Timeline shows a series of events in a vertically time-sorted structure.

Cubism.js is a D3 plugin for visualizing time series. Use Cubism to construct better realtime dashboards, pulling data from Graphite, Cube and other sources.

Build your own mapping portal and publish it to the world or to just a few collaborators. WorldMap is open source software.

Topic models aid analysis of text corpora by identifying latent topics based on co-occurring words. Real-world deployments of topic models, however, often require intensive expert verification and model refinement. In this paper we present Termite, a visual analysis tool for assessing topic model quality. Termite uses a tabular layout to promote comparison of terms both within and across latent topics. We contribute a novel saliency measure for selecting relevant terms and a seriation algorithm that both reveals clustering structure and promotes the legibility of related terms. In a series of examples, we demonstrate how Termite allows analysts to identify coherent and significant themes.

openFrameworks is an open source C++ toolkit for creative coding.

Cinder is a community-developed, free and open source library for professional-quality creative coding in C++.

Boundary is the application performance monitoring solution designed for distributed application environments. Boundary addresses two critical challenges faced by DevOps professionals: the need to immediately see and understand the impact of a rapidly changing application together with a significantly higher degree of visibility.

Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method that learns the underlying themes in a large collection of otherwise unorganized documents. This discovered structure summarizes and organizes the documents. However, topic models are high-level statistical tools--a user must scrutinize numerical distributions to understand and explore their results. In this paper, we present a method for visualizing topic models. Our method creates a navigator of the documents, allowing users to explore the hidden structure that a topic model discovers. These browsing interfaces reveal meaningful patterns in a collection, helping end-users explore and understand its contents in new ways. We provide open source software of our method. Understanding and navigating large collections of documents has become an important activity in many spheres. However, many document collections are not coherently organized and organizing them by hand is impractical. We need automated ways to discover and visualize the structure of a collection in order to more easily explore its contents. Probabilistic topic modeling is a set of machine learning tools that may provide a solution (Blei and Lafferty 2009). Topic modeling algorithms discover a hidden thematic structure in a collection of documents; they find salient themes and represent each document as a combination of themes. However, topic models are high-level statistical tools. A user must scrutinize numerical distributions to understand and explore their results; the raw output of the model is not enough to create an easily explored corpus. We propose a method for using a fitted topic model to organize, summarize, visualize, and interact with a corpus. With our method, users can explore the corpus, moving between high level discovered summaries (the "topics") and the documents themselves, as Figure 1 illustrates.

The goal of this article is to assist designers, researchers, professional analysts, procurement officers, educators, and students in evaluating and creating visual analysis tools. We present a taxonomy of interactive dynamics that contribute to successful analytic dialogues. The taxonomy consists of 12 task types grouped into three high-level categories, as shown in table 1: (1) data and view specification (visualize, filter, sort, and derive); (2) view manipulation (select, navigate, coordinate, and organize); and (3) analysis process and provenance (record, annotate, share, and guide). These categories incorporate the critical tasks that enable iterative visual analysis, including visualization creation, interactive querying, multiview coordination, history, and collaboration. Validating and evolving this taxonomy is a community project that proceeds through feedback, critique, and refinement.

jsPlumb provides a means for a developer to visually connect elements on their web pages. It uses SVG or Canvas in modern browsers, and VML on IE 8 and below.

Tableau Public is a free service that lets you create and share data visualizations on the web. Thousands use it to share data on websites and blogs and through social media like Facebook and Twitter. Tableau Public allows you to see data efficiently and powerfully without any programming.

Positive law, inscribed in legal texts, entails an authority not inherent in literary texts, generating legal consequences that can have real effects on a person’s life and liberty. The interpretation of legal texts, necessarily a normative undertaking, resists the mechanical application of rules, though still requiring a measure of predictability, coherence with other relevant legal norms and compliance with constitutional safeguards. The present proliferation of legal texts on the internet (codes, statutes, judgments, treaties, doctrinal treatises) renders the selection of relevant texts and cases next to impossible. We may expect that systems to mine these texts to find arguments that support one’s case, as well as expert systems that support the decision-making process of courts, will end up doing much of the work.

This raises the question of the difference between human interpretation and computational pattern-recognition and the issue of whether this difference makes a difference for the meaning of law. Possibly, data mining will produce patterns that disclose habits of the minds of judges and legislators that would have otherwise gone unnoticed (reinforcing the argument of the ‘legal realists’ at the beginning of the 20th century). Also, after the data analysis it will still be up to the judge to decide how to interpret the results or up to the prosecution which patterns to engage in the construction of evidence (requiring a hermeneutics of computational patterns instead of texts). My focus in this paper regards the fact that the mining process necessarily disambiguates the legal texts in order to transform them into a machine-readable data set, while the algorithms used for the analysis embody a strategy that will co-determine the outcome of the patterns. There seems a major due process concern here to the extent that these patterns are invisible for the naked human eye and will not be contestable in a court of law, due to their hidden complexity and computational nature.

This position paper aims to explain what is at stake in the computational turn with regard to legal texts. This prepares for the question I want to put forward to those involved in distant reading and not-reading of texts: could a visualization of computational patterns constitute a new way of un-hiding the complexity involved, opening the results of computational ‘knowledge’ to citizens’ scrutiny?

Visualizing and analyzing social networks is a challenging problem that has been receiving growing attention. An important first step, before analysis can begin, is ensuring that the data is accurate. A common data quality problem is that the data may inadvertently contain several distinct references to the same underlying entity; the process of reconciling these references is called entity resolution. D-Dupe is an interactive tool that combines data mining algorithms for entity resolution with a task-specific network visualization. Users cope with complexity of cleaning large networks by focusing on a small subnetwork containing a potential duplicate pair. The subnetwork highlights relationships in the social network, making the common relationships easy to visually identify. D-Dupe users resolve ambiguities either by merging nodes or by marking them distinct. The entity resolution process is iterative: as pairs of nodes are resolved, additional duplicates may be revealed; therefore, resolution decisions are often chained together. We give examples of how users can flexibly apply sequences of actions to produce a high quality entity resolution result.

Writing Without Words is a project that explores methods of visually representing text and visualizes the differences in writing styles of various authors.

London-based artist Stefanie Posavec has a gift for words. Or for the lack thereof, to be exact. Her latest project, Writing Without Words, explores the literary world when its most important building blocks are removed by visually representing text.

How do we explore? If you move to a new city, you might learn the territory by walking around. Or you might peruse a map. But far more effective than either is both together — a street-level experience with higher-level guidance.

Likewise, the most powerful way to gain insight into a system is by moving between levels of abstraction. Many designers do this instinctively. But it's easy to get stuck on the ground, experiencing concrete systems with no higher-level view. It's also easy to get stuck in the clouds, working entirely with abstract equations or aggregate statistics.

This interactive essay presents the ladder of abstraction, a technique for thinking explicitly about these levels, so a designer can move among them consciously and confidently.

Pronounced "geo" or "jQuery geo", this open-source project from Applied Geographics provides a streamlined API for a large percentage of your online mapping needs. Whether you just want to display a map on a wep page as quickly as possible or you are a more advanced GIS user, $.geo can help!

Load SPARQL result table from an end-point as a data.frame

This listing is but an initial step in portraying the history of the visualization of data. We started with the developments listed by Beniger and Robyn (BenigerRobyn:1978) and incorporated additional listings from Hankins (Hankins:1999), Tufte (Tufte:1983, Tufte:1990, Tufte:1997), Heiser (Heiser:2000), and others (now too numerous to cite individually). In most cases, we cite original sources (where known) for the record; occasional secondary sources are included as well, where they appear to contribute to telling the story.

To convey a real sense of the accomplishments requires much more context- words, images, and, most usefully, interpretation. In this chronological listing, it has proved convenient to make divisions by epochs, and we provide some more detailed commentaries for each of these. The careful reader will be able to discern other themes, relations, and connections, not stated explicitly.

I’d like to propose a working definition of computational journalism as the application of computer science to the problems of public information, knowledge, and belief, by practitioners who see their mission as outside of both commerce and government. This includes the journalistic mainstay of “reporting” — because information not published is information not known — but my definition is intentionally much broader than that. To succeed, this young discipline will need to draw heavily from social science, computer science, public communications, cognitive psychology and other fields, as well as the traditional values and practices of the journalism profession.

The extra work required in producing graphs is rewarded by greatly enhanced presentation and communication of empirical results.

Creates a GraphViz dot file for the specified app names. You can pass multiple app names and they will all be combined into a single model. Output is usually directed to a dot file.

Gephi is a visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.

NodeBox is a Mac OS X application that lets you create 2D visuals (static, animated or interactive) using Python programming code and export them as a PDF or a QuickTime movie. NodeBox is free and well-documented.