The District of Columbia offers several interactive online visualizations highlighting data and information from various fields of interest such as crime statistics, public school profiles, detailed property information and more. The web visualizations in this group present data coming from agencies across the Government of the District of Columbia. Click each to read a brief introduction and to access the site. This app is embedded in https://opendata.dc.gov/pages/dashboards.

This is a link to the United States Federal Government's Open Data Portal. Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations.

Check out the attachment in the metadata detailing all the Opioid Related datasets contained in this portal.

Data.gov is the federal government’s open data site, and aims to make government more open and accountable. Opening government data increases citizen participation in government, creates opportunities for economic development, and informs decision making in both the private and public sectors.

Links included for Center for Disease Control and Prevention both the business website and their Data and Statistics website.

Disclosed capital expenditure, business expenses and revenue in relation to a range of agencies in the Finance, Services and Innovation cluster. Budget data is available for download in a variety of formats. Also includes a link to the DFSI Budget Data Visualisation tool. The tool is an interactive visualisation, enabling users to drill-down into DFSI capital expenditure, business expenses and revenue. This makes it easy to see where DFSI funds are distributed and are being spent.

The city of Austin has administered a community survey for the 2015, 2016, 2017, 2018 and 2019 years (https://data.austintexas.gov/City-Government/Community-Survey/s2py-ceb7), to “assess satisfaction with the delivery of the major City Services and to help determine priorities for the community as part of the City’s ongoing planning process.” To directly access this dataset from the city of Austin’s website, you can follow this link https://cutt.ly/VNqq5Kd. Although we downloaded the dataset analyzed in this study from the former link, given that the city of Austin is interested in continuing administering this survey, there is a chance that the data we used for this analysis and the data hosted in the city of Austin’s website may differ in the following years. Accordingly, to ensure the replication of our findings, we recommend researchers to download and analyze the dataset we employed in our analyses, which can be accessed at the following link https://github.com/democratizing-data-science/MDCOR/blob/main/Community_Survey.csv. Replication Features or Variables The community survey data has 10,684 rows and 251 columns. Of these columns, our analyses will rely on the following three indicators that are taken verbatim from the survey: “ID”, “Q25 - If there was one thing you could share with the Mayor regarding the City of Austin (any comment, suggestion, etc.), what would it be?", and “Do you own or rent your home?”

Interactive data map of COVID-19 cases around the world. Shows number of total cases and deaths by country over time, starting from December 31, 2019 to present time.

The Public Assistance (PA) Funded Projects Details dataset contains a list of funded (obligated) PA projects, called project worksheets. Unobligated projects (still in formulation) are not represented. The Applicant ID is provided for this dataset to be used with the OpenFEMA “Public Assistance Applicants - v1” dataset.rnFEMA provides supplemental Federal disaster grant assistance for debris removal, emergency protective measures, and the repair, replacement, or restoration of disaster-damaged, publicly owned facilities and the facilities of certain Private Non-Profit (PNP) organizations through the PA Program (CDFA Number 97.036). The PA Program also encourages protection of these damaged facilities from future events by providing assistance for 406 hazard mitigation measures during the recovery process.rnThis is raw, unedited data from FEMA's Emergency Management Mission Integrated Environment (EMMIE) and as such is subject to a small percentage of human error. The financial information is derived from EMMIE and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations, and application of business rules, this financial information may differ slightly from official publication on public websites such as www.usaspending.gov . This dataset is not intended to be used for any official federal reporting.rnThe data has been incorporated into a graphic visualization at Public Assistance Program Summary of Obligations: https://www.fema.gov/data-visualization/public-assistance-program-summary-obligations. Questions pertaining to the data visualizations should be addressed to EnterpriseAnalytics@fema.dhs.gov.rnIf you have media inquiries about this dataset, please email the FEMA News Desk at FEMA-News-Desk@fema.dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open Government program, please email the OpenFEMA team at OpenFEMA@fema.dhs.gov.

[213+ Pages Report] The global Data Visualization market size is expected to grow from USD 9 billion to USD 19.25 billion by 2028, at a CAGR of 10.15% from 2022-2028

Global Data Visualization Tools Market size worth at USD 8.75 Billion in 2023 and projected to USD 22.11 Billion by 2032, with a CAGR of around 9.7% between 2024-2032.

Data Visualization Market is Segmented by Organization Department (Executive Management, Marketing, Operations, Finance, Sales), Deployment Mode (On-premise, Cloud/On-demand), End User (BFSI, IT and Telecommunication, Education, Manufacturing, Government, Retail/E-commerce) and Geography (North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa). The market sizes and forecasts are provided in terms of value (USD) for all the above segments.

The Power Africa Enabling Environment Tracker 2020 data in the DDL are used in Power Africa's Enabling Environment Tracker dashboard. The Enabling Environment Tracker is an interactive data aggregation and visualization tool that pulls together publicly available data on policy and regulatory trends across Africa’s energy sector into one, easily accessible location. The dataset includes publicly available, third-party data points, which were selected based off Power Africa's Enabling Environment Principles. The principles lay out key elements for increasing private sector investment and doubling electricity access in Sub-Saharan Africa. The hope is that Power Africa's African government partners, private sector partners, development partners, and other stakeholders use the tool to assess enabling environment progress, inform technical assistance interventions, and guide advocacy for needed reforms.

According to Cognitive Market Research, the global Government Open Data Management Platform Market size will be USD XX million in 2024. It will expand at a compound annual growth rate (CAGR) of 9.90% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.1% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD XX million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.9% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.3% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.6% from 2024 to 2031.
The large enterprises held the highest Government Open Data Management Platform Market revenue share in 2024.

Market Dynamics of Government Open Data Management Platform Market

Key Drivers for Government Open Data Management Platform Market

Streamlining Procedures and Increasing Productivity to Increase the Demand Globally

Operational effectiveness and process optimization are propelling market expansion. Organizations can increase operational efficiency and streamline procedures by implementing open data management solutions. Organizational data is gathered, managed, organized, and stored with the use of open data management platforms to increase accessibility and usability. These kinds of solutions are commonly applied to business process automation as well as operational optimization and streamlining. For instance, by significantly reducing human engagement and contact during the data extraction procedures, open data management platforms are often used to automate corporate processes. In response to advancements in technology and the creation of increasingly complicated data sets, open data management platforms have developed.

Advancements in Technology to Propel Market Growth

The Government Open Data Management Platform Market has witnessed steady growth, driven by advancements in technology, such as improving analytics, security, and data accessibility. Governments can more effectively manage and use huge volumes of public data because of advances in AI, cloud computing, and big data analytics. By enhancing the integration of data, real-time analysis, and visualization, these technologies promote availability and well-informed decision-making. Furthermore, improvements in cybersecurity guarantee data security, encouraging public confidence. The need for advanced data management platforms in the public sector is being driven by the increasing capacity to handle and exploit open data as a result of technological advancements.

Restraint Factor for the Government Open Data Management Platform Market

Lack of Skilled Workforce in Government Open Data Management Platform to Limit the Sales

The government's open data management platform needs skilled workers to oversee its operations, but a key hindrance to its expansion is the need for a skilled workforce. Understanding HTML, CSS, and JavaScript is necessary for the developer to execute data platform management. Thus, lacking in this fundamental knowledge makes it more difficult to hire the proper specialists, which lowers productivity inside the firm. These important problems make it harder for the market for government open data platform management to expand.

Impact of Covid-19 on the Government Open Data Management Platform Market

The Government Open Data Management Platform Market has witnessed growth. In order for researchers and policymakers to follow the virus's transmission, locate hotspots, and make defensible decisions, open data management technologies were essential in the collection, analysis, and visualization of COVID-19 data. Consequently, the outbreak had a favorable effect on the expansion of the local market. The need for improved data security, the growing focus on data-driven decision-making, the need for transparent and accessible government data, changing...

The global visual data analysis tool market is experiencing robust growth, driven by the increasing need for businesses to extract actionable insights from ever-expanding datasets. The market, currently valued at approximately $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. This significant expansion is fueled by several key factors. The proliferation of big data, coupled with the rising adoption of cloud-based solutions and advanced analytics techniques, empowers organizations across various sectors – including banking, manufacturing, and government – to make data-driven decisions. Furthermore, the continuous innovation in visualization technologies, offering more intuitive and user-friendly interfaces, is broadening accessibility and accelerating market penetration. The growing demand for real-time data analysis and predictive modeling further contributes to the market's upward trajectory. Despite the significant growth potential, the market faces certain challenges. High implementation costs, particularly for on-premises solutions, and the need for specialized skills to effectively utilize these tools can act as restraints for smaller businesses. However, the emergence of affordable cloud-based alternatives and increased availability of training programs are gradually mitigating these barriers. The market segmentation reveals a clear preference towards cloud-based solutions due to their scalability, flexibility, and cost-effectiveness. The banking and finance sectors, followed by manufacturing and consultancy, represent the largest market segments. Key players like Tableau, Microsoft, and Salesforce are driving innovation and shaping market competition through continuous product enhancements and strategic acquisitions. The geographical landscape displays strong growth potential across North America and Europe, while Asia-Pacific is expected to emerge as a significant market in the coming years.

This dataset was created for the Data Visualization map on FEMA.gov/data-visualization using Agency data that was released to the public by OpenFEMA. It is created by pulling, processing and combining multiple OpenFEMA datasets (listed below) together. Merging data tables depends on common fields being present throughout each source file. For this reason many columns in the original files were not included. For example, county level details were excluded because they are not available in all the source files. Additionally, we added new columns to ensure integrity existed between the source file and the merged file. For example, we added and populated when needed Grant Bucket, Program Name, Program Abbr, and Incident Type. Open FEMA data is available at: http://www.fema.gov/media-library/resources-documents/collections/339

Presentation Date: Monday, April 1, 2019 - Location: Radcliffe Institute for Advanced Study at Harvard, Cambridge, MA - Innovative data visualization reveals patterns and trends otherwise unseen. The four speakers in this program represent a range of visualization expertise, from human cognition to user interaction to tool design to the use of visualizations in journalism. As data sets in science, medicine, and business become larger and more diverse, the need for—and the impact of—good visualization is growing rapidly. The presentations will highlight a wide scope of visualization’s applicability, using examples from personalized medicine, government, education, basic science, climate change, and more.

Overview The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.4 (published 24 February 2025). The 11.4 release contains updated boundary lines and data refinements designed to extend the functionality of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control. National Geospatial Data Asset This dataset is a National Geospatial Data Asset (NGDAID 194) managed by the Department of State. It is a part of the International Boundaries Theme created by the Federal Geographic Data Committee. Dataset Source Details Sources for these data include treaties, relevant maps, and data from boundary commissions, as well as national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process includes analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground. Cartographic Visualization The LSIB is a geospatial dataset that, when used for cartographic purposes, requires additional styling. The LSIB download package contains example style files for commonly used software applications. The attribute table also contains embedded information to guide the cartographic representation. Additional discussion of these considerations can be found in the Use of Core Attributes in Cartographic Visualization section below. Additional cartographic information pertaining to the depiction and description of international boundaries or areas of special sovereignty can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues: https://hiu.state.gov/data/cartographic_guidance_bulletins/ Contact Direct inquiries to internationalboundaries@state.gov. Direct download: https://data.geodata.state.gov/LSIB.zip Attribute Structure The dataset uses the following attributes divided into two categories: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | Core CC1_GENC3 | Extension CC1_WPID | Extension COUNTRY1 | Core CC2 | Core CC2_GENC3 | Extension CC2_WPID | Extension COUNTRY2 | Core RANK | Core LABEL | Core STATUS | Core NOTES | Core LSIB_ID | Extension ANTECIDS | Extension PREVIDS | Extension PARENTID | Extension PARENTSEG | Extension These attributes have external data sources that update separately from the LSIB: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | GENC CC1_GENC3 | GENC CC1_WPID | World Polygons COUNTRY1 | DoS Lists CC2 | GENC CC2_GENC3 | GENC CC2_WPID | World Polygons COUNTRY2 | DoS Lists LSIB_ID | BASE ANTECIDS | BASE PREVIDS | BASE PARENTID | BASE PARENTSEG | BASE The core attributes listed above describe the boundary lines contained within the LSIB dataset. Removal of core attributes from the dataset will change the meaning of the lines. An attribute status of “Extension” represents a field containing data interoperability information. Other attributes not listed above include “FID”, “Shape_length” and “Shape.” These are components of the shapefile format and do not form an intrinsic part of the LSIB. Core Attributes The eight core attributes listed above contain unique information which, when combined with the line geometry, comprise the LSIB dataset. These Core Attributes are further divided into Country Code and Name Fields and Descriptive Fields. County Code and Country Name Fields “CC1” and “CC2” fields are machine readable fields that contain political entity codes. These are two-character codes derived from the Geopolitical Entities, Names, and Codes Standard (GENC), Edition 3 Update 18. “CC1_GENC3” and “CC2_GENC3” fields contain the corresponding three-character GENC codes and are extension attributes discussed below. The codes “Q2” or “QX2” denote a line in the LSIB representing a boundary associated with areas not contained within the GENC standard. The “COUNTRY1” and “COUNTRY2” fields contain the names of corresponding political entities. These fields contain names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the ‘"Independent States in the World" and "Dependencies and Areas of Special Sovereignty" lists maintained by the Department of State. To ensure maximum compatibility, names are presented without diacritics and certain names are rendered using common cartographic abbreviations. Names for lines associated with the code "Q2" are descriptive and not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS denote independent states. Names rendered in normal text represent dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user. Descriptive Fields The following text fields are a part of the core attributes of the LSIB dataset and do not update from external sources. They provide additional information about each of the lines and are as follows: ATTRIBUTE NAME | CONTAINS NULLS RANK | No STATUS | No LABEL | Yes NOTES | Yes Neither the "RANK" nor "STATUS" fields contain null values; the "LABEL" and "NOTES" fields do. The "RANK" field is a numeric expression of the "STATUS" field. Combined with the line geometry, these fields encode the views of the United States Government on the political status of the boundary line. A value of “1” in the “RANK” field corresponds to an "International Boundary" value in the “STATUS” field. Values of ”2” and “3” correspond to “Other Line of International Separation” and “Special Line,” respectively. The “LABEL” field contains required text to describe the line segment on all finished cartographic products, including but not limited to print and interactive maps. The “NOTES” field contains an explanation of special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, limitations regarding the purpose of the lines, or the original source of the line. Use of Core Attributes in Cartographic Visualization Several of the Core Attributes provide information required for the proper cartographic representation of the LSIB dataset. The cartographic usage of the LSIB requires a visual differentiation between the three categories of boundary lines. Specifically, this differentiation must be between: - International Boundaries (Rank 1); - Other Lines of International Separation (Rank 2); and - Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Please consult the style files in the download package for examples of this depiction. The requirement to incorporate the contents of the "LABEL" field on cartographic products is scale dependent. If a label is legible at the scale of a given static product, a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field contains the preferred description for the three LSIB line types when they are incorporated into a map legend but is otherwise not to be used for labeling. Use of the “CC1,” “CC1_GENC3,” “CC2,” “CC2_GENC3,” “RANK,” or “NOTES” fields for cartographic labeling purposes is prohibited. Extension Attributes Certain elements of the attributes within the LSIB dataset extend data functionality to make the data more interoperable or to provide clearer linkages to other datasets. The fields “CC1_GENC3” and “CC2_GENC” contain the corresponding three-character GENC code to the “CC1” and “CC2” attributes. The code “QX2” is the three-character counterpart of the code “Q2,” which denotes a line in the LSIB representing a boundary associated with a geographic area not contained within the GENC standard. To allow for linkage between individual lines in the LSIB and World Polygons dataset, the “CC1_WPID” and “CC2_WPID” fields contain a Universally Unique Identifier (UUID), version 4, which provides a stable description of each geographic entity in a boundary pair relationship. Each UUID corresponds to a geographic entity listed in the World Polygons dataset. These fields allow for linkage between individual lines in the LSIB and the overall World Polygons dataset. Five additional fields in the LSIB expand on the UUID concept and either describe features that have changed across space and time or indicate relationships between previous versions of the feature. The “LSIB_ID” attribute is a UUID value that defines a specific instance of a feature. Any change to the feature in a lineset requires a new “LSIB_ID.” The “ANTECIDS,” or antecedent ID, is a UUID that references line geometries from which a given line is descended in time. It is used when there is a feature that is entirely new, not when there is a new version of a previous feature. This is generally used to reference countries that have dissolved. The “PREVIDS,” or Previous ID, is a UUID field that contains old versions of a line. This is an additive field, that houses all Previous IDs. A new version of a feature is defined by any change to the feature—either line geometry or attribute—but it is still conceptually the same feature. The “PARENTID” field

The global Government Open Data Management (ODM) Platform market is expected to witness substantial growth in the coming years, driven by the increasing demand for transparency and accountability in government operations. The market is anticipated to reach a value of XX million by 2033, expanding at a CAGR of XX% during the forecast period of 2025-2033. Key drivers of the market include growing government initiatives to improve citizen engagement, rising adoption of cloud-based ODM platforms, and advancements in data analytics and visualization tools. The market is segmented based on application, type, and region. By application, the Information Technology (IT) and Cybersecurity segment is projected to dominate the market due to the increasing demand for data-driven decision-making in government agencies. Cloud-based ODM platforms are anticipated to gain traction due to their scalability, cost-effectiveness, and ease of deployment. Geographically, North America is expected to be the largest market, followed by Europe and Asia Pacific. Government initiatives to promote open data and the presence of key players in these regions contribute to their market dominance.

The data visualization and analysis platform market has witnessed steady growth over the past few years and is projected to continue its upward trajectory in the coming years. In 2025, the market was valued at USD 6580 million, and it is expected to reach USD 15420 million by 2033, exhibiting a CAGR of 8.5%. This growth can be attributed to the increasing adoption of data visualization tools by businesses looking to gain insights from their data and make informed decisions. The market for data visualization and analysis platforms is segmented by application, type, and geography. By application, the market is divided into enterprise and government. By type, the market is segmented into area & size visualization, color visualization, graphical visualization, geospatial visualization, and conceptual visualization. Geographically, the market is divided into North America, South America, Europe, the Middle East & Africa, and Asia Pacific. North America is the largest market for data visualization and analysis platforms, followed by Europe and Asia Pacific. The increasing adoption of data visualization tools by businesses in these regions is driving the growth of the market.

Web map service according to the INSPIRE profile of ISO/DIS 19128 for the visualization of the INSPIRE cartography of the Government of La Rioja, in EPSG:23030; EPSG:25830; EPSG:32630; EPSG:4230; EPSG:4258; EPSG:3857 and EPSG:4326.

Geographical coverage is defined by the delimiting table: West: -3.13, this: -1.70, South: 41.95, North: 42.63

This data set includes the FEMA disaster tribal declarations found on fema.gov/data-visualization and was created using the publicly available disaster declarations summary dataset published by OpenFEMA, FEMA's open government program. The original Disaster Declarations dataset OpenFEMA publishes can be downloaded here http://www.fema.gov/media-library/assets/documents/28318.

This dataset contains FEMA applicant-level data for the Individuals and Households Program (IHP). All PII information has been removed. The location is represented by county, city, and zip code. This dataset contains Individual Assistance (IA) applications from DR1439 (declared in 2002) to those declared over 30 days ago. The full data set is refreshed on an annual basis and refreshed weekly to update disasters declared in the last 18 months. This dataset includes all major disasters and includes only valid registrants (applied in a declared county, within the registration period, having damage due to the incident and damage within the incident period). Information about individual data elements and descriptions are listed in the metadata information within the dataset.rnValid registrants may be eligible for IA assistance, which is intended to meet basic needs and supplement disaster recovery efforts. IA assistance is not intended to return disaster-damaged property to its pre-disaster condition. Disaster damage to secondary or vacation homes does not qualify for IHP assistance.rnData comes from FEMA's National Emergency Management Information System (NEMIS) with raw, unedited, self-reported content and subject to a small percentage of human error.rnAny financial information is derived from NEMIS and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and application of business rules, this financial information may differ slightly from official publication on public websites such as usaspending.gov. This dataset is not intended to be used for any official federal reporting. rnCitation: The Agency’s preferred citation for datasets (API usage or file downloads) can be found on the OpenFEMA Terms and Conditions page, Citing Data section: https://www.fema.gov/about/openfema/terms-conditions.rnDue to the size of this file, tools other than a spreadsheet may be required to analyze, visualize, and manipulate the data. MS Excel will not be able to process files this large without data loss. It is recommended that a database (e.g., MS Access, MySQL, PostgreSQL, etc.) be used to store and manipulate data. Other programming tools such as R, Apache Spark, and Python can also be used to analyze and visualize data. Further, basic Linux/Unix tools can be used to manipulate, search, and modify large files.rnIf you have media inquiries about this dataset, please email the FEMA News Desk at FEMA-News-Desk@fema.dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open Government program, please email the OpenFEMA team at OpenFEMA@fema.dhs.gov.rnThis dataset is scheduled to be superceded by Valid Registrations Version 2 by early CY 2024.