Abstract

The page contains materials from the PHS Seminar on Weighting Techniques for Large Private Claims Data that was held on On October 24, 2024, as well as some additional documentation and the weights themselves.

Methodology

On October 24, 2024, PHS hosted a Seminar on Weighting Techniques for Large Private Claims Data. Using the MarketScan Commercial Database as an example case, Social Scientist Sarah Hirsch discussed three schemes for weighting private claims data using US census-based surveys, and the associated methods and techniques. She provided researchers with the tools to implement these methodologies, or to formulate their own for other datasets.

We invite you to view the Recording of the Seminar to learn more about this topic! The slide deck and transcript are also available for reference.

We have also added some code scripts, a written description of the weighting process, and the final MarketScan weights. Some additional have also been made related to the following:

• The region imputation.
• Patients from Puerto Rico (who are under a different survey from those employed here), who are being removed.
• Imputation based on non-null values in other years that were available for some people.

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The global patient portal market is experiencing robust growth, driven by increasing adoption of electronic health records (EHRs), rising demand for telehealth services, and a growing emphasis on patient engagement and empowerment. The market's expansion is fueled by several key factors. Firstly, the increasing digitization of healthcare systems is pushing providers to adopt patient portals as a crucial tool for enhancing communication and care coordination. Secondly, the rising prevalence of chronic diseases necessitates better patient monitoring and management, a function readily facilitated by these portals. Thirdly, governments and healthcare payers are increasingly incentivizing the use of technology to improve healthcare efficiency and reduce costs, further propelling the market's growth. The integration of patient portals with other healthcare technologies, such as telehealth platforms and wearable devices, is expanding their functionality and enhancing their appeal to both providers and patients. This integration streamlines data sharing, improves care coordination, and enhances the overall patient experience. Standalone portals remain popular, but the increasing adoption of integrated systems promises greater efficiency and data interoperability. The market is segmented by application (providers, pharmacies, employer groups and government bodies) and type (standalone and integrated portals), with the provider segment currently holding the largest share. Geographic growth is expected across all regions, with North America and Europe leading due to advanced healthcare infrastructure and higher adoption rates. However, Asia-Pacific is poised for significant growth in the coming years owing to increasing healthcare spending and technological advancements. Despite these positive trends, the market faces certain challenges. Interoperability issues across different healthcare systems can hinder the seamless exchange of patient data, a critical aspect for effective utilization of patient portals. Concerns about data privacy and security remain a significant restraint, requiring robust security measures and compliance with stringent regulations. Furthermore, the need for substantial upfront investment in infrastructure and training can limit adoption, particularly among smaller healthcare providers. However, the long-term benefits of improved patient care, increased efficiency, and reduced costs are likely to outweigh these challenges, leading to continued market expansion. The forecast period (2025-2033) anticipates sustained growth, driven by ongoing technological innovation, increasing regulatory support, and the evolving needs of both patients and healthcare providers. We estimate the market size to be approximately $15 Billion in 2025, growing at a CAGR of 12% over the forecast period.

Secure Data Sharing for Insurance Ecosystems Market Outlook

According to our latest research, the global Secure Data Sharing for Insurance Ecosystems market size reached USD 2.47 billion in 2024, with a robust compound annual growth rate (CAGR) of 19.1% projected through the forecast period. By 2033, the market is expected to attain a value of USD 10.98 billion, driven by rapid digital transformation, increasing regulatory scrutiny, and the growing need for secure, interoperable platforms within the insurance industry. As per the latest research, the market’s expansion is underpinned by the rising adoption of cloud-based solutions, advanced analytics, and blockchain technology, all of which are enabling more efficient and secure data exchange across the insurance value chain.

One of the primary growth drivers for the Secure Data Sharing for Insurance Ecosystems market is the escalating volume and sensitivity of data generated by insurance operations. The proliferation of digital touchpoints, such as mobile apps, online portals, and IoT-enabled devices, has exponentially increased data flows between insurers, brokers, agents, and third-party administrators. This surge in data exchange heightens the risk of breaches and data misuse, compelling organizations to invest in sophisticated secure data sharing solutions. Furthermore, the integration of artificial intelligence and machine learning into insurance processes, such as underwriting and claims management, necessitates secure, real-time access to vast datasets, further fueling market demand.

Regulatory compliance is another significant factor propelling the growth of secure data sharing solutions in insurance ecosystems. Stringent data protection frameworks like the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) in the United States, and similar regulations in Asia Pacific and other regions mandate rigorous standards for data privacy, consent, and auditability. Insurers are increasingly required to demonstrate robust data governance and secure sharing practices, not only to avoid hefty fines but also to maintain customer trust and competitive differentiation. As a result, regulatory compliance is catalyzing the adoption of advanced encryption, access controls, and blockchain-based audit trails in the insurance sector.

The rapid shift towards digital transformation and the adoption of cloud-based architectures are further accelerating the need for secure data sharing in insurance. Cloud platforms offer scalability, flexibility, and cost-efficiency, enabling insurers to collaborate more effectively with partners, reinsurers, and ecosystem participants. However, the migration to the cloud also introduces new security challenges, such as data residency, multi-tenancy risks, and complex access management. This has led to a surge in demand for specialized software, hardware, and managed services that can safeguard sensitive insurance data in hybrid and multi-cloud environments. Additionally, the rise of insurtech startups and ecosystem-driven innovation is expanding the market’s scope, as these new entrants prioritize secure, API-driven data exchange to deliver differentiated customer experiences.

From a regional perspective, North America currently dominates the Secure Data Sharing for Insurance Ecosystems market, accounting for the largest revenue share in 2024. This leadership is attributed to the region’s advanced digital infrastructure, high insurance penetration, and proactive regulatory environment. Europe follows closely, with significant investments in GDPR-compliant solutions and digital insurance initiatives. Meanwhile, Asia Pacific is emerging as the fastest-growing region, driven by rapid urbanization, digital adoption, and the rise of new insurance models. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as insurers in these regions increasingly recognize the strategic value of secure data sharing for operational efficiency and customer trust.

Component Analysis

A list of NIH-supported repositories that accept submissions of appropriate scientific research data from biomedical researchers. It includes resources that aggregate information about biomedical data and information sharing systems. Links are provided to information about submitting data to and accessing data from the listed repositories. Additional information about the repositories and points-of contact for further information or inquiries can be found on the websites of the individual repositories.

A unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.

The Fiscal Intermediary Shared System (FISS) Attending and Rendering dataset provides a list of those attending and rendering physicians for the FISS. FISS edits require that the Line Item Rendering Physician information be transmitted when providers submit a combined claim. Claims that include both facility and professional components, need to report the rendering physician or other practitioner at the line level if it differs from the rendering physician/practitioner reported at the claim level.

Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.

A selection of official and unofficial national open data portals gathered through a combination of queries and triangulating existing lists (e.g. https://dataportals.org/). Developed with support from King’s Undergraduate Research Fellowship (KURF) scheme in Summer 2021, with input from Sebastian Stros, Elena Wüllhorst, Khizer Sajid.

As per Cognitive Market Research's latest published report, the Global Insurance Claims Management market size was $15,764.89 Million in 2024 and it is forecasted to reach $22,340.54 Million by 2030. Insurance Claims Management Industry's Compound Annual Growth Rate was 6.09% from 2023 to 2030. Market Dynamics of the Insurance Claims Management Solution Market

Market Driver of the Insurance Claims Management Solution

Rising Demand for Faster and Error-Free Claims Processing: Insurers are adopting claims management solutions to reduce manual paperwork, minimize errors, and accelerate turnaround time. This automation improves customer satisfaction, reduces operational costs, and enhances competitive edge in an increasingly digital-first insurance ecosystem. Increasing Adoption of AI, Machine Learning, and Automation: Advanced technologies like AI and machine learning are transforming claims handling through intelligent fraud detection, predictive analytics, and automated decision-making. These features are driving adoption among insurers aiming to modernize legacy systems and streamline complex workflows. Growth of Health, Auto, and Property Insurance Segments: Expanding insurance coverage across sectors leads to a growing volume of claims. Scalable, cloud-based claims management platforms enable insurance firms to handle large claim inflows efficiently, especially in fast-growing health, vehicle, and disaster-related insurance categories.

Market Restraints of the Insurance Claims Management Solution Market

Increasing Demand for Swift and Accurate Claims Processing: Insurers are implementing claims management solutions to decrease manual documentation, lessen errors, and speed up turnaround times. This automation enhances customer satisfaction, lowers operational expenses, and strengthens competitive advantage in a progressively digital-centric insurance landscape. Rising Utilization of AI, Machine Learning, and Automation: Cutting-edge technologies such as AI and machine learning are revolutionizing claims processing through sophisticated fraud detection, predictive analytics, and automated decision-making. These capabilities are encouraging insurers to adopt modernized systems and simplify intricate workflows. Expansion of Health, Auto, and Property Insurance Sectors: The broadening of insurance coverage across various sectors results in an increasing number of claims. Scalable, cloud-based claims management systems allow insurance companies to manage substantial claim volumes effectively, particularly in rapidly expanding health, automotive, and disaster-related insurance segments.

Market Trends of the Insurance Claims Management Solution Market

Shift Toward Cloud-Based Claims Management Platforms: Cloud-based solutions provide scalability, cost-effectiveness, and remote accessibility, rendering them suitable for contemporary insurers. These platforms facilitate real-time data sharing, expedited updates, and smooth third-party integrations, prompting a shift from on-premise to cloud-native claims infrastructure. Integration of Customer Self-Service Portals and Mobile Apps: In order to improve transparency and minimize service delays, insurers are introducing mobile applications and portals that allow policyholders to submit claims, upload documents, and monitor claim status in real time. This movement enhances user experience while decreasing reliance on call centers. Emphasis on End-to-End Digital Transformation: Insurers are implementing comprehensive digital transformation strategies that encompass claims automation, CRM integration, chatbot assistance, and omnichannel communication. Claims management solutions are advancing into multifunctional platforms that provide support for analytics, compliance, fraud detection, and tailored customer engagement.

Opportunity for the Insurance Claims Management Solution Market

Predictive Maintenance for Claims Management is an opportunity for the market

The insurance claims management market has a new opportunity in leveraging predictive maintenance to improve claims management. Predictive maintenance enables insurers to anticipate and prevent potential claims, reducing losses and improving overall business performance. By leveraging predictive maintenance, insurers can develop more proactive claims management strategies, improving policyholder satisfaction and loyalty. By implementing predictive mainte...

The Open Data Portal (ODP) is our new hub for open data, built on the idea of finding several datasets in one platform so anyone can easily search and extract the data they need. The ODP is a unified platform that offers public patent data in one place. Enhanced APIs and robust documentation help improve the entire data experience. Customer demand for our data has grown rapidly since the launch of the original Open Data Portal initiative in 2015 � from 50 users to millions. The new Open Data Portal is the next step in the USPTO journey to amplify the public value, accessibility, and efficiency of patent data sharing. ODP will fold several data dissemination services into one central website that empowers you to rapidly discover and easily extract USPTO data however you want. Improved Patent Examination Data System (PEDS) capabilities, Bulk Data Storage System (BDSS), and Developer Hub features and datasets will be included in this tool.

IntroductionObtaining real-world data from routine clinical care is of growing interest for scientific research and personalized medicine. Despite the abundance of medical data across various facilities — including hospitals, outpatient clinics, and physician practices — the intersectoral exchange of information remains largely hindered due to differences in data structure, content, and adherence to data protection regulations. In response to this challenge, the Medical Informatics Initiative (MII) was launched in Germany, focusing initially on university hospitals to foster the exchange and utilization of real-world data through the development of standardized methods and tools, including the creation of a common core dataset. Our aim, as part of the Medical Informatics Research Hub in Saxony (MiHUBx), is to extend the MII concepts to non-university healthcare providers in a more seamless manner to enable the exchange of real-world data among intersectoral medical sites.MethodsWe investigated what services are needed to facilitate the provision of harmonized real-world data for cross-site research. On this basis, we designed a Service Platform Prototype that hosts services for data harmonization, adhering to the globally recognized Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) international standard communication format and the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Leveraging these standards, we implemented additional services facilitating data utilization, exchange and analysis. Throughout the development phase, we collaborated with an interdisciplinary team of experts from the fields of system administration, software engineering and technology acceptance to ensure that the solution is sustainable and reusable in the long term.ResultsWe have developed the pre-built packages “ResearchData-to-FHIR,” “FHIR-to-OMOP,” and “Addons,” which provide the services for data harmonization and provision of project-related real-world data in both the FHIR MII Core dataset format (CDS) and the OMOP CDM format as well as utilization and a Service Platform Prototype to streamline data management and use.ConclusionOur development shows a possible approach to extend the MII concepts to non-university healthcare providers to enable cross-site research on real-world data. Our Service Platform Prototype can thus pave the way for intersectoral data sharing, federated analysis, and provision of SMART-on-FHIR applications to support clinical decision making.

The data contained in this resource were uploaded from the WikiWatershed Data Sharing Portal – http://data.wikiwatershed.org. They were collected at a site named Smelly Lake. The full URL to access this site in the WikiWatershed Data Sharing portal is: http://data.wikiwatershed.org/sites/SMELL_LAKE/.

Instructions on the Open Data Portal process for the Open Data Team.This is a step by step instructional document detailing the following processes:PUBLISH DATA TO ARCGIS SERVER MANAGE WEB LAYERS IN PORTAL CREATE FEATURE LAYER IN ARCGIS ONLINEHOW TO ADD DOCUMENTS AND FILESSHARE STATIC FILES THROUGH THE COLLABORATIONCHANGE ITEMS OWNER TO OPEN_DATA_ADMIN

In the landscape of Open Science, Open Data [OD] plays a crucial role as data are one of the most basic components of research despite their diverse formats across scientific disciplines. Opening up data is a recent concern for policy makers and researchers as the basis for good open science practices. The common factor underlying these new practices – the relevance of promoting open data circulation and reuse – is mostly a social form of knowledge sharing and construction. However, while data sharing is being strongly promoted by policy making and is becoming a frequent practice in some disciplinary fields, open data sharing is much less developed in social sciences and in educational research.

The Open Data hereby introduced is composed of two integrated datasets which collect data relating practices of Open Data publication and sharing in the field of Educational Thecnologies. This data was collected to suport the aim of investigating open data sharing in a selection of open data repositories as well as in the academic social network site ResearchGate.

The research questions addressing this study are:

1. Do researchers in the field of Educational Technology publish Open Datasets [ODs]?
2. To which extent are ODs compliant with the FAIR data principles?
3. What is the social life relating to the ODs in terms of the metrics provided by the OD portals? As a subsidiary question: 3.a- To what extent do open data portals allow researchers to cultivate social practices around OD?

In order to investigate OD presence in ResearchGate, the following research aim guided the second part of the study: Analysis of the presence of the same selected OD in ResearchGate and of the type of social activity OD exhibited by OD according to ResearchGate mètrics.

The Open Data here presented is composed by two datasets.

1. 23 datasets extracted out from 82 randomly selected datasets, from an inital total of 633. The data set presents a Codebook explaining the several categories of analysis or variables and the values assigned to the same. Since the analysis was performed in two phases (first selection and screening, second selection and classification) the codebook is divided in two tables. Moreover, the data set contains 6 Worksheets, ordered taking the workflow as reference: Codebook, Dataset_Extraction, Analysis_Workflow, Selected_Analysis. This dataset has been produced and curated by J.E.Raffaghelli
2. The analysis of correspondance for the 23 datasets in ResearchGate. The data set presents a Codebook, and is divided into two worksheets: Codebook, ODT&RG. The last worksheet introduces the comparison between the social mètrics within RG of the found datasets and the relating papers. This dataset has been produced and curated by S. Manca and J.E. Raffaghelli.

The California Health and Human Services Agency (CalHHS) has launched its Open Data Portal initiative in order to increase public access to one of the State’s most valuable assets – non-confidential health and human services data. Its goals are to spark innovation, promote research and economic opportunities, engage public participation in government, increase transparency, and inform decision-making. "Open Data" describes data that are freely available, machine-readable, and formatted according to national technical standards to facilitate visibility and reuse of published data. The portal offers access to standardized data that can be easily retrieved, combined, downloaded, sorted, searched, analyzed, redistributed and re-used by individuals, business, researchers, journalists, developers, and government to process, trend, and innovate. The CalHHS Open Data Handbook provides guidelines to identify, review, prioritize and prepare publishable CalHHS data for access by the public via the CalHHS Open Data Portal – with a foundational emphasis on value, quality, data and metadata standards, and governance. This handbook is meant to serve as an internal resource and is also freely offered to any party that may be interested in improving the general public’s online access to data and to provide an understanding of the processes by which CalHHS makes its publishable data tables available. The handbook focuses on general guidelines and thoughtful processes but also provides linked tools/resources that operationalize those processes. The CalHHS Open Data Handbook is based on and builds upon the New York State Open Data Handbook, and we would like to acknowledge and thank the New York staff who created that document and made it available for public use. The role of the California Health and Human Services Agency is to provide policy leadership and direction to the departments and programs it oversees, to reduce duplication and fragmentation and improve coordination among the departments, to ensure programmatic integrity, and to advance the Governor's priorities on health and human services issues. The Agency coordinates the administration of state and federal programs for public health, health care services, social services, public assistance, health planning and licensing, and rehabilitation. These programs touch the lives of millions of California's most needy and vulnerable residents. The Agency is responsible for balancing the twin imperatives of providing access to essential health and human services for California's most disadvantaged and at-risk residents and managing and controlling costs. The following Departments and Offices are under the direct supervision of the California Health and Human Services Agency: The Agency Secretary also serves as Chair of Covered California, the health benefit exchange established pursuant to the Affordable Care Act. The CalHHS Open Data initiative encourages entrepreneurs, and civic coders and developers to use CalHHS data to create applications, products and services to better the health and lives of Californians. We are eager to hear from you how we can improve the portal and answer your questions, please send us an email at [email protected].

ArcGIS Hub allows governments to compile data, maps, apps, and dashboards into one-stop destination websites to communicate local details about the global crisis.Key takeaways:Open data sites communicate key details about the COVID-19 crisis to the public.State and local governments and agencies have quickly stood up data sharing sites to ease collaboration and improve transparency.Open data helps governments improve public trust, illustrating how we’re all in this together._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

This workbook contains the survey data reported in: "Sanderson, Todd; Reeson, Andrew; Box, Paul. Understanding and unlocking the value of public research data: OzNome social architecture report. Canberra: CSIRO; 2017. csiro:EP168075. https://doi.org/10.4225/08/58a5e8d940904"

There are two CSIRO Data Access Portal (DAP) surveys reported in the workbook, (1) a survey of depositors to the DAP, and (2) a survey of DAP withdrawers (users). Each of these were conducted under CSIRO Social Science Human Research Ethics Committee Approval: project 055/16 “Data Access Portal – costs and benefits for depositors and users”.

(1) The survey of depositors involved semi-structured interviews with depositors of research data collections on the DAP. This group were entirely composed of researchers within CSIRO. Depositors were interviewed using guiding questions which are presented here and in Appendix A of the report. A total of 15 data depositors from a wide variety of research disciplines accepted invitations and were interviewed. Because the interviews were semi-structured, not all questions were answered by respondents; the corresponding cells have been left blank. The interviews were conducted exclusively over the phone for a period of 30 minutes, during April 2016. In order to maintain their anonymity, some responses and some sections of responses have been removed. In these instances, a "YYYYY" will appear in the cell or text to indicate redaction.

(2) The survey of withdrawers (users) of the DAP involved a structured online survey with a focus on eliciting their assessment of the value of the data collections they were using. Withdrawers were presented with questions reported here and in Appendix B of the report. The survey was administered using a Survey Monkey application, to which a link was presented in a banner on the DAP webpage inviting users to participate. Banner advertising text: “Please help us understand the value of data in the Data Access Portal - to take part in our survey please visit https://www.surveymonkey.com/r/529MT2P”. The survey captured responses from 23 users over the period October 2016 - February 2017.

HHS responsibly shares “open by default” data with the public to democratize access to information, demystify the Department, and increase transparency through data sharing. HHS Open Data is non-sensitive data, meaning thousands of health and human services datasets are publicly available to fuel new business models, enable emerging technologies like AI, accelerate scientific discoveries, and inspire American innovation. This top-1000 HHS Open Data websites and resources page, dynamically generated from the Digital Analytics Program (DAP) provided by the U.S. General Services Administration (GSA), is driven by near-real-time user demand. GSA’s DAP helps federal agencies and the public see how visitors find, access, and use government websites, data, and services online. The below list filters DAP for only resources from HHS and includes all HHS Divisions. You may filter by individual HHS Divisions and columns.

20 minute lightning talk presentation given by Aliaksandr Yakutovich, from École Polyechnique Fédérale de Lausanne, at the Better Science through Better Data 2018 event. The video recording and scribe are included.

Gun Violence Data Portals Market Outlook

According to our latest research, the Global Gun Violence Data Portals market size was valued at $420 million in 2024 and is projected to reach $1.2 billion by 2033, expanding at a robust CAGR of 12.5% during the forecast period of 2025–2033. The primary driver for this impressive growth trajectory is the increasing demand for real-time, transparent, and actionable data to inform policy decisions, law enforcement strategies, and public health interventions in response to escalating gun violence incidents worldwide. As governments, non-profit organizations, and academic institutions intensify their focus on data-driven solutions to address the complex challenge of gun violence, investments in advanced data portals have surged, underpinning the expansion of this market on a global scale.

Regional Outlook

North America currently dominates the Gun Violence Data Portals market, accounting for the largest share of global revenue, estimated at over 45% in 2024. This leadership is attributed to the region's mature technology infrastructure, high-profile gun violence incidents, and the presence of established data analytics and software providers. The United States, in particular, has witnessed significant policy-driven investments and public-private partnerships aimed at enhancing data transparency and accessibility for law enforcement, academic researchers, and advocacy groups. The region’s proactive stance on leveraging digital solutions for crime prevention and public health, coupled with strong regulatory mandates around data reporting and sharing, has cemented its position as the epicenter of innovation and adoption in this space.

In contrast, the Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR exceeding 15% during the forecast period. This accelerated growth is fueled by rising urbanization, increasing concerns over public safety, and the rapid digitization of government and law enforcement operations. Countries such as India, Japan, and Australia are investing heavily in cloud-based analytics platforms and collaborative data-sharing frameworks to address localized gun-related challenges and support evidence-based policymaking. The influx of foreign direct investment, coupled with government initiatives to modernize surveillance and crime reporting systems, is expected to further propel the adoption of gun violence data portals across Asia Pacific.

Meanwhile, emerging economies in Latin America and the Middle East & Africa present unique opportunities and challenges for the Gun Violence Data Portals market. While these regions are grappling with high rates of gun-related violence, the adoption of advanced data portals is often hindered by infrastructural limitations, fragmented data sources, and varying levels of digital literacy among end-users. However, targeted international funding, capacity-building programs, and regional collaborations are gradually overcoming these barriers, paving the way for localized solutions tailored to specific policy and enforcement needs. As these markets mature, the potential for scalable, cloud-based data portal solutions is expected to rise significantly, contributing to the overall global market growth.

Report Scope

This technical assistance document provides guidance to Medicaid and child welfare agencies to assist and support the creation of automated, bi-directional (two-way) data exchanges between their respective information systems.

Metadata-only record linking to the original dataset. Open original dataset below.