Data Access Policy Management Market Outlook

According to our latest research, the global Data Access Policy Management market size in 2024 stands at USD 2.3 billion, reflecting the growing prioritization of data security and compliance across industries. The market is experiencing robust expansion, with a projected CAGR of 13.2% from 2025 to 2033. By 2033, the market is forecasted to reach an impressive USD 6.7 billion. This growth is primarily driven by increasing regulatory requirements, the rapid adoption of cloud technologies, and the ever-expanding digital footprint of organizations worldwide. As per our latest research, organizations are investing heavily in advanced data access policy management solutions to ensure secure, compliant, and efficient access to critical data assets.

A key growth factor for the Data Access Policy Management market is the intensifying regulatory landscape. With the introduction and enforcement of data protection regulations such as the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and Health Insurance Portability and Accountability Act (HIPAA), organizations are under immense pressure to manage and monitor data access efficiently. These regulations mandate strict controls over who can access sensitive data, how access is granted, and how access activities are audited. Non-compliance can result in severe financial penalties and reputational damage, prompting organizations across sectors to invest in comprehensive data access policy management solutions. The demand for automated policy enforcement, real-time monitoring, and detailed audit trails is higher than ever, spurring innovation and adoption in this market.

Another significant driver is the accelerated adoption of cloud computing and hybrid IT environments. As organizations migrate their workloads to public and private clouds, the complexity of managing data access policies across diverse platforms increases exponentially. Traditional access management approaches often fall short in these dynamic environments, necessitating more sophisticated, centralized solutions that can enforce consistent policies regardless of where data resides. The need to support remote workforces and facilitate secure collaboration further amplifies the demand for robust data access policy management tools. These solutions not only help organizations maintain control over their data but also enhance operational agility by enabling secure, role-based access to information assets.

Furthermore, the proliferation of digital transformation initiatives is fueling market growth. Enterprises are leveraging big data, artificial intelligence, and Internet of Things (IoT) technologies to gain competitive advantage, resulting in a dramatic increase in data volume and diversity. Managing access to this expanding data landscape requires scalable and flexible policy management frameworks. Organizations are seeking solutions that can integrate seamlessly with existing identity and access management (IAM) systems, support granular policy definition, and provide real-time insights into access activities. The integration of advanced analytics and machine learning capabilities into data access policy management solutions is enabling proactive risk identification and policy optimization, further driving market expansion.

From a regional perspective, North America continues to dominate the Data Access Policy Management market, owing to the presence of leading technology providers, stringent regulatory requirements, and high awareness of data security best practices. Europe follows closely, driven by strong regulatory enforcement and increasing digitalization across industries. The Asia Pacific region is witnessing the fastest growth, propelled by rapid economic development, increasing digital adoption, and evolving regulatory frameworks. Latin America and the Middle East & Africa are also emerging as promising markets, as organizations in these regions ramp up their investments in data security and compliance infrastructure. The global nature of data flows and the interconnectedness of business ecosystems underscore the importance of robust data access policy management across all regions.

Component Analysis

The Data Access Policy Management market is segmented by component into software and services, each playing a pivotal role in the overall value proposition. The software segment encompasses standalone policy management platforms as well

Data Access Control for Analytics Market Outlook

According to our latest research, the global Data Access Control for Analytics market size reached USD 4.7 billion in 2024, with a robust year-on-year expansion fueled by rapid digital transformation across industries. The market is projected to grow at a CAGR of 15.2% from 2025 to 2033, culminating in a forecasted value of USD 16.4 billion by 2033. The primary growth driver is the increasing need for robust data security and compliance frameworks as organizations harness analytics for strategic decision-making.

The surge in digital data generation, coupled with the proliferation of advanced analytics platforms, is significantly driving the growth of the Data Access Control for Analytics market. As enterprises collect and process vast volumes of sensitive information, the risk of data breaches and unauthorized access has escalated. This heightened risk landscape has compelled organizations to invest in sophisticated data access control solutions that ensure only authorized personnel can access critical analytics resources. Moreover, the adoption of cloud-based analytics platforms has introduced new complexities to data governance, further amplifying the demand for granular access control mechanisms. The convergence of these factors is expected to sustain the market’s upward trajectory over the forecast period.

Another key growth factor is the tightening regulatory environment across major economies. Governments and industry regulators are imposing stringent data privacy and security mandates, such as the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) in the United States, and similar frameworks in Asia Pacific. These regulations require organizations to implement comprehensive data access control policies to ensure compliance and avoid hefty penalties. Consequently, enterprises are increasingly prioritizing investments in access control technologies that offer audit trails, policy management, and real-time monitoring of data access activities. This regulatory push is not only driving market growth but also fostering innovation among solution providers.

The growing integration of artificial intelligence (AI) and machine learning (ML) into analytics workflows is also shaping the Data Access Control for Analytics market. As organizations leverage AI-driven analytics to extract actionable insights from complex datasets, the need to secure sensitive models and data pipelines becomes paramount. AI-powered access control solutions are emerging, capable of dynamically adjusting permissions based on user behavior, risk profiles, and contextual factors. This evolution is particularly relevant for sectors like BFSI, healthcare, and government, where data sensitivity is exceptionally high. The convergence of AI, analytics, and access control is expected to unlock new market opportunities and accelerate adoption across verticals.

From a regional perspective, North America currently dominates the Data Access Control for Analytics market, accounting for the largest share in 2024. This leadership is attributed to the region’s advanced digital infrastructure, high adoption of analytics solutions, and a mature regulatory landscape. However, Asia Pacific is emerging as the fastest-growing market, driven by rapid digitization, expanding cloud adoption, and increasing awareness of data privacy. Europe continues to show steady growth, underpinned by strict compliance requirements and a strong focus on data governance. Other regions, including Latin America and the Middle East & Africa, are gradually catching up as enterprises in these markets recognize the strategic value of secure analytics.

Component Analysis

The Data Access Control for Analytics market is segmented by component into Software, Hardware, and Services. The Software segment currently holds the largest market share, benefiting from the widespread adoption of analytics platforms and the growing complexity of data environments. Modern

Self-Serve Data Access Portals Market Outlook

According to our latest research, the global Self-Serve Data Access Portals market size reached USD 4.1 billion in 2024. The market is experiencing robust momentum, with a CAGR of 18.2% projected from 2025 to 2033. By the end of 2033, the market is forecasted to attain a valuation of USD 19.7 billion. This significant growth is being propelled by the increasing demand for democratized data access, the proliferation of big data analytics, and the widespread adoption of self-service business intelligence tools across diverse industry verticals. The market is also being shaped by the accelerating pace of digital transformation and the need for agile, data-driven decision-making processes within organizations.

A primary growth factor for the Self-Serve Data Access Portals market is the escalating need for organizations to empower non-technical users with seamless access to data. As enterprises strive to become more data-driven, there is a pronounced shift towards enabling business users to independently extract, analyze, and visualize data without relying on IT teams. This trend is particularly pronounced in sectors such as BFSI, healthcare, and retail, where timely insights are critical for operational efficiency and competitive advantage. The democratization of data is fostering a culture of self-service analytics, reducing bottlenecks, and accelerating the decision-making process. Furthermore, the integration of advanced analytics and AI-driven features within self-serve portals is enhancing user experience and broadening the scope of actionable insights, thereby fueling market expansion.

Another significant driver is the rapid adoption of cloud-based solutions, which has transformed the deployment landscape for self-serve data access portals. Cloud deployment offers scalability, flexibility, and cost-effectiveness, making it an attractive option for organizations of all sizes, especially small and medium enterprises (SMEs). The cloud enables seamless integration with various data sources, supports remote access, and ensures high availability and disaster recovery. As a result, cloud-based self-serve data access portals are gaining traction among enterprises seeking to modernize their data infrastructure and streamline operations. Additionally, the rise of hybrid and multi-cloud environments is further facilitating the adoption of self-serve portals, as organizations look to leverage the best features of different cloud platforms while maintaining data security and compliance.

The growing emphasis on regulatory compliance and data governance is also contributing to the expansion of the Self-Serve Data Access Portals market. Organizations are increasingly required to adhere to stringent data protection regulations such as GDPR, HIPAA, and CCPA, necessitating robust data access controls and audit trails. Modern self-serve portals are equipped with advanced security features, role-based access controls, and comprehensive logging capabilities, enabling organizations to maintain compliance while providing users with the freedom to explore and utilize data. This balance between accessibility and governance is driving adoption across highly regulated industries, further strengthening the market's growth trajectory.

From a regional perspective, North America continues to dominate the market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The mature IT infrastructure, high digital literacy, and early adoption of advanced analytics solutions in North America have positioned the region as a frontrunner. Meanwhile, Asia Pacific is emerging as a high-growth market, driven by rapid digitalization, expanding enterprise IT budgets, and increasing awareness of data-driven business strategies. The presence of a large SME sector and government initiatives promoting digital transformation are further accelerating market growth in the region. Europe, with its strong focus on data privacy and compliance, is also witnessing steady adoption of self-serve data access portals, particularly in the BFSI and healthcare sectors.

Component Analysis

The Self-Serve Data Access Portals market by component is segmented into software and services. The software segment comprises the core platforms and applications that facilitate self-service data access, analytics, and visualization. These solutions are designed to offer intuitive interfaces, robust data i

Sources of data for Figure 3 (in the online article; Figure 2 in print) and Tables 1, 2a, 2b, 3a and 3b of the Geoscientist article Digging into data access: The need for reform. Files:

digging_into_data_access_sources.xlsx - spreadsheet listing all references for Figure 3 (in the online article; Figure 2 in print) and Tables 1, 2a, 2b, 3a and 3b. The spreadsheet includes references to page numbers on which quoted figures are given

Source files for Figure 3 (in the online article; Figure 2 in print):

digging_into_data_access_figure3online_figure2print_source_documentA.pdf - British Geological Survey Annual Report 2019–2020. Source of data for the column BGS in Figure 3 digging_into_data_access_figure3online_figure2print_source_documentB.pdf - OGA Annual Report and Accounts 2020–21. Source of data for the column OGA in Figure 3 digging_into_data_access_figure3online_figure2print_source_documentC.pdf - UK Onshore Geophysical Library Trustees' Report and Financial Statements 2020 for the Year Ended 31 December 2020. Source of data for the column UKOGL in Figure 3 digging_into_data_access_figure3online_figure2print_source_documentD.pdf - Environment Agency Annual Report and Accounts for the Financial Year 2020 to 2021. Source of data for the column EA in Figure 3

Source files for Tables 1, 2a, 2b, 3a and 3b:

digging_into_data_access_tables_source_documentX.pdf - X corresponds to the number in the column Source in Tables 1, 2a, 2b, 3a and 3b. See also the tab 'tables_sources' in the spreadsheet digging_into_data_access_sources.xlsx

MY NASA DATA (MND) is a tool that allows anyone to make use of satellite data that was previously unavailable.Through the use of MND’s Live Access Server (LAS) a multitude of charts, plots and graphs can be generated using a wide variety of constraints. This site provides a large number of lesson plans with a wide variety of topics, all with the students in mind. Not only can you use our lesson plans, you can use the LAS to improve the ones that you are currently implementing in your classroom.

Data Access Policy Orchestration Market Outlook

According to our latest research, the Global Data Access Policy Orchestration market size was valued at $1.52 billion in 2024 and is projected to reach $6.47 billion by 2033, expanding at a robust CAGR of 17.5% during the forecast period of 2025–2033. This remarkable growth is primarily driven by the escalating need for streamlined data governance and compliance management across industries, as organizations grapple with an ever-increasing volume of sensitive data and stringent regulatory requirements. The integration of advanced automation and artificial intelligence into data access policy orchestration platforms is enabling enterprises to enforce granular, dynamic access controls while reducing manual intervention and operational risk, further fueling market expansion.

Regional Outlook

North America currently dominates the Data Access Policy Orchestration market, accounting for the largest market share of approximately 38% in 2024. This region's leadership is attributed to its mature technology infrastructure, early adoption of advanced cybersecurity solutions, and the presence of leading industry players. Regulatory frameworks such as HIPAA, CCPA, and SOX have compelled organizations in the United States and Canada to invest heavily in robust data governance and access management solutions, fostering sustained demand. Furthermore, the proliferation of cloud computing and digital transformation initiatives among enterprises in this region has led to a surge in the deployment of sophisticated data access policy orchestration platforms, ensuring secure, compliant, and efficient data utilization.

The Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR of 20.2% from 2025 to 2033. Rapid digitalization, expanding IT infrastructure, and increasing awareness of data privacy regulations such as China’s Cybersecurity Law and India’s Personal Data Protection Bill are major growth drivers. Investments from both local governments and international technology giants are accelerating the adoption of advanced data management and orchestration solutions across industries such as BFSI, healthcare, and telecommunications. Additionally, the region's thriving SME sector is increasingly recognizing the importance of automated, scalable data access policy tools to support business agility and compliance, further propelling market growth.

Emerging economies in Latin America, the Middle East, and Africa are also witnessing gradual adoption of Data Access Policy Orchestration solutions, albeit at a slower pace due to infrastructural challenges, limited digital literacy, and budget constraints. Nevertheless, the growing demand for secure digital services, coupled with evolving regulatory landscapes and increased foreign investment, is encouraging organizations in these regions to modernize their data governance practices. Localized solutions that address language, compliance, and integration requirements are gaining traction, although market penetration remains hindered by fragmented IT ecosystems and inconsistent policy enforcement.

Report Scope

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Update on StatsCan/Data Access Division (DAD), EAC/DLI, PDC

Information for how to cite the MTE bundle.

Historical dataset showing Haiti clean water access by year from N/A to N/A.

This database refers to the data collected by the European University Association (EUA) for its Open Access Survey 2017-2018, which gathered responses from universities and higher education institutions across Europe. The full report published by the association is available at https://eua.eu/resources/publications/826:2017-2018-eua-open-access-survey-results.html.

The data included in this database refers only to those universities and higher education institutions that accepted their data to be available in open access (n=266). All information that could lead to the identification of individual universities and higher education institutions was removed from the database. The following files are available:

Questionnaire

Database in the following formats: .sav (IBM SPSS Statistics), .xlsx (Microsoft Excel) and .csv

Codebook: includes information on all the variables and their coding.

This dataset contains the predicted prices of the asset Access over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

What this collection is: A curated, binary-classified image dataset of grayscale (1 band) 400 x 400-pixel size, or image chips, in a JPEG format extracted from processed Sentinel-1 Synthetic Aperture Radar (SAR) satellite scenes acquired over various regions of the world, and featuring clear open ocean chips, look-alikes (wind or biogenic features) and oil slick chips.

This binary dataset contains chips labelled as: - "0" for chips not containing any oil features (look-alikes or clean seas)
- "1" for those containing oil features.

This binary dataset is imbalanced, and biased towards "0" labelled chips (i.e., no oil features), which correspond to 66% of the dataset. Chips containing oil features, labelled "1", correspond to 34% of the dataset.

Why: This dataset can be used for training, validation and/or testing of machine learning, including deep learning, algorithms for the detection of oil features in SAR imagery. Directly applicable for algorithm development for the European Space Agency Sentinel-1 SAR mission (https://sentinel.esa.int/web/sentinel/missions/sentinel-1 ), it may be suitable for the development of detection algorithms for other SAR satellite sensors.

Overview of this dataset: Total number of chips (both classes) is N=5,630 Class 0 1 Total 3,725 1,905

Further information and description is found in the ReadMe file provided (ReadMe_Sentinel1_SAR_OilNoOil_20221215.txt)

US B2B Contact Database | 200M+ Verified Records | 95% Accuracy | API/CSV/JSON Elevate your sales and marketing efforts with America's most comprehensive B2B contact data, featuring over 200M+ verified records of decision-makers, from CEOs to managers, across all industries. Powered by AI and refreshed bi-weekly, this dataset ensures you have access to the freshest, most accurate contact details available for effective outreach and engagement.

Key Features & Stats:

200M+ Decision-Makers: Includes C-level executives, VPs, Directors, and Managers.

95% Accuracy: Email & Phone numbers verified for maximum deliverability.

Bi-Weekly Updates: Never waste time on outdated leads with our frequent data refreshes.

50+ Data Points: Comprehensive firmographic, technographic, and contact details.

Core Fields:

Direct Work Emails & Personal Emails for effective outreach.

Mobile Phone Numbers for cold calls and SMS campaigns.

Full Name, Job Title, Seniority for better personalization.

Company Insights: Size, Revenue, Funding data, Industry, and Tech Stack for a complete profile.

Location: HQ and regional offices to target local, national, or international markets.

Top Use Cases:

Cold Email & Calling Campaigns: Target the right people with accurate contact data.

CRM & Marketing Automation Enrichment: Enhance your CRM with enriched data for better lead management.

ABM & Sales Intelligence: Target the right decision-makers and personalize your approach.

Recruiting & Talent Mapping: Access CEO and senior leadership data for executive search.

Instant Delivery Options:

JSON – Bulk downloads via S3 for easy integration.

REST API – Real-time integration for seamless workflow automation.

CRM Sync – Direct integration with your CRM for streamlined lead management.

Enterprise-Grade Quality:

SOC 2 Compliant: Ensuring the highest standards of security and data privacy.

GDPR/CCPA Ready: Fully compliant with global data protection regulations.

Triple-Verification Process: Ensuring the accuracy and deliverability of every record.

Suppression List Management: Eliminate irrelevant or non-opt-in contacts from your outreach.

US Business Contacts | B2B Email Database | Sales Leads | CRM Enrichment | Verified Phone Numbers | ABM Data | CEO Contact Data | US B2B Leads | US prospects data

The Swedish Contextual Database provides a large number of longitudinal and regional macro-level indicators primarily assembled to facilitate research on the effects of contextual factors on family and fertility behavior. It can be linked to the individual-level data of the Swedish GGS as well as to data of other surveys. It can also be used for other types of research and for teaching. The comparative data will also be integrated into the international Contextual Database of the GGP. The contextual data are available open-access through the GGP webpage: www.ggp-i.org and through the webpage of Stockholm University Demography Unit www.suda.su.se

Purpose:

The Swedish contextual database (CDB) was established to accompany the Swedish Generations and Gender Survey (GGS) and to complement the contextual database of the international Generations and Gender Programme (GGP).

The Swedish Contextual Data Collection is available in xls format. In addition to that, the internationally comparative data will be integrated into the Contextual Database (CDB) of the GGP in 2018. These data can be exported in other formats, as well (e.g. CSV, XML). The indicators can also be accessed in a single file in STATA or SPSS format. The data can be matched with the Swedish GGS. International regional coding schemes are also supported, such as NUTS, OECD.

Data set consists of daily logs by menhaden purse-seine vessels w/ data on individual purse-seine set size, location, and date

This collection comprises datasets collected from an array of 12 coastal Integrated Marine Observing System (IMOS) moorings off the southwest coast of Western Australia (WA) during 2009-2023, at depths ranging from 47 m to 500 m. The dataset includes temperatures and salinities collected with Seabird SBE37 and SBE39 sensors and Water Quality Monitor (WQM). Velocities were collected by Teledyne RDI Workhorse, RDI Long Ranger, Nortek Aquadopp, Nortek Continental, and Nortek Signature 250 and 500 ADCPs. In the collection, daily gridded in-situ subsurface temperature, salinity, and ocean currents, and their average annual cycles are presented. Monthly average data are also included. This integrated dataset provides an overview of data availability and allows users to have quick access to the mooring data, without the need of manipulating over one thousand files individually. This unique dataset offers an invaluable baseline perspective on water column properties and temporal variability in WA coastal waters. The data can be used to characterise subsurface features of extreme events such as marine heatwaves, marine cold-spells, and to detect long-term change signals along the WA coast, influenced by the Leeuwin Current and the wind-driven Capes Current.

Lineage: Firstly, raw data (FV00) were processed using IMOS Matlab Toolbox. Quality Assurance (QA) and Quality Control (QC) of the data were performed using the Toolbox and assessed by oceanographers. Secondly, quality-controlled data (FV01) were concatenated, and then (linearly) interpolated to a grid of 1m vertical resolution and averaged daily. Monthly data were then derived from daily data if there were more than 10 days of data during that month.

The asteroid lightcurve database (LCDB) is one of the more widely-used research tools for those doing research that compares and contrasts physical characteristics of asteroid spin axis rates, sizes, pole orientations, and/or taxonomic class - among others. The v3.0 release includes lightcurve photometry results for more than 24500 targets. Each object has one to several dozen detail records that contain results obtained by scanning the literature.

The Urban Big Data Centre (UBDC) is an ESRC research centre based at the University of Glasgow that promotes the use of smart data and innovative methods to improve social, economic & environmental well-being in cities.

From 2014-26, it was also funded by ESRC to provide a national data service to enhance access to 'smart data'. UBDC focuses on six main research themes (labour market, housing and neighbourhoods, transport and mobility, urban governance, urban sustainability, and education) as well as two research methods (urban sensing and participatory analytics).

You can find more information about UBDC by visiting https://www.ubdc.ac.uk. To explore UBDC’s data offerings, please visit https://data.ubdc.ac.uk/.

Some of UBDC’s data collections are only available with permission from UBDC. These collections have been archived with the University of Glasgow repository. Details on the hosting and availability of safeguarded datasets can be found in the attached metadata sheet (snapshot as of 07/05/2025).

The proposed UBDRC will bring together an internationally outstanding combination of researchers, data resources and engaged local and national stakeholders to establish a unique linked data resource based in the University of Glasgow (UoG). Through extensive partnerships with other key academic institutions, data-owning organizations, and other scientific, governmental, third sector and business organizations, the UBDRC will: (i) establish a world leading facility to create an multi-sectoral urban linked data resource from local government authorities and business owners in Glasgow; (ii) provide outstanding training and research support services to ensure wide exploitation of the data; and (iii) deliver a strategic approach to knowledge transfer and training to build capacity and engage with policy, business, and the wider public. The UBDRC will provide a unique facility for researching cross-cutting urban issues and complex urban challenges by enabling access to multi-sectoral linked data from local government, business and other sources. This vision will be achieved by: (1) Data Services: UBDRC will focus on bringing together myriad of datasets many of which are unique and hard to obtain, from multiple urban sectors to create a linked urban data resource that allows comprehensive and cross-sectoral research. The centre will provide data curation services and the necessary metadata and provide a range of data access services to users, including, where necessary, secure access to confidential data. (2) Methods and social science research: UBDRC will develop, test and evaluate a wide range of methodological approaches including urban and regional modeling, agent-based models, machine learning and other methods and will support research leading to new cross-cutting theoretical insights, hypotheses and understanding of urban systems, thereby stimulating foundational research on new models of urban behaviour, processes and service provision. The data resource will be used to develop spatially-indexed (and perhaps temporally-indexed) urban indicators on myriad aspects describing the quality and character of urban spaces, and the spatial distribution of the urban processes, eg, on environmental risks, mobility and accessibility patterns, housing and educational aspects, and other aspects that desribe the socio-demographic, economic, environmental, built environment, physical and other aspects of urban areas.. The data would further allow policy research on a wide range of urban sectors and the derivation of a multitude of approaches for urban governance and business development. Additionally, new insights may be derived for capacity-building, innovations and learning strategies to better equip citizens to meet a diversity of challenges in cities of the future. (3) Knowledge Exchange, Outreach and Public Engagement: The UBDRC will be an important node in a growing network of UK-wide and international initiatives on cities. The networks include: international centres on urban research and cities, international research Networks, and networks of governmental, private, non-profit and other organizations. The UBDRC will undertake a research programme to advance the state-of-the-art of methods related to the use of the data resource, as well as an applied urban research stream to demonstrate the use of the linked urban Big Data resource and to derive understanding towards theory, planning and policy. Research Group 1: Methods Research: A series of computational, data management, statistical, and urban analytics projects will be undertaken to make the data more easily accessible and usable. Group 2: Urban Research Projects (URPs): Research projects on substantive urban issues such as transport, housing, migration and education will demonstrate to data owners and policy makers the value of large-scale, cross-sectoral data linkage and lead to policy insights for public, private and non-profit decision-makers.

This study uses historical records from 36 archives in the United States to analyze 8,437 enslaved people's sale and/or appraisal prices from 1797 to 1865.