The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of location-based services (LBS) and geographic information systems (GIS) across industries like real estate, tourism, logistics, and urban planning is a major catalyst. Businesses are increasingly leveraging interactive maps to enhance customer engagement, improve operational efficiency, and gain valuable insights from geospatial data. Furthermore, advancements in mapping technologies, including the integration of AI and machine learning for improved data analysis and visualization, are contributing to market growth. The accessibility of user-friendly tools, coupled with the decreasing cost of cloud-based solutions, is also making interactive map creation more accessible to a wider range of users, from individuals to large corporations. However, the market also faces certain challenges. Data security and privacy concerns surrounding the use of location data are paramount. The need for specialized skills and expertise to effectively utilize advanced mapping technologies may also hinder broader adoption, particularly among smaller businesses. Competition among established players like Mapbox, ArcGIS StoryMaps, and Google, alongside emerging innovative solutions, necessitates constant innovation and differentiation. Nevertheless, the overall market outlook remains positive, with continued technological advancements and rising demand for data visualization expected to propel growth in the coming years. Specific market segmentation data, while unavailable, can be reasonably inferred from existing market trends, suggesting a strong dominance of enterprise-grade solutions, but with substantial growth expected from simpler, more user-friendly tools designed for individuals and small businesses.

This dataset was created within an independent project seeking to further analyze and understand trends in filming locations for films and television in recent years. Analysis highlights the 50 highest-grossing films for the United States domestic box office in 2019, 2023, and 2024, as well as the 50 most-watched television series in the United States during the 2024-2025 season.

My comprehensive data analysis and visualization can be found at the Tableau dashboard linked HERE.

I created the Executive Summary below to provide further analysis, consolidating context and insights into major takeaways. As one aim of this project is to make filming location data more easily accessible, all Data Spreadsheets that I created for the project are below as well.

Location Intelligence Market size was valued at USD 18.5 Billion in 2024 and is projected to reach USD 63.15 Billion by 2032, growing at a CAGR of 15.63% from 2026 to 2032.Proliferation of Spatial Data: A rich source of data for location intelligence and analytics is made possible by the exponential increase of spatial data produced by sources including GPS enabled devices, Internet of Things sensors, and geographic information systems (GIS). In order to extract meaningful insights, there is a growing need for sophisticated tools and technologies due to the volume and diversity of spatial data.Location Based Services (LBS) are Growing: The demand for location intelligence and analytics solutions is fueled by the widespread use of location based services including ride sharing services, navigation apps, and location based marketing. Companies use location data to target services based on local context, optimize operations, and improve customer experiences.

The Geographic Information Systems (GIS) platform market is poised for substantial growth, projected to reach an estimated market size of $XXX million in 2025, with a Compound Annual Growth Rate (CAGR) of XX% expected throughout the forecast period of 2025-2033. This robust expansion is primarily driven by the increasing demand for sophisticated data visualization, spatial analysis, and location-based services across a multitude of sectors. The government and utilities sector is a significant contributor, leveraging GIS for infrastructure management, urban planning, resource allocation, and emergency response. Commercial applications are also rapidly adopting GIS for customer analytics, supply chain optimization, real estate development, and targeted marketing. The proliferation of web-enabled GIS solutions, including Web Map Services, is democratizing access to geospatial data and tools, fostering innovation and wider adoption beyond traditional GIS professionals. Desktop GIS continues to hold its ground for complex analytical tasks, but the trend towards cloud-based and mobile GIS solutions is accelerating, offering greater flexibility and scalability. Key trends shaping the GIS platform market include the integration of Artificial Intelligence (AI) and Machine Learning (ML) for advanced spatial analytics and predictive modeling, the growing importance of real-time data processing and streaming, and the rise of open-source GIS solutions challenging established players. The increasing availability of high-resolution satellite imagery and IoT sensor data further fuels the need for powerful GIS platforms. However, certain restraints might temper this growth, such as the initial cost of implementation for some advanced solutions, a potential shortage of skilled GIS professionals, and data privacy concerns associated with extensive location data collection. The market is characterized by intense competition among established global players and emerging innovators, all vying to capture market share by offering comprehensive, user-friendly, and technologically advanced GIS solutions. This comprehensive report delves into the dynamic Geographic Information Systems (GIS) Platform market, providing in-depth analysis and forecasts from 2019 to 2033, with a base year of 2025. The study meticulously examines market concentration, key trends, regional dominance, product insights, and the driving forces and challenges shaping this vital industry. We project the market to reach values in the tens of millions and hundreds of millions of dollars across various segments.

Explore the dynamic Mapping Software market, driven by engineering and industrial design needs. Discover growth drivers, key trends, restraints, and leading companies shaping the future of geospatial solutions from 2019-2033.

This tutorial will teach you how to take time-series data from many field sites and create a shareable online map, where clicking on a field location brings you to a page with interactive graph(s).

The tutorial can be completed with a sample dataset (provided via a Google Drive link within the document) or with your own time-series data from multiple field sites.

Part 1 covers how to make interactive graphs in Google Data Studio and Part 2 covers how to link data pages to an interactive map with ArcGIS Online. The tutorial will take 1-2 hours to complete.

An example interactive map and data portal can be found at: https://temple.maps.arcgis.com/apps/View/index.html?appid=a259e4ec88c94ddfbf3528dc8a5d77e8

Presentation Date: Friday, March 15, 2019. Location: Barnstable, MA. Abstract: A presentation to a crowd of Barnstable High "AstroJunkies," about how we use physics, statistics, and visualizations to turn information from large, public, astronomical data sets, across many wavelengths into a better understanding of the structure of the Milky Way.

Dataset

This dataset was created by CodeBreaker619

Released under Other (specified in description)

Contents

Presentation Date: Monday, April 1, 2019. Location: Radcliffe Institute for Advanced Study at Harvard, Cambridge, MA. Abstract: 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.

For conversion of GPS to KML we used the GPS datatypes such asGPGGAwhich is described as Global Positioning System Fix Data andGPRMCwhichis described as Recommended minimum specific GPS/Transit data. To begin with, we first created two data frames with the given GPS data, by filtering out GPGGA and GPRMC types. As per our observation, we could see that GPGGAtype gave us information like Longitude, Latitude, Altitude, and Fix Quality (ifits 0 0 then it is invalid). On the other hand, GPRMC type fetched information like T Time, Speed in knots and Navigation receiver warning. Out of the other information from GPRMC datatype, we were only interested in speed and re-ceive warning. So we copied those columns and combined these columns into pandas data frame created for type GPGGA. Moving to the next part which is conversion of data. We converted the Latitude and Longitude of$GPGGA us-ing formula DDMMSSSS eg, 4533.35 is 45 degrees and 33.35 minutes. ”.35” of a minute is exactly 21 seconds. We checked for the direction and assigned proper sign as per the directon (W is -ve and E is +ve). We then converted all the numeric columns in dataframe for further calculation. Finally created a tuple with latitude, longitude and speed. This list of tuples was added as coordinates. One of the major challenge was to understand the GPS data.

The global Business Mapping Software market is poised for significant expansion, projected to reach an estimated USD 5,000 million by 2025 and growing at a compound annual growth rate (CAGR) of XX% through 2033. This robust growth is underpinned by the increasing demand for advanced data visualization and spatial analytics across diverse industries. Key drivers include the burgeoning need for optimized logistics and supply chain management, enhanced customer relationship management (CRM) through location intelligence, and improved operational efficiency via dynamic route planning and site selection. The manufacturing sector, in particular, leverages business mapping software for factory layout optimization, resource allocation, and risk assessment in global operations. Similarly, the automotive industry is integrating these solutions for advanced navigation systems, fleet management, and the development of autonomous driving technologies, which heavily rely on precise geospatial data. The financial services sector is also a significant adopter, utilizing mapping software for fraud detection, risk analysis, and identifying optimal branch locations. The market's trajectory is further bolstered by emerging trends such as the widespread adoption of cloud-based solutions, offering greater scalability, accessibility, and cost-effectiveness compared to traditional on-premise installations. This shift democratizes access to sophisticated mapping tools for small and medium-sized enterprises. The integration of AI and machine learning with business mapping platforms is another transformative trend, enabling predictive analytics, pattern recognition, and more intelligent decision-making. However, the market faces certain restraints, including the initial high cost of implementation for some advanced features, the need for specialized skills to leverage the full potential of these tools, and concerns around data privacy and security, especially when dealing with sensitive customer or operational information. Despite these challenges, the continuous innovation and increasing integration of geospatial capabilities into core business processes are expected to drive sustained market growth and adoption across a wide spectrum of industries. Here's a comprehensive report description for Business Mapping Software, incorporating all your specified elements:

MBI is one of the first distributors of HERE Technologies and provides detailed street maps from HERE for most of the countries or territories worldwide.

HERE Maps are available as Essential or Advanced Map. Essential Map is a basic 2D canvas of the world that enables use cases such as basic map display, data visualization, search, localization tracking and tracing.

Building on Essential Map, Advanced Map is the most complete and detailed map available. It includes detailed features for modeling road networks, such as navigable attributes, speed limits, sign text and the full set of Places (Point of Interest), and enables use cases such as point-to-point routing, turn-by-turn navigation, advanced navigation for cars and trucks, business intelligence, planning and optimization, and much more.

The HERE Map product line can be further enriched with additional curated and specialized location content products that enable you to build differentiating location-enabled services and applications. Over 50 premium location content products seamlessly integrate with the HERE Map Data product line, such as Places, Point Addressing, Trucks, Road Infrastructure, and many more. Available in the following formats: GDF, RDF, NavStreets, FGDB,

In this project, we aimed to map the visualisation design space of visualisation embedded in right-to-left (RTL) scripts. We aimed to expand our knowledge of visualisation design beyond the dominance of research based on left-to-right (LTR) scripts. Through this project, we identify common design practices regarding the chart structure, the text, and the source. We also identify ambiguity, particularly regarding the axis position and direction, suggesting that the community may benefit from unified standards similar to those found on web design for RTL scripts. To achieve this goal, we curated a dataset that covered 128 visualisations found in Arabic news media and coded these visualisations based on the chart composition (e.g., chart type, x-axis direction, y-axis position, legend position, interaction, embellishment type), text (e.g., availability of text, availability of caption, annotation type), and source (source position, attribution to designer, ownership of the visualisation design). Links are also provided to the articles and the visualisations. This dataset is limited for stand-alone visualisations, whether they were single-panelled or included small multiples. We also did not consider infographics in this project, nor any visualisation that did not have an identifiable chart type (e.g., bar chart, line chart). The attached documents also include some graphs from our analysis of the dataset provided, where we illustrate common design patterns and their popularity within our sample.

Presentation Date: Friday, December 2, 2022 Location: Barcelona, Spain Abstract: An introduction to data visualization concepts, using key concepts from the "10 Questions to Ask when Creating a Visualization" (10QViz.org) website. Presented at "Data Viz for Society." Featured software includes glue (see glueviz.org and gluesolutions.io). Files included are Keynote slides (in .key and .pdf formats)

Here, we make available the supplemental material regarding data collection from the publicaiton "Research Data Curation in Visualization : Position Paper". The dataset represents an aggregated collection of the data policies of selected publication venues in the areas of visualization, computer graphics, software, HCI, and Virtual Reality with inclusions from multimedia, collaboration, and network visualization, for the years 2021-2022. Based on a derived index, long-term preservation and data sharing are evaluated for each venue. The index ranges from No policy to Required sharing and preservation. Additionally the verbatim statements (or the lack thereof) used to reach the concluded score are also provided. Abstract: Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualization are not yet part of the researcher’s compendium. In this position paper, we discuss the unique challenges visualization faces and propose how data curation can be practically realized. We share eight lessons learned in managing data in two large research consortia, outline the larger curation workflow, and define the typical roles. We complement our lessons with minimum criteria for selecting a suitable data repository and five challenging scenarios that occur in practice. We conclude with a vision of how the visualization research community can pave the way for new curation standards.

ABSTRACT: The MODIS global subsetting and visualization tool provides customized subsets and visualizations of 13 MODIS Collection 5 land products on demand for any land area on Earth, from 1 pixel up to 201 x 201 km. Subset products are made available to the user through an interactive web page. On this page are time series plots, QC information, land cover and phenology, citation, and data download. Users specify a location for the center point of their area of interest by either entering the geographic coordinates or selecting the location on an interactive map. The land area is then defined by specifying the desired number of kilometers “Above and Below†and “Left and Right†of the center point (recall that MODIS land products are in sinusoidal projection). Users then choose the desired MODIS land product and date range for this subset. After providing a valid e-mail address, the request is submitted and the subset and associated products created. The user receives an e-mail with a link to a customized “Data Visualization and Download†page. The tool provides time series plots of the measurement, quality information, land cover grid (land cover classification) of the area and phenology, along with an estimate of heterogeneity (Shannon richness and evenness). The land product subset data are provided in comma-separated value (.csv) and GeoTIFF (.tif) formats.

The data contains ranks of Experts, Masters, and Grandmasters of the Datasets Tier. You can apply EDA to this data and see which country is having the highest-ranked Kaggle Users. Name: User name. Rank: User rank on the leaderboard. Level: User level whether a user is an expert, master, or grandmaster. Link: Profile link Gold: Total number of gold a user got. Silver: Total number of silver a user got. Bronze: Total number of bronze a user got. Points: Total number of points a user got. Joined: Year/Month joined Total Competitions: Total number of competitions a user participated in. Total Dataset: Total number of datasets a user uploaded. Total Codes: Total number of codes/notebooks a user uploaded. Total Discussion: Total number of discussions a user had. Highest Rank: Highest rank hit by a user. Current Rank: User's current rank. Current Level: Current Level represents whether a user's level is expert, master, or grandmaster in one of the four tiers. City: User's city. State: User's state. Country: User's country.