kaplan , and R. Araujo. Net Zero Fort Carson: Integrating Energy, Water, and Waste Strategies to Lower the Environmental Impact of a Military Base. JOURNAL OF INDUSTRIAL ECOLOGY. Berkeley Electronic Press, Berkeley, CA, USA, online, (2015).

Data sources list for Occurrence records of tropical Asian butterflies (1970-2024)

This presentation provides an introduction to aggregate data sources, primarily from Statistics Canada, that may be of value to those using GIS to explore the spatial distribution of Canadian socio-economic characteristics.

Increasing amounts of data is collected in most areas of research and application. The degree to which this data can be accessed, analyzed, and retrieved, is a decisive in obtaining progress in fields such as scientific research or industrial production. We present a novel methodology supporting content-based retrieval and exploratory search in repositories of multivariate research data. In particular, our methods are able to describe two-dimensional functional dependencies in research data, e.g. the relationship between ination and unemployment in economics. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models to describe the data mathematically. We denote this approach Regressional Features and use it for content-based search and, since our approach motivates an intuitive definition of interestingness, for exploring the most interesting data. We apply our method on considerable real-world research datasets, showing the usefulness of our approach for user-centered access to research data in a Digital Library system.

Reference Data Management Platform Market Outlook

According to our latest research, the global Reference Data Management Platform market size reached USD 3.45 billion in 2024, reflecting robust expansion fueled by increasing digitization and data governance initiatives across industries. The market is projected to grow at a CAGR of 11.2% during the forecast period, with the market value anticipated to reach USD 9.20 billion by 2033. Primary growth factors include the rising need for data accuracy, regulatory compliance, and operational efficiency in data-driven organizations worldwide.

One of the key drivers propelling the growth of the Reference Data Management Platform market is the escalating volume and complexity of enterprise data. Organizations are increasingly recognizing the importance of accurate, consistent, and centralized reference data to support mission-critical business processes, analytics, and reporting. The proliferation of digital transformation initiatives, coupled with the adoption of cloud computing and big data analytics, has heightened the need for robust reference data management solutions. As enterprises integrate disparate data sources and legacy systems, the demand for platforms that ensure data consistency, reduce redundancies, and enhance data governance is surging. This trend is particularly pronounced in highly regulated sectors such as BFSI, healthcare, and government, where data integrity is paramount for compliance and risk management.

Another significant growth factor is the intensification of regulatory requirements across various industries. Regulatory bodies worldwide are imposing stringent mandates around data management, privacy, and reporting, compelling organizations to adopt advanced reference data management platforms. These platforms enable enterprises to maintain accurate and auditable records, automate compliance workflows, and mitigate operational risks associated with data discrepancies. The increasing frequency of regulatory updates, particularly in financial services and healthcare, is driving continuous investments in reference data management technologies. Furthermore, the growing emphasis on data democratization and self-service analytics is encouraging organizations to implement platforms that provide business users with easy access to trusted reference data, thereby accelerating decision-making and innovation.

The rapid evolution of artificial intelligence (AI) and machine learning (ML) technologies is also contributing to the expansion of the Reference Data Management Platform market. AI-powered data management solutions are enabling organizations to automate data matching, cleansing, and enrichment processes, significantly reducing manual efforts and operational costs. These intelligent platforms can identify data anomalies, recommend corrective actions, and enhance the overall quality of reference data. The integration of AI and ML capabilities is expected to drive further innovation in the market, empowering enterprises to derive actionable insights from complex data sets and unlock new business opportunities. As organizations strive to harness the full potential of their data assets, the adoption of next-generation reference data management platforms is set to accelerate in the coming years.

From a regional perspective, North America continues to dominate the Reference Data Management Platform market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The presence of leading technology vendors, early adoption of digital solutions, and a mature regulatory landscape are key factors contributing to the region’s leadership. However, Asia Pacific is emerging as a high-growth market, driven by rapid industrialization, expanding IT infrastructure, and increasing investments in data management technologies. Countries such as China, India, and Japan are witnessing significant demand for reference data management platforms, particularly in BFSI, healthcare, and manufacturing sectors. As organizations across regions prioritize data governance and compliance, the global market is poised for sustained growth throughout the forecast period.

Component Analysis

The Component segment of the Reference Data Management Platform market is bifurcated into Software and Services, each playing a pivotal role in the overall market ecosystem. The software component encompasses core reference data management platform

This dataset contains PMID-to-PMID citations of PubMed 2020 Baseline extracted from five freely available bibliographic data sources (COCI, Dimensions, MAG, NIH-OCC, and S2ORC).

Each line contains one citing PubMed document and its cited references. The citing and cited documents are separated by a tab (\t) and the cited references are separated by a semicolon (;).

Public health-related decision-making on policies aimed at controlling the COVID-19 pandemic outbreak depends on complex epidemiological models that are compelled to be robust and use all relevant available data. This data article provides a new combined worldwide COVID-19 dataset obtained from official data sources with improved systematic measurement errors and a dedicated dashboard for online data visualization and summary. The dataset adds new measures and attributes to the normal attributes of official data sources, such as daily mortality, and fatality rates. We used comparative statistical analysis to evaluate the measurement errors of COVID-19 official data collections from the Chinese Center for Disease Control and Prevention (Chinese CDC), World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC). The data is collected by using text mining techniques and reviewing pdf reports, metadata, and reference data. The combined dataset includes complete spatial data such as countries area, international number of countries, Alpha-2 code, Alpha-3 code, latitude, longitude, and some additional attributes such as population. The improved dataset benefits from major corrections on the referenced data sets and official reports such as adjustments in the reporting dates, which suffered from a one to two days lag, removing negative values, detecting unreasonable changes in historical data in new reports and corrections on systematic measurement errors, which have been increasing as the pandemic outbreak spreads and more countries contribute data for the official repositories. Additionally, the root mean square error of attributes in the paired comparison of datasets was used to identify the main data problems. The data for China is presented separately and in more detail, and it has been extracted from the attached reports available on the main page of the CCDC website. This dataset is a comprehensive and reliable source of worldwide COVID-19 data that can be used in epidemiological models assessing the magnitude and timeline for confirmed cases, long-term predictions of deaths or hospital utilization, the effects of quarantine, stay-at-home orders and other social distancing measures, the pandemic’s turning point or in economic and social impact analysis, helping to inform national and local authorities on how to implement an adaptive response approach to re-opening the economy, re-open schools, alleviate business and social distancing restrictions, design economic programs or allow sports events to resume.

Reference Data Management Software Market Outlook

According to our latest research, the global reference data management software market size reached USD 3.2 billion in 2024, reflecting a robust expansion driven by the increasing need for data accuracy and regulatory compliance across industries. The market is projected to grow at a CAGR of 13.8% from 2025 to 2033, reaching approximately USD 9.2 billion by 2033. This significant growth is primarily fueled by advancements in data integration technologies, the proliferation of cloud-based solutions, and heightened emphasis on data governance and risk management in sectors such as BFSI, healthcare, and government.

One of the key growth factors propelling the reference data management software market is the escalating complexity of data ecosystems within organizations. As enterprises increasingly operate in multi-cloud and hybrid environments, the volume, variety, and velocity of data have surged exponentially. This complex data landscape necessitates robust reference data management solutions that can ensure data consistency, accuracy, and integrity across disparate systems. Industries such as banking, financial services, and insurance (BFSI) are particularly reliant on these solutions to streamline operations, mitigate risks, and comply with stringent regulatory requirements. The growing adoption of advanced analytics and artificial intelligence further amplifies the demand for high-quality reference data, as these technologies depend on reliable, standardized data sets to deliver actionable insights and drive strategic decision-making.

Another significant driver of market growth is the increasing regulatory scrutiny and compliance mandates imposed by governments and industry bodies worldwide. Regulatory frameworks such as GDPR in Europe, HIPAA in the United States, and similar data protection laws in other regions have heightened the need for organizations to maintain accurate and auditable reference data. Non-compliance can result in severe penalties, reputational damage, and operational disruptions. As a result, enterprises are investing heavily in reference data management software to automate compliance processes, enhance data traceability, and facilitate real-time reporting. This trend is particularly pronounced in sectors such as healthcare and government, where data privacy and security are paramount.

The rapid digital transformation across industries is also contributing to the robust expansion of the reference data management software market. Organizations are increasingly leveraging digital technologies to enhance customer experiences, optimize operations, and drive innovation. However, these digital initiatives often involve the integration of multiple data sources, applications, and platforms, which can lead to data silos and inconsistencies. Reference data management solutions play a critical role in addressing these challenges by providing centralized, standardized repositories of reference data that support seamless data integration and interoperability. This, in turn, enables organizations to realize the full potential of their digital transformation initiatives and gain a competitive edge in the market.

From a regional perspective, North America remains the largest market for reference data management software, accounting for a substantial share of global revenues in 2024. The region's dominance is attributed to the presence of leading technology vendors, high levels of IT spending, and stringent regulatory frameworks, particularly in the BFSI and healthcare sectors. However, the Asia Pacific region is emerging as a high-growth market, driven by rapid economic development, increasing digitalization, and growing awareness of data governance among enterprises. Europe also continues to witness steady growth, supported by robust regulatory compliance requirements and the widespread adoption of advanced data management solutions. Latin America and the Middle East & Africa are gradually catching up, with increasing investments in digital infrastructure and a growing focus on data-driven decision-making.

Component Analysis

The reference data management software market is segmented by component into software and services, each playing a distinct role in addressing the evolving needs of enterprises. The software segment comprises core reference data management platforms that offer functionalities such as data modeling, data validation, data integration, and w

This view provides an overall representation of the relative performance of tourism-related activities with respect to the reference period, over time and geography, as well as the grouped data sources which were used to create it.

A SQLite database containing mass absorption coefficient (both discrete and continuous), atomic sub-shell binding energy, X-ray energy, jump ratio, ground-state occupancy, atomic relaxation rate following core shell ionization and X-ray linewidth data. The data is in the common SQLite format and also available in SQL format. SQLite is an open-source database which is supported on many different platforms. This database represents a compilation of data from other sources. Each datum is labeled with a literature reference which represents the source. The references are listed in the LIT_REFERENCES table with associated BIBTEX reference data. The two exceptions to this rule are the FFAST and FFAST_EXTRA tables which are associated with the Chantler2005 reference.

The National Software Reference Library (NSRL) collects software from various sources and incorporates file profiles computed from this software into a Reference Data Set (RDS) of information. The RDS can be used by law enforcement, government, and industry organizations to review files on a computer by matching file profiles in the RDS. This alleviates much of the effort involved in determining which files are important as evidence on computers or file systems that have been seized as part of criminal investigations. The RDS is a collection of digital signatures of known, traceable software applications. There are application hash values in the hash set which may be considered malicious, i.e. steganography tools and hacking scripts. There are no hash values of illicit data, i.e. child abuse images.