Use the Media Map template to maximize the potential of a map with map navigation tools, time animation, and swipe. Display and animate time-enabled data to highlight changes over time. Set the option to disable scroll and configure pop-ups to optimize the app for embedding, even in a small web page space. Enable the export tool to allow users to save the map to a file for export. Examples: Support a map with descriptive text by including an information panel with a title and description, or a splash screen to help orient your audience and communicate your message. Provide an app with common map tools, including a legend, layer list, basemap toggle, overview map, swipe, and time slider. Allow app users to choose between two basemaps to explore different perspectives. Data requirements The Media Map template has no data requirements. Key app capabilities Time - Provide a configurable time slider that animates changes in data over time. The map must be time enabled. Swipe tool - Compares two layers in the map by viewing them simultaneously. Hover pop-ups - Provide users quick access to attribute information that appears when hovering over a feature in the map. Locator map - Display an inset map with the app's map area in the context of a broader area. Layer list - Display a list of layers with options to turn visibility off and on in the map or scene. This setting also allows opening a layer's attribute table, which includes an option for users to export their records as a .csv file. Bookmarks - Allow users to zoom and pan to a collection of preset extents that are saved in the map. Export - Capture an image (PDF, JPG, or PNG) from the app that a user can save. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

Financial overview and grant giving statistics of Maps Media Institute Inc.

Our dataset offers a unique blend of attributes from YouTube and Google Maps, empowering users with comprehensive insights into online content and geographical reach. Let's delve into what makes our data stand out:

Unique Attributes: - From YouTube: Detailed video information including title, description, upload date, video ID, and channel URL. Video metrics such as views, likes, comments, and duration are also provided. - Creator Info: Access author details like name and channel URL. - Channel Information: Gain insights into channel title, description, location, join date, and visual branding elements like logo and banner URLs. - Channel Metrics: Understand a channel's performance with metrics like total views, subscribers, and video count. - Google Maps Integration: Explore business ratings from Google My Business and location data from Google Maps.

Data Sourcing: - Our data is meticulously sourced from publicly available information on YouTube and Google Maps, ensuring accuracy and reliability.

Primary Use-Cases: - Marketing: Analyze video performance metrics to optimize content strategies. - Research: Explore trends in creator behavior and audience engagement. - Location-Based Insights: Utilize Google Maps data for market research, competitor analysis, and location-based targeting.

Fit within Broader Offering: - This dataset complements our broader data offering by providing rich insights into online content consumption and geographical presence. It enhances decision-making processes across various industries, including marketing, advertising, research, and business intelligence.

Usage Examples: - Marketers can identify popular video topics and optimize advertising campaigns accordingly. - Researchers can analyze audience engagement patterns to understand viewer preferences. - Businesses can assess their Google My Business ratings and geographical distribution for strategic planning.

With scalable solutions and high-quality data, our dataset offers unparalleled depth for extracting actionable insights and driving informed decisions in the digital landscape.

The dataset presents a list of laboratories set up in the humanities, digital humanities, and media studies within universities across the world in 1983-2018. The data are collected and organized in an interactive map designed in the digital StoryMapJS tool, creating a valuable visible representation of the laboratory concept from a geographical and historical perspective. Based on the interactive map, I analyze the history of the laboratory in the humanities within a global context from the 1980s to 2018. The dataset includes 214 laboratories.

Data collection

I identified laboratories by using different resources such as universities’ websites, articles, and research projects. Besides, I sent a questionnaire to the most relevant networks in October 2018 to identify even more labs created in (digital) humanities and media studies at universities.

Data organization

I collected data about each lab based on its website and other resources. I extracted the following data: year established, year ended (if applicable), lab’s name, university, city, country, affiliation and location (if provided), disciplines and keywords (based on labs’ statements and projects and aiming to situate a lab), selected projects (if provided), purpose (a short quotation of a lab’s statement published on its website), website, and geographical latitude and longitude. I organized all the data in chronological order according to year established in Google Sheets. Next, I used StoryMapJS, a free tool designed by the Northwestern University’s Knight Lab, to map my data.

This is data collection to create crow-sourced cognitive maps of Bundang, Ilsan, Dongtan, Songdo in Republic of Korea.

Supplementary material for the article "A Bibliometric Map of Research in Media Psychology" (2025), published in the Atlantic Journal of Communication. There are four files: the SciMat maps, the VOSviewer maps, the records database, and the technical specifications.

The dataset aims to product a technical infrastructure to analyse the French media ecosystem. The dataset is composed of a large sample of websites of major authoritative news media and alternative sources. Each website of media is associated with topological and statistical metadata, qualitative metadata related to their administrative status and information about fact checks.

The post-digital era is characterized by the vast presence of platforms imposing their digital affordances and algorithmic control on our behavior. This environment is challenging education and training, with implications for digital and transmedial literacy. Investigating instructional methodologies is crucial to foster critical comprehension of such novel informational environments. The argument maps (AM), which were first created and evaluated in static information contexts (analogical/old web), could be useful in the emergence of dynamic (post-digital) textual forms.

The current paper describes a comprehensive literature review based on the assumptions above. We looked into state of the art in research on using AM to handle dynamic information. We found 150 papers using a PRISMA procedure and then examined 25 of them. Our review produced pertinent data about the current state of AM, including the sorts of texts on which they are used and the tools (especially digital and AI-based) that have been employed. Our research lays the groundwork for teaching the literacies needed in new informational settings, such as multimodal, dynamic, algorithmic, and data-driven contexts, with a specific focus on AM as an effective mediational tool.

This Zenodo record presents the full dataset composed of the following sheets:

Codebook

Italian Journals

List of articles extracted from SCOPUS

List of articles extracted from ERIC

List of articles extracted from WOS

List of articles extracted from DOAJ

PRISMA workflow

Analysis - First Level (classification of 25 articles selected)

Analysis - Second Level (List of 19 articles selected)

Final Dataset

Interrater Agreement.

As for the Keywords' Map, a primo file .txt displays the text over which basis was performed the keyword maps analysis. The second .txt file shows notes relating to the analysis procedures using the software VOS-Viewer http://www.vosviewer.com/

Any comments or improvements are welcome!

Numerous visualisation methods have been proposed, including Origin-Destination maps to represent movement patterns gathered from social media; however, visual clutter remains a persistent issue due to complex data dimensionality. Besides, most Origin-Destination maps fail to illustrate the temporal dimension of social network phenomena within the geographical environment. To tackle this issue, we propose the visualisation method for geo-located Facebook social-media data while emphasising the time aspect. Based on the citizen-generated data for the European Union (EU), we estimated the EU citizens’ residing or travelling across the EU member states as a means of current and previous destinations to reveal the extent of the hypothetical human migration. The proposed methodology consists of Origin-Destination maps implemented within the time geography framework as a model to support the process of analysis for decision-making. The generated visualisation allows comprehension of the scale of human movement distribution internally within the EU from a space–time perspective.

This game presents the libraries and media libraries of Île-de-France as well as the constructions supported by the Region between 2000 and 2013.

Source: cross-referenced files of the Ile-de-France departments and the Ministry of culture, verified and updated. On the result file were added aid from the Region for construction, with the amount and the year, over the period 2000-2013 (data communicated by the Book service of the Region).

Only facilities open to the public appear in the file (projects under construction or facilities not open to the public do not appear).

Are you looking to identify B2B leads to promote your business, product, or service? Outscraper Google Maps Scraper might just be the tool you've been searching for. This powerful software enables you to extract business data directly from Google's extensive database, which spans millions of businesses across countless industries worldwide.

Outscraper Google Maps Scraper is a tool built with advanced technology that lets you scrape a myriad of valuable information about businesses from Google's database. This information includes but is not limited to, business names, addresses, contact information, website URLs, reviews, ratings, and operational hours.

Whether you are a small business trying to make a mark or a large enterprise exploring new territories, the data obtained from the Outscraper Google Maps Scraper can be a treasure trove. This tool provides a cost-effective, efficient, and accurate method to generate leads and gather market insights.

By using Outscraper, you'll gain a significant competitive edge as it allows you to analyze your market and find potential B2B leads with precision. You can use this data to understand your competitors' landscape, discover new markets, or enhance your customer database. The tool offers the flexibility to extract data based on specific parameters like business category or geographic location, helping you to target the most relevant leads for your business.

In a world that's growing increasingly data-driven, utilizing a tool like Outscraper Google Maps Scraper could be instrumental to your business' success. If you're looking to get ahead in your market and find B2B leads in a more efficient and precise manner, Outscraper is worth considering. It streamlines the data collection process, allowing you to focus on what truly matters – using the data to grow your business.

https://outscraper.com/google-maps-scraper/

As a result of the Google Maps scraping, your data file will contain the following details:

Query Name Site Type Subtypes Category Phone Full Address Borough Street City Postal Code State Us State Country Country Code Latitude Longitude Time Zone Plus Code Rating Reviews Reviews Link Reviews Per Scores Photos Count Photo Street View Working Hours Working Hours Old Format Popular Times Business Status About Range Posts Verified Owner ID Owner Title Owner Link Reservation Links Booking Appointment Link Menu Link Order Links Location Link Place ID Google ID Reviews ID

If you want to enrich your datasets with social media accounts and many more details you could combine Google Maps Scraper with Domain Contact Scraper.

Domain Contact Scraper can scrape these details:

Email Facebook Github Instagram Linkedin Phone Twitter Youtube

Division into map sheets of medium scale base maps at scale 1:1,000,000 (KZM 1M) allows localization of map sheets of Base maps 1:25,000, 1:50,000, 1:100,000 and 1:200,000 based on the Map of the Czech Republic 1: 1,000,000. Map layout consists of the system of neat lines which indicates the relative position and identification of map sheets of Base maps 1:200,000, 1:100,000 and 1:50,000 and location of Base map 1:25,000 map sheets. Map lettering includes standard geographical names (names of settlements,hydrografy and orographic units), numeric designation of map sheets of base maps at scales 1:200,000, 1:100,000 and 1:50,000, name and scale of map layout, tirage data, data of graphic scale and text part of map legend. Map legend includes map layout of medium scale base maps, limitation and examples of numeric designation of base maps at scales 1:25,000 to 1:200,000 and map symbols of district, regional and state boundaries. The subjects of topographic content (ie planimetry and geographic names) and map layout of medium scale base maps, with the exception of national administrative boundaries, are shown also on adjacent parts of the neighboring countries territory. In the overview of map layout neat lines are only in the neighboring countries territory of the map sheets which contain the Czech Republic territory.

This dataset contains all the datasets used in the study conducted for the research publication titled "Mapping dynamic human sentiments of heat exposure with location-based social media data". This paper develops a cyberGIS framework to analyze and visualize human sentiments of heat exposure dynamically based on near real-time location-based social media (LBSM) data. Large volumes and low-cost LBSM data, together with a content analysis algorithm based on natural language processing are used effectively to generate heat exposure maps from human sentiments on social media. ## What’s inside - A quick explanation of the components of the zip file * US folder includes the shapefile corresponding to the United State with County as spatial unit * Census_tract folder includes the shapefile corresponding to the Cook County with census tract as spatial unit * data/data.txt includes instruction to retrieve the sample data either from Keeling or figshare * geo/data20000.txt is the heat dictionary created in this paper, please refer to the corresponding publication to see the data creation process Jupyter notebook and code attached to this publication can be found at: https://github.com/cybergis/real_time_heat_exposure_with_LBSMD

Live Maps is a configurable app template that provides the ability to consume a live data feeds from a variety of sources.Use CasesProvide a map that shows locations of health care facilities and the reported cases of the influenza.Present the locations of political campaign events with related tweets.Configurable OptionsLive Maps is used to combine social media feeds with your operational content, it can be configured using the following options:Map: Choose the web map used in your application.Title: The application name displayed in the header.Subitle: The application subtitle displayed in the header.Color: Choose the color scheme for the application.Feed: The live feed to use in the application, currently supports: Twitter, Flickr, SickWeather.Keyword: Optional search keyword for feeds like Twitter and Flickr.Interval: The interval in minutes to switch between records.Refresh interval: The interval in minutes to refresh the feed.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis application has no data requirements.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

Financial overview and grant giving statistics of Media Awareness Project Map Inc. A Delaware Corporation

The S_LOMR feature class should contain at least one record for each Letter of Map Revision incorporated into the NFHL. Multipart polygons are not allowed. The spatial entities representing LOMRs are polygons. The spatial information contains the bounding polygon for each LOMR area, broken on panel boundaries.Technical Reference - http://www.fema.gov/media-library-data/1449862521789-e97ed4c7b7405faa7c3691603137ec40/FIRM_Database_Technical_Reference_Nov_2015.pdfFlood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the National Flood Hazard Layer with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy. The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. USGS imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information.The NFHL data are from FEMA’s Flood Insurance Rate Map (FIRM) databases. New data are added continually. The NFHL also contains map changes to FIRM data made by Letters of Map Revision (LOMRs). The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications.

According to Cognitive Market Research, the global electronic cartography market size is USD 26.94 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 9.49% from 2024 to 2031. Market Dynamics of Electronic Cartography Market

Key Drivers for Electronic Cartography Market

Rising use of Smartphones and IoT - The prominent factor that drives the market growth include the widespread use of smartphones, tablets, and electronic devices. In addition rise in the usage of Internet of Things (IoT) devices, heightened the demand for real-time mapping solutions, consequently driving the demand for the electronic cartography market. In addition, growing dependence on location-based services (LBS), Geographic Information Systems (GIS), and GPS applications for searching nearby theatre halls, gasoline stations, restaurants, urban planning, disaster management, is another factor that drives the demand for electronic cartography during the forecast period.
The increasing need for real-time data mapping to create precise and current digital representations, combined with the capability to analyze and visualize streaming data from sensors, devices, and social media feeds, is expected to propel market growth.

Key Restraints for Electronic Cartography Market

Integrating geographic,and geo-social data from different sources, such as social media and satellite imagery, can be challenging due to differences in data formats and scales.
Lack of expertise among users regarding the adoption of electronic cartography in marine industry may hampered the market growth

Introduction of the Electronic Cartography Market

Electronic cartography is a technology that allows to simulate the surrounding area with the help of special technical means and computer programs. Electronic cartography integrated with various processes such as data processing, data acquisitions, map distribution, and map creation. As the demand for topographical information systems grows, the deployment of digital mapping has grown in the government and public sectors. The Science & Technology Directorate (S&T), in May 2024,has launched a digital indoor map navigator Mappedin. This digital indoor map navigator transform floor plans into interactive and easily maintainable digitized maps, and is currently being used by both response agencies and corporate clients. Mappedin provides high-quality 3D map creation, easy-to-use mapping tools and data, map sharing, and data maintenance, to city executives, building owner operators and first responders to make and deliver maps for a variety of safety-related situations—from advance preparation and planning to assistance during emergency incidents. Additionally the rapid rise in the number of smartphone and internet users has fueled industry expansion. Additionally, the increasing number of connected and semi-autonomous vehicles along with anticipated advancements in self-driving and navigation technologies, are expected to boost the demand for electronic cartography market.

Urban sound has a huge influence over how we perceive places. Yet, city planning is concerned mainly with noise, simply because annoying sounds come to the attention of city officials in the form of complaints, whereas general urban sounds do not come to the attention as they cannot be easily captured at city scale. To capture both unpleasant and pleasant sounds, we applied a new methodology that relies on tagging information of georeferenced pictures to the cities of London and Barcelona. To begin with, we compiled the first urban sound dictionary and compared it with the one produced by collating insights from the literature: ours was experimentally more valid (if correlated with official noise pollution levels) and offered a wider geographical coverage. From picture tags, we then studied the relationship between soundscapes and emotions. We learned that streets with music sounds were associated with strong emotions of joy or sadness, whereas those with human sounds were associated with joy or surprise. Finally, we studied the relationship between soundscapes and people's perceptions and, in so doing, we were able to map which areas are chaotic, monotonous, calm and exciting. Those insights promise to inform the creation of restorative experiences in our increasingly urbanized world.

Division into map sheets of medium scale base maps (KZM 500) allows localization of map sheets of medium scale base maps using graphically suppressed content of the Map of the Czech Republic 1: 500,000. Map layout consists of the system of neat lines which indicates the relative position and identification of map sheets of Base maps 1:200,000, 1:100,000, 1:50,000, 1:25,000, 1:10,000. In addition map lettering includes standard geographical names, spot heights (altitude), numeric designation of map sheets of base maps at scales 1:25,000 to 1:200,000 in map layout, name and scale of map sheets, tirage data, data of graphic scale, text part of map legend and frame data (geographical coordinates). Map legend includes map layout of Base map 1:10,000, map layout of Base maps 1:50,000 and 1:25,000, limitation and examples of numeric designation of base maps at scales 1:10,000 to 1:200,000 and delimitation of Base map 1:10,000 map sheets. The subjects of topographic content KZM 500, with the exception of national administrative boundaries, are shown also on adjacent parts of the neighboring countries territory. In the overview of map layout neat lines are only in the neighboring countries territory of the map sheets which contain the Czech Republic territory.

From today’s point of view, the MMK is a concept floor map with some terrain checks. After mapping in the years 1974 to 1981, the digital data on the MMK were collected with the technical possibilities of that time. GIS systems did not exist yet. It was a technical method for driving down the surface contours with relatively few bases with the aim of determining the area size of the respective mapping unit. The target of the MMK was 1: 100 000. The contours were digitised by the working cards (topographical maps 1: 25000, edition before 1945, with the boundary lines of the catage units). These formed the basis for the printed maps on a scale of 1: 100000, whose topography was distorted for reasons of secrecy. Before 1990, these land regulations were used for the division of conditions and cultivation planning for agricultural production cooperatives and state goods. After 1990, this data was made GIS-capable by the Federal Institute for Geosciences and Raw Materials. Changes were made to the coarse contouring of the individual surfaces only if surfaces overlapped, winding surfaces were present or surfaces were mirrored due to the technical survey procedure. Detected content errors have been fixed. After that, these data were divided into the then five new federal states. Until about 2001, this data was distributed in Brandenburg. After that, the land survey map of the country solved 1: 300000 (BÜK300) with comparable surface resolution and a comprehensive representation of this map.