Research Data Management

As an open-source suite of web visualization components that make use of the Python language, Candela emphasizes scalable, rich visualizations created with a normalized API for use in real-world data science situations.

With Chartbuilder’s intuitive web-based application, creating charts and diagrams is a matter of copy and paste. Easy-to-understand buttons and settings, as well as a consistent display showing what your visualizations look like on mobile and desktop browsers, allow for a clean user experience.

A clean user interfaces and easy to use. All you have to do is upload a CSV file, or a Google Sheets link, and it’ll generate the chart for you.

Chartist.js includes a large array of charts that are responsive, animated, and rendered beautifully.

In reality, this is not really a data visualization tool on its own but more of an additional tool to enhance your data storytelling. By providing options for colors and styles painted on a complicated map graph, ColorBrewer gives you the chance to experiment and make informed decisions on your data visualizations.

D3 is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS. D3's emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualisation components and a data-driven approach to DOM manipulation.

Datawrapper is an extremely easy-to-use data visualization tool for plotting interactive charts. All you need to do is upload your data via a CSV file, choose the chart you want to plot. It's free and no sign-up needed.

In reality, this is not really a data visualization tool on its own but more of an additional tool to enhance your data storytelling. By providing options for colors and styles painted on a complicated map graph, ColorBrewer gives you the chance to experiment and make informed decisions on your data visualizations.

Dygraphs is a JavaScript charting library that allows for panning, zooming, and mouse-over actions. It handles and interprets dense data sets very effectively.

Flot is an easy-to-use charting library that provides very elegant charts and graphs. It allows advanced user-interactions like panning, zooming, resizing, switching a data series on and off, and more.

Built on JavaScript, FusionCharts provides ready-to-use code snippets to create your own data visualizations based on popular templates from the typical bar and column charts to treemaps and waterfall charts. One of the biggest benefits of using FusionCharts is that it integrates perfectly with popular JavaScript frameworks, as well as front-end and back-end frameworks, allowing for a greater level of customization.

An extension of Google Charts, Google Data Studio provides further functionalities to create full reports based on analytics. These reports are fully customizable with data visualizations and trackable via Google Analytics, giving you a wider view of your data. Most importantly, its integrations with Google’s other products, like Google Sheets and Google Cloud Storage, is crucial for any pre-existing user of Google’s suite of digital solutions.

Google Charts is user-friendly and compatible with all browsers and platforms. It covers a wide range of data visualization types — from simple line and bar graphs to complex hierarchical tree maps — making Google charts suitable for almost any project.

Beautiful and highly customizable, Infogram features a Microsoft Word-style dashboard that carries the capabilities of Excel and most other visualization platforms. It’s drag-and-drop markdown menu style also allows for solid reports to be created, helping to bring data storytelling to the next level.

Leaflet is an open-source JavaScript library that specializes in mobile-friendly, responsive, and interactive maps. With particularly readable source code and documentation, Leaflet is easy to pick up for beginner coders and works well across different platforms.

Developed at the Humanities + Design lab at Stanford University, Palladio is a browser-based visualization tool built to handle immense amounts of historical data with relative ease. Palladio is, however, more specialized, focusing on specific case studies and research questions. Some of these features include a gallery view, list view, map view, and a special graph view for illustrating relationships between data points.

For those familiar with Microsoft Excel, pivot tables are a complex but powerful tool for distilling and displaying data. An interesting means of data storytelling, PivotTable.js is a free web pivot table that allows users to explore data using an easy drag-and-drop format.

An open-source library for R, Python, and JavaScript, Plotly works seamlessly with its enterprise-ready deployment servers to enable easy and code-free collaborations. For those with some knowledge of coding, tutorials and further guidance enhance Plotly’s functionalities.

As its name suggests, Polymaps is for creating catographical data visualizations. It pulls in data from OpenStreetMap, Bing, and other map image providers, while also rendering its own representations.

Raw bridges the gap between spreadsheets and vector graphics. It’s built on the D3.js platform. If you’re not a programmer, Raw could be the perfect data visualization tool for you. Raw provides a selection of 16 ready-to-use chart types. Customization is one of the biggest positive aspects of Raw, for it allows you to use your own custom layouts.

Shiny is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards. You can also extend your Shiny apps with CSS themes, html widgets, and JavaScript actions.

Your data has a story. Share it with the world. Visualize and publish data on topics you care about. Explore and be inspired by creations from like-minded data enthusiasts.

TimelineJS is a great tool for creating interactive, visually rich timelines without having to write code. TimelineJS has built-in API support for a variety of data sources like Wikipedia, Twitter, SoundCloud, Vine, Google Maps, and YouTube.