OpenVis Conf is a two-day, single track conference centered around the practice of visualizing data on the web.
Join us to learn about data visualization, information design, data analysis and implementation using the best Open Web technology.
OpenVis Conf will be taking place on April 24th and 25th of 2017 at the State Room in Boston, MA.
Wanna join us
Ticket Info and Policies
All tickets are non-refundable, but are transferable until the day of the conference. You can transfer the ticket directly using the link you receive when you purchased it, or contact us for help.
Sharing their knowledge
Amanda Cox is the editor of The Upshot, at The New York Times. She joined the Times graphics desk in 2005, where she creates charts and maps for the newspaper and its website. With a focus on data visualization, her work with colleagues has won several dozen awards, including top honors at Malofiej, the largest international infographics competition. She has a masters degree in statistics from the University of Washington and received the 2012 Excellence in Statistical Reporting Award from the American Statistical Association. Amanda was OpenVis Conf's first keynote, in 2013.
The Role of Visualization in Exploratory Data Analysis
Visualisation is an important Exploratory Data Analysis (EDA) tool for two reasons:
- 1. Visualisations can surprise you - you might see something that you never expected
- 2. Visualisation can help you refine the vague questions in your head into something that you can answer quantitatively
In this talk, Hadley will discuss these two roles of exploratory visualisation in the context of R, focusing on the importance of rapid iteration, and showing examples of why it's so important to couple visualisations with other EDA tools.
Hadley Wickham is Chief Scientist at RStudio and a member of the R Foundation. He builds tools (both computational and cognitive) that make data science easier, faster, and more fun. His work includes packages for data science (the tidyverse is a collection of libraries such as: ggplot2, dplyr, tidyr, purrr, readr, ...), and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and frequent speaker promoting the use of R for data science.
What story does your timeline tell?
For centuries, people have been drawing timelines to visually communicate stories about sequences of events, from historical and biographical data to project plans and health records. There are many ways to draw a timeline, and depending on how a timeline is drawn, it is possible to emphasize different aspects of the data, such as chronology, periodicity, or synchronicity. However, many contemporary visualization tools do not allow people to easily express themselves with timeline data, often constraining them to a linear chronological design.
In this talk, Matt will embark on a tour of the timeline design space, revisiting old yet interesting designs by the likes of Gerardus Mercator, Elizabeth Peabody, and Mark Twain, as well as highlighting several inspiring bespoke timeline designs from 13pt, Moebio, and Accurat. Matt will also introduce an interactive web-based timeline storytelling tool that he has been developing at Microsoft Research. With this new authoring environment, he aims to unlock the expressive potential of the timeline design space, and allow educators, journalists, and other storytellers to tell a greater variety of timeline stories.
Visualizing Incarceration in the US on Polygraph
The cause of the US's mass incarceration problem is vast and complex, but public discourse weighs heavily towards two stats: prisoner rates and drug crimes. In this talk, Matt will discuss his visual essay on every layer of incarceration, from crime to parole. He'll also review the difficulty of representing the US's prison system and visualization's role in public discourse.
Matt Daniels is a founder of Polygraph, a collection for visualization, and The Pudding, a journal for visual essays. Since 2014, he has authored a number of articles that have gained national attention, such as Rappers, ranked by the size of their vocabulary, Film Dialogue, broken down by gender, and How Music Taste Evolved.
Pulling a polygon out of a hat
Like good stage magic, web visualizations are full of small effects that require surprising complexity behind the scenes. Something straightforward to do by hand, like arranging labels nicely on a map or drawing out a curve, can require unconventional methods and mountains of code to pull off in a browser. In this talk Noah will explore a series of little web animation puzzles that led him on an unexpectedly deep journey into the scary and wonderful world of computational geometry.
Noah Veltman is a developer and journalist who builds interactive graphics and tells data-driven stories. He has worked as a developer on the WNYC Data News Team and as a Knight-Mozilla OpenNews Fellow at BBC News. He once tried to calculate the longest possible subway ride in New York City and failed, but he can tell you that it's at least 154 miles long. Noah's work has won a duPont Award, a Peabody Award, a Malofiej gold medal, and two Society of Professional Journalists Public Service Awards.
Visualizing data with deck.gl
Data is at the core of Uber's business and is fundamental for making informed decisions. The mission of the Visualization team at Uber is to deliver intelligence through the crafting of visual exploratory data analysis tools. To meet these needs, the team developed an open source visualization stack. In this talk Nicolas will give a brief overview of the Visualization team, their history, mission, and the most challenging problems they tackle. Then he'll do a deep dive into their core open source components and libraries that power most data products at Uber. He'll present their abstract and scientific data visualization stack, focusing on deck.gl, a WebGL framework for high-performance visualizations.
Nicolas Belmonte runs the Visualization group (https://eng.uber.com/data-viz-intel/) at Uber. The Visualization team powers many data products across experimentation, machine learning, BI, maps (http://deck.gl), operations, policy, comms, and the advanced technologies group (ATG). Prior to Uber, Nico visualized data at Twitter, where he shaped the interactive.twitter.com project for their public-facing visualization work.
Lisa Charlotte Rost
A Data Point Walks Into a Bar: Designing Data For Empathy
When working with data, it is easy to forget that our audience isn't always rational. As a result, even though data can convey insight, that alone isn't enough to convince our audience to act accordingly. Stories stick, but data doesn't. Stories stick because they make us feel something; and we remember situations in which we felt intense feelings. Stories make us act; they change our beliefs. Stories make us feel warm and empathic and alive. Data doesn't make us feel anything on it’s own. Data is cold.
And still, we all love data, and we all love to work with it. Can we create feelings with data? Away from the beaten paths of company dashboards, scientific plots and newspaper graphics? In this talk, Lisa will showcase some ways to present data so that it sticks. We'll talk about the status quo of data presentation for empathy and where we still need to go.
Lisa Charlotte Rost is a designer from Berlin who's deeply in love with data visualisation. When she's not providing context and overview with her graphics, she writes about tools, map poetry, her Google history or latitudes. In 2016, Lisa was an OpenNews Fellow for the NPR Visuals team; before that, she visualized data for magazines like SPIEGEL, taught data visualization at universities and organized the Data Vis Meetup Berlin.
What happens to your blood sugar when you eat an ice cream cone? How does your heart react when you meditate? What happens to your body when you're really stressed out? These are some of the questions Alan endeavoured to answer with data visualization.
In this talk, Alan will demo the research and visual explorations he's undertaken as he tried to connect to medical devices like insulin pumps, real-time glucose meters and heart rate monitors for his own care as a Type 1 diabetic. He'll also discuss some of the challenges of connecting to these devices, and the power of connecting to your own health by reverse-engineering it.
Alan Mclean designs health and fitness experiences that feel personal and inspire action. Working at the intersection of design and engineeering, he conceptualizes, prototypes and refines new products for Fitbit. Previously he's designed and built exercise visualizations at Strava and interactive graphics in the New York Times Graphics Department.
Why does data vis need a style guide
A style guide is a set of standards for the writing and design of documents, either for general use or for a specific publication, organization, or field. While they are common for visual and brand design, organizations that make use of data visualization in their communication could benefit from a set of guidelines around that as well. In this talk, Amy will talk about what makes a style guide effective, why it is useful, and how style guides apply to data visualization. She will speak about the difference between a style guide and a template, and why organizations should have both. Amy will also share insights into the goals, tone and creation process of a style guide for data visualization, using her work with organizations like the Sunlight Foundation.
Amy Cesal is a graphic designer specializing in data visualization. Before joining the federal government, Amy worked for the Sunlight Foundation, a nonprofit focused on increasing government transparency. At Sunlight, she created one of the first data visualization style guides after working with their team of data scientists. Amy holds a master’s degree in Information Visualization from the Maryland Institute College of Art.
Kanit "Ham" Wongsuphasawat, Dominik Moritz & Arvind Satyanarayan
Vega-Lite: A Grammar of Interactive Graphics
Vega-Lite is a declarative format for rapidly creating interactive visualizations. The simplest form of a Vega-Lite specification describes a single view–a mapping between data values and the visual properties for a single mark type. These single views can be composed into more complex layered and multi-view displays, or made interactive through a novel grammar of interaction. With Vega-Lite, a diverse range of interactive visualizations–from brushing and linking a scatterplot matrix, to cross-filtering and interactive index charts–can be built with only a few dozen lines of JSON. In these concise specifications, users can omit low-level details such as scale, axes, and legends properties as well as event handling logic, letting the Vega-Lite compiler infer sensible defaults. Under the hood, Vega-Lite leverages Vega’s high-performance dataflow architecture and cross-platform renderers for both SVG and Canvas.
Kanit is a PhD Student at the UW Interactive Data Lab, advised by Jeffrey Heer. His research seeks to accelerate data exploration and analysis with better visualization tools including Voyager 2, Voyager, CompassQL, and Vega-Lite.
Kanit holds MS from Stanford and BEng from Chulalongkorn University, and was a recipient of Fulbright Scholarship. He has worked at a number of leading data-driven companies including Google, Tableau, Trifacta, and Thomson Reuters. At Google, Kanit also designed the Graph Visualization for TensorFlow.
Dominik is a PhD student in Computer Science at the University of Washington. He is advised by Bill Howe from the eScience Institute and the Database Group and Jeff Heer from the Interactive Data Lab. Before coming to the US, Dominik has completed his undergraduate studies at Hasso-Plattner-Institute in Germany. In his research, he combines large-scale systems for data analysis with interactive data visualization to enable novel insights into large multi-dimensional data.
Dominik is a co-author of various libraries and tools in the Vega stack, including Vega-Lite, Voyager, and Polestar. He has worked for the Open Knowledge Foundation, Google, and Microsoft Research and has been awarded fellowships by the German National Academic Foundation and the Fulbright Committee. When he is not working on research or coding, Dominik likes to travel, sail, hike in the mountains around Seattle, or bake bread.
Arvind Satyanarayan is a Computer Science PhD candidate at Stanford University, working with Jeffrey Heer and the University of Washington Interactive Data Lab. Arvind's research develops new declarative languages for interactive visualization, and leverages them in new systems for visualization design and data analysis. His work has been recognized with a Google PhD Fellowship, Best Paper Awards at IEEE InfoVis and ACM CHI, and has been deployed on Wikipedia to enable interactive visualizations within articles.
Catherine D'Ignazio & Rahul Bhargava
Designing Visualization Tools for Learners
Communicating with data is becoming popular in fields far beyond data science, statistics and graphic design. People working in government, journalism, education, non-profits, and the arts are working with data. What this means is that there are many newcomers to the field who are not familiar with the process, vocabulary and methods. Currently our tools do not support them well.
It's not for lack of tools. There has been a proliferation of tools created to assist novices in gathering, working with, and visualizing data. We have logged more than 500 such tools and the list keeps growing. But one of the challenges for new learners is that designers have prioritized features that quickly create strong visuals, at the expense of tools that scaffold a process for learners.
In this talk Catherine and Rahul will take you through a quick tour of this tool universe from the perspective of learners new to data analysis and visualization. They will show their four design principles for learner-centered data tools and give examples of those principles in action.
Catherine D'Ignazio is a scholar, artist/designer and software developer who focuses on data literacy and visualization for civic engagement and community empowerment. Her research at the intersection of technology, design & the humanities has been published in the Journal of Peer Production, the Journal of Community Informatics, and the proceedings of Human Factors in Computing Systems (ACM SIGCHI). Her art and design projects have won awards from the Tanne Foundation, Turbulence.org and the Knight Foundation and exhibited at the Venice Biennial and the ICA Boston.
D'Ignazio is an Assistant Professor of Civic Media and Data Visualization at Emerson College, a principal investigator at the Engagement Lab and a research affiliate at the MIT Center for Civic Media. She holds an MFA from Maine College of Art, an MS from the MIT Media Lab and a BA (Summa Cum Laude, Phi Beta Kappa) from Tufts University.
Rahul Bhargava is a researcher and technologist specializing in civic technology and data literacy. He creates interactive websites used by hundreds of thousands of people, playful educational experiences across the globe, and award-winning visualizations for museum settings. As a Research Scientist at the MIT Center for Civic Media, Rahul leads technical development on projects ranging from interfaces for quantitative news analysis, to platforms for crowd-sourced sensing. He has a special interest in how new technologies are introduced to people in settings focused on learning. Rahul is a drummer and father based in Somerville, MA. He holds a MS from the MIT Media Lab and a BS from Carnegie Mellon University.
Shirley Wu & Nadieh Bremer
Data Sketch|es: A Visualization A Month
Data sketches is a collaboration between Shirley Wu and Nadieh Bremer, where they choose a topic and visualize it by the end of the month. The collaboration started for many reasons: they weren’t creating as many personal data visualization projects, so they were looking for the motivation to make more. They wanted to explore their creativity, to experiment with the tools that are out there, to learn from each other, and to have fun.
In this talk, Shirley and Nadieh will share the lessons they learned while working on Data Sketches. They will highlight their favorite months of data, sketches, and code: what made them their favorites, the mistakes made along the way, and how they overcame them. They hope that by sharing their visualizations' humble, ugly duckling beginnings and their many (embarrassing) iterations, that it will inspire others to create their own unique and compelling visualizations.
Shirley Wu is currently a freelance consultant specializing in data visualization. Previously, she was a software engineer at security company Illumio working on an interesting part of the product called Illumination: a visualization of application traffic and visual tools for writing security policy on top of them.
Most recently, Shirley has worked on An Interactive Visualization of Every Line in Hamilton, The Political Brain, Four Years of Vacations in 20,000 colors, and film flowers. She is a co-organizer of the Bay Area D3.js User Group as well as the annual d3.unconf, and has spoken at OpenVis Conf, BackboneConf, and various meetups. Shirley has a B.S. in Business Administration and a minor in Computer Science from the University of California, Berkeley.
After graduating as an astronomer Nadieh Bremer became a data scientist finding insights in the vast amounts of data that are hidden within many companies. It took a few years, but she eventually figured out that she loved the visualization of the data and insights even more than the analysis itself.
Since then she's been focusing on and experimenting with the more creative side of data visualization. Sharing her final results along with tutorials on her blog, Visual Cinnamon. These days she's doing a year long collaboration with Shirley Wu called data sketch|es and is working part-time at Adyen, where she gets the freedom to explore new ways of applying data visualization, besides freelancing as a Data Visualization Designer in her remaining days and weekends.
She was named Rising Star of 2016 by the Kantar Information is Beautiful Awards and has been speaking about her passion of data visualization at international conferences.
D3 with Canvas
Kai will give a lightning introduction to basic Canvas methods, with just a couple d3 utilities to make things interesting (like color scales and d3.timer). He will then briefly cover techniques to solve the most common Canvas problem: selecting what's under or near the cursor, d3 utilities like quadtree, simulation.find and the hidden canvas method. Lastly, he will demonstrate these techniques and others through projects he developed over time.
Text Mining and Visualization, the Tidy Way
Unstructured, text-heavy data sets are increasingly important in many domains, but data scientists and analysts are often trained to handle tabular or rectangular data that is mostly numeric. Using tidy data principles and tidy tools can make text mining easier, more effective, and consistent with tools already in wide use by analysis practitioners. In this talk, Julia will demonstrate how we can manipulate, summarize, and visualize the characteristics of text using R packages from the tidy tool ecosystem; these tools extend naturally to many text analyses and allow analysts to integrate natural language processing into proven, effective workflows. We will explore how to implement and visualize approaches such as sentiment analysis of texts and measuring tf-idf to quantify what a document is about.
Julia Silge is a data scientist at Stack Overflow. Her work involves analyzing and modeling complex data sets, and communicating about technical topics with diverse audiences. She enjoys making beautiful charts, the statistical programming language R, black coffee, red wine, and the mountains of her adopted home state of Utah. She has a PhD in astrophysics and an abiding love for Jane Austen.
How spatial polygons shape our world
Borders often do not have much to do with the physical world. The edges of voting districts, cities, counties, states, and countries are decided by arbitrary human processes, always implicitly if not explicitly political.
Data are often provided pre-aggregated at a particular spatial level. For example, data on poverty is collected at the block-group level, while data on education is easiest to obtain at the school district level. This makes it difficult to combine data, and can lead to major issues when the data does not make sense at the level it was collected.
In this talk, Amelia will discuss issues related to spatial aggregation, such as gerrymandering, the electoral college, and the Modifiable Areal Unit Problem. While there is no one accepted solution to the problem, she will present a few methods that allow data analysts to move from one level of spatial aggregation to another.
Amelia McNamara teaches statistics and data science at Smith College. Her research is focused on making it easier for everyone to do and understand statistics. As such, she works at the intersection of statistics education, statistical computing, and data visualization. She is committed to open source tools and transparency in data science.
Unidirectional data flow (as popularized by react) is a powerful and efficient paradigm for building complex user interfaces. In this talk, Mikola will introduce regl, a high performance functional abstraction over WebGL. Because regl greatly reduces the amount of shared state compared to traditional graphics engines, it is much easier to write modular and testable graphics applications. He will also demonstrate the power of this new library by surveying some different patterns for building high performance visualizations on top of regl.
Mikola Lysenko is a founding member of BITS cooperative, a worker-owned technology company based out of the big island of Hawai'i. Previously at plot.ly, he helped develop the WebGL rendering systems for 3D and 2D plots. He has contributed to several open source projects, including stack.gl, scijs and regl and has written several hundred npm modules.
An Introduction to GDAL (the Geospatial Data Abstraction Library) for Those Afraid of the Command Line
We’re currently awash in geospatial information: from raster datasets from satellites, aircraft, and drones; to vector data archived and distributed by government agencies; to the data exhaust of social media and the Internet of things. Visualization is a powerful tool to make sense of all of this information, and GDAL (the Geospatial Data Abstraction Library) is one of the principal tools used to manipulate and transform geospatial data. This allows disparate datasets to be combined to show cause and effect and build narratives. Unfortunately, GDAL can be intimidating to the uninitiated. The documentation is technical, the syntax is inconsistent, and various tips and tricks are buried on message boards or Stack Overflow.
In this talk, Robert will approach GDAL from the perspective of someone who is slightly terrified of the command line: covering how to install GDAL and its dependencies, convert between file formats, reproject maps (along with the basics of map projections and cartography), merge images, and transform OpenStreetMap databases into ubiquitous shapefiles. He will also demonstrate some of GDAL’s lesser-known, but very powerful capabilities: perform mathematical operations using gdal_calc, pan-sharpen imagery, create shaded relief maps, build custom slippy maps, display data with exponential scaling, and manipulate wavelength bands in satellite imagery.
Robert Simmon is a data visualizer and designer working with Planet. He previously spent 20 years working at NASA, co-founding the Earth Observatory. He is an expert at creating clear and compelling satellite imagery. He focuses on producing visualizations that are elegant and easily understandable, while accurately presenting the underlying data. He helped create some of NASA’s most widely-seen imagery, including the Earth at Night and the 2002 Blue Marble. His imagery has appeared in newspapers, web sites, advertisements, the cover of the November 2015 issue of National Geographic, and was featured on the login screen of the original Apple iPhone.
John Alexis Guerra Gomez
Untangling the hairball
Many times a data analysis task can be represented as a collection of connections or relationships between entities, such as partnerships, business relationships, or simple co-occurrences. In information visualization, we can model and represent those relationships as networks, and we usually represent them using force directed node link diagrams. However, despite their promise, network visualizations with a few hundred nodes can quickly turn into a tangled hairball. In this talk, John will present a crash course on how to untangle that hairball and produce insights. He will summarize of the visualization alternatives for the node link diagram alongside code examples and pros and cons of each approach. He will also augment his examples with insights found on in scientific community. Lastly, he will show many of his own projects in this space to illustrate the practical lessons he learned.
John Alexis is a researcher, an entrepreneur and a dreamer.
He is a researcher at Los Andes University where he investigates novel information visualization techniques for photos, networks and trees. He is also a lecturer at UC Berkeley. Previously, he worked at Yahoo Labs and PARC. He studied Information Visualization while pursuing his PhD at the HCIL working with Ben Shneiderman and Catherine Plaisant.
As an entrepreneur, he co-founded BTactile a search engine of images for the blind; he also co-created a device to allow blind children to see colors and shapes with their hands.
He also likes to dream and build applications to generate insights using infovis such as: a report of the most followed accounts by the online communities of Openvis and IEEEVIS, a visualization of the results of the Colombian peace referendum (and of the 2016 US elections), a tool to monitor who likes your Facebook the most, or a Twitter monitor for the 2014 Colombian presidential election where he uncovered more than 500 fake accounts. He has also created open source libraries for in-browser network clustering and to distribute clusters on a network visualization using the group-in-a-box technique.
Data as a Creative Constraint
Design requires constraints. Art, on the other hand, thrives outside of constraints. Data visualization often straddles the gap between the two disciplines: open-ended generative systems are brought under control by applying data as constraints.
What do we gain by thinking of visualization as art and design together? What techniques can we borrow from each discipline, and how do they work together? The session will survey recent and past algorithmic artworks, examine systems and processes employed by generative artists, and derive techniques for applying them to the practice of data visualization.
An architecture background and a new media foreground come together to shape Eric Socolofsky's body of work. His experience with interaction design, coding, and spatial installations was wrought in NYU's Interactive Telecommunications Program (ITP), honed at gigs at New York-based Eyebeam and Gamelab, and channeled through teaching stints at NYU and Pratt and speaking engagements at Eyeo Festival, INST-INT, and FITC.
While in San Francisco, he designed and built exhibits at the Exploratorium, helped make Flickr awesome again, and is now making maps and visualizations at Stamen Design. You can find him wandering the World Wide Web as @ericsoco.
Connor C. Gramazio
Empowering effective visualization (color) design
This talk will use recent trends in visualization color research as an example of how to reshape our own perspectives of “effective design” to better align with the growing diaspora of visualization creators and consumers. In this talk, Connor will cover some background on color perception and novel research in this space -What are CIELAB and CIECAM02-UCS? How does color swatch size affect discriminability? How can we better support those who want to create their own categorical color palettes? If they want to incorporate a brand’s coloring? What about creating sequential palettes? Conor will cover academic research in this space, and guide us on how to transfer color science principles into our creative work.
Connor Gramazio is a computer science PhD Candidate and NSF Graduate Research Fellow at Brown University. His research focuses on expanding our understanding of effective design practices and developing new computational techniques to improve visualization design. Prior to Brown, he graduated from Tufts University with a BS in Computer Science and a minor in Religion.
Growing a more inclusive DataViz Community
We are constantly seeking ways to make the data visualization community broader and more inclusive, and our Diversity Scholarship program, which covers a full OpenVis Conf ticket as well as travel and hotel stay in Boston, is an important part of that effort. The scholarship is open to people who self-identify as part of any group that's under-represented in technology. We invite you to learn more and apply for the scholarship.
If you want to help us extend the reach of this program, you can get the word out to groups and people who'd be interested in applying and attending, or your company can sponsor additional scholarships.Learn More & Apply
Where the magic happens
We're excited to bring OpenVis Conf to new heights at the State Room. From this perch atop the Sixty State Street skyscraper, we'll have a bird's-eye view of modern data visualization practice – and of Boston! It's the perfect place for an anniversary celebration and we hope you'll join us there!
Curating the conference
We are incredibly grateful to our committee members for their continuing dedication to OpenVis and the Data Visualization community at large. These people work hard to make this conference program the best that it can be.
Sponsoring OpenVis Conf is a great way to connect with our expert community of data visualization practitioners. Help us make OVC be the best it can be by providing Diversity Scholarships or by supporting our speakers and attendee. Take a look at our sponsorship prospectus to see all the ways you can be part of creating a shared experience and foster long-lasting relationships with members of the data visualization community.Review Sponsorships Get In Touch
Code of Conduct
We believe that everyone deserves a thoroughly pleasant conference experience, regardless of who they are. We adhere to the Bocoup Code of Conduct and expect that all of our speakers, attendees, sponsors, and volunteers will do the same.Read more