Zoomdata Interview - Next Generation Big Data Analytics And Visualization


Zoomdata Interview - Next Generation Big Data Analytics And Visualization. Picture of Dashboard.

We recently caught up with Justin Langseth - CEO of Zoomdata. Zoomdata is a next generation data visualization system that easily allows companies and people to understand data visually in real time with a special focus on big data analytics. As such, we were keen to learn more about how Zoomdata connects to Hadoop, Stream Process billions of records and visualizes them using D3.js...

Hi Justin, firstly thank you for the interview. Looking forward to hearing your thoughts on Zoomdata.

Q - Visualising historical and real-time Data feels like such a new thing to the internet. Can you give us a brief history of the field and how Zoomdata fits into the picture?
A - Visualization has been around for a while but typically was for static data and done in proprietary desktop interfaces. Zoomdata makes this much more accessible for data from modern big data and hadoop based sources, for for modern devices and interfaces.

Q - Does Zoomdata use D3.js and if so, how?
A - Yes, most of our out of the box visuals in Zoomdata are powered by d3.js, and users can add their own d3.js or other Javascript-based visuals (NVD3, Vega, etc.) to the system, with Zoomdata responsible for all the data plumbing for historical and real-time data, and for user interactivity and dashboarding.

Q - At Strata2014 Santa Clara you are presenting a session named "Minority Report Meets Big Data: Touch and Interactive Big Data is Here" Who are you hoping this prevention will appeal to? And why?
A - To people who are interested in designing new experiences for humans to interact with data. We will discuss the design of the data, backend storage and systems, models, analytics, and front-ends to get closer to the “minority report” interface vision.

Q - At Strata2014 Santa Clara you are presenting a session named "Napoleon’s March to d3.js--The Future of Big, Real-time Interactive Data Visualization" Who are you hoping this prevention will appeal to? And why?
A - To people who are interested in how data visualization and analytics can be deployed to normal business people. We will focus on the organizational aspects of empowering analysts.

Q - To you, what are the ingredients of a good data visualisation? And a bad one?
A - The best is one that conveys data in a way that is intuitive and obvious to a human user, and allows for understanding of data in ways that leverage the native processing power of the human brain, which is a massively parallel pattern recognition engine with a mostly visual input. A bad one is anything that is confusing, ugly, slow, or leads users to an incorrect conclusion.

Q - What are some examples of real-world user-centric design approach that create competitive advantage by providing users and customers with a real-time data experience?
A - The whole world is becoming more real-time. Competition is becoming more intense. Ads are served online using multiparty microauctions that last only milliseconds. To be competitive in the future, you will need to be adjusting all the little knobs and levers of your business nearly continuously.

Q - What does it mean that Zoomdata is one of the first data analysis technology vendors specifically designed for Cloudera Impala and what does it mean for your customers?
A - We leverage Impala using our patented microquery sharpening approach. It means users can start to see and interact with Impala-stored data in just a few seconds or less, even at massive data scale.

Q - Tell us about speed-of-thought visual analytics and what tools you are using to construct them.
A - The front end us all Javascript based, heavily leveraging D3.js. Our backend is a scalable stream processing system that we branched from the Storm engine to make it more scalable along the dimension that is important for a multi-user data analytics system.

Q - What do you think of the future of data visualization?
A - I think we’re just getting started. We are playing with completely novel approaches to human-data interaction, including new ways to “finger paint” with data, and even virtual reality data rooms. We will be exhibiting both of these at our booth at Strata.


Editor Note - I attended Justin's presentation at Strata2014 titled "Minority Report Meets Big Data: Touch and Interactive Big Data is Here". I am excited to see more of how Justin and the Zoomdata team continue to develop and grow the "finger painting" approach to data!


Justin - Thank you so much for your time! Really enjoyed learning more about Zoomdata and the future of real-time Data Visualization and new approaches to human-data interaction. Per the Editor's note, I am really excited to continue to see this technology develop. Justin can be found online on Twitter. Zoomdata can be found online at the Zoomdata website and on Twitter.


DataHero Interview - Data Analysis Tools And Design


DataHero Interview - Data Analysis Tools And Design: Picture of DataHero Dashboard

We recently caught up with Chris Neumann - CEO and Cofounder of DataHero. We were keen to learn more about how DataHero is working on Democratizing Data Visualization And Analysis...

Hi Chris, firstly thank you for the interview. Looking forward to hearing your thoughts on DataHero.

Q - Why did you start DataHero?
A - DataHero was founded with a singular goal: to empower anyone to be able to get answers from the data that matters to them. Data is fast becoming a central aspect of our jobs and our lives, and we believe that everyone should be able to work with data - not just people with backgrounds in statistics, computer science and the like.

Q - What does DataHero do/make that users want?
A - The foundation for DataHero is based on three pillars: UI, UX and data processing algorithms. Whereas traditional data analytics products start with the data and algorithms and layer the UI on top, we start with our users. Our UI and UX teams get feedback from hundreds of our users on each prototype and are constantly iterating to make sure that DataHero is the easiest-to-use data analysis and visualization product around. This user-centric approach drives our development process and the classification, data processing, and machine learning algorithms we build to support the needs of our users.

Q - How does DataHero empower people?
A - DataHero empowers users by letting them focus on the questions they want to ask of their data, rather than the process of data analysis. For example, when a user imports data into DataHero (either by connecting to one of many popular SaaS services we support or by just dragging a spreadsheet or other data file into their web browser), our data classification algorithms automatically process the data to identify patterns and suggest visualizations of interesting insights in the data. Users can either start with a suggested chart or create their own by simply dragging the attributes they want to visualize onto the chart canvas and DataHero does the rest! By combing an interface with the sensibilities of a consumer web application, advanced data processing algorithms and powerful recommendation engines, we've created a product that takes the complexity out of data visualizations and empowers users of any technical ability (or lack thereof) to be able to work with data on their own.

Q - What tools do you use both for back and front of the stacks as well as for the data visualizations?
A - On the backend, DataHero is built entirely in node.js (more on that here: http://strongloop.com/strongblog/in-the-loop-datahero-providing-instant-access-to-your-data-via-node-js/), with a variety of data stores used to process and analyze the data. DataHero's client side app uses the backbone.js framework and several different visualization libraries to create the charts. For example, we use HighCharts for most of the "standard" chart types and Google's Geochart library for maps. We're currently working on prototypes to leverage D3.js in some of our newer visualizations.

Q - At Strata2014 Santa Clara, DataHero has been selected to present at the Startup Showcase as one of the Finalist Companies - what does this mean to you?
A - We're thrilled and humbled to be chosen as one of the top data startups of the year by O'Reilly. All of the companies selected for this year's Startup Showcase are doing exciting and important things, so we're honored to be able to present alongside them.


Editor Note - DataHero won the judges choice for best startup this year at Strata2014! Many congratulations to Chris and the DataHero Team!


Q - What do you think of the future of data visualization??
A - Today, we sit at an important inflection point in the use of data in our world. Everyday people are increasingly expected to be able to work with data in their day-to-day jobs, yet not everyone studied statistics or computer science in school. Data visualization provides a window through which everyone can understand data, yet up until now only experts could create them. Tools like DataHero bring the ability to work with data and create data visualizations to a broader audience, which we feel is incredibly important as our world and our lives become more data driven.

Chris - Thank you so much for your time! Really enjoyed learning more about DataHero and Data Empowerment through Data Visualization. Chris can be found online on Twitter. DataHero can be found online at the DataHero website and on Twitter.


Strata Conference 2014 - Santa Clara


Strata Conference 2014 - Santa Clara

As a media partner for the Strata Conference 2014 - Santa Clara I was able to offer a free ticket to the conference to one of the D3.js email list subscribers.

The O'Reilly Strata Conference brings together the brightest minds in data science and big data: decision makers using data to drive business strategy, as well as practitioners who collect, analyze, and manipulate it. By attending you can tap into the collective intelligence of over 150 of the leading data experts, network with thousands of your peers, and hear about the latest (and emerging) data tools, technologies, and best practices.

The entry was free to any member of the email list and all they had to do was telling me a little bit about themselves as well as what talks they really wanted to see at the conference.

The person who won was a student from Finland who is currently interning in San Francisco. The four talks they are really excited seeing are Perry Samson's talk about Mining Student Notes, Shrinat Perera's talk about Tracking a Soccer Game with Big Data, Justin Langseth's talk about Napoleon's March to d3js and Hadley Wickham's Expressing Yourself in R.

A big congrats goes out to the student. Also - If you are going, let me know and I'll buy you a coffee/beer as I'd love to meet you in person!


Erin Shellman, Data Scientist at Nordstrom Innovation Lab Interview


Nordstrom innovation Lab


We recently caught up with Erin Shellman from Nordstrom Innovation Lab to hear more about her and the Lab. Specifically, we wanted to get a better picture of what it means to be a data scientist within a company as well as the ups and downs that come along with the journey of getting there. Lastly, we wanted to hear more about her upcoming presentation (with David Von Lehman) at the Strata NY Conference titled "How Nordstrom utilizes humans as learning machines to blend brick-and-mortar with online commerce".

Nordstrom Innovation Lab is a team of techies, designers, entrepreneurs, statisticians, researches, and artists, all trying to discover the future of retail. Nordstrom, which started in 1901 in Seattle, is an American Upscale fashion retailer with 247 stores located in 33 USA States as well as an online store. Nordstrom's philosophy, started by the founder and carried through four generations of family oversight, is "offer the customer the best possible service, selection, quality and value." To that end Nordstrom Labs is a internal technology lab focused on innovating on the technology, operations, products, business models and even management of Nordstrom. In addition to using D3.js, D3 / Data Viz stand out Jim Vallandingham recently joined the company, technologies such as node.js, Objective-C, AngularJS, R, Go, Hadoop, Mahout and others are being used within the labs.

The format below is based on question / answer.

Hi Erin, thank you for the interview. Let's start with your background.

Q - What is your 30 second bio?
A - I am a data scientist in the Nordstrom Data Lab and a specialist in statistical computing. I am interested in the development of scalable machine learning methods with applications in recommendation systems, market segmentation and customer engagement. I have a master of science degree in biostatistics and a PhD in Bioinformatics, both from the University of Michigan in Ann Arbor. Big data problems are my passion.

Q - When did you realize you wanted to work with data as a career?
A - I think I always sort of knew. I went into econ as an undergrad because I wanted to study human behavior and the only way of describing it formally was through math. I’ve always been kind of obsessed with communication and I think I’ve always been drawn to mathy things because of the clarity of communication. If I say that a behavior can be described as a process with exponential decay, that can be understood in any language. The language of math is universal!

Q - How did you get involved with / interested in machine learning?
A - I did my undergraduate work at Case Western Reserve University in Cleveland, Ohio where I studied economics and evolutionary biology and minored in math. While I was there I did an internship at the National Institutes of Health in the Division of Computational Biosciences and was first introduced to machine learning through my advisor, Jim Malley. He’s a huge open-source and machine learning advocate so that’s when I first started programming in R and using machine learning methods. I loved my work at the NIH so much that I went on to get a master of science degree in biostatistics from the University of Michigan, and then a PhD in bioinformatics also from the University of Michigan. I’m a scientist at heart.

Q - Who took a chance on you?
A - Lots of people have taken chances on me, and I’m grateful to all of them. Most recently the director of the Nordstrom Data Lab, Jason Gowans (@jasongowans) took a chance on me when I was fresh out of grad school, had no retail experience and would become the first (and for a little while the only) person on his team. It’s a big vote of confidence, and a big motivator to do great work.

Erin, very compelling background. Thank you for sharing. Next, let's talk about your work.

Q - Why work at Nordstrom Data Labs?
A - Well, we’re the coolest people I know and we work on some of the coolest problems in the business.

Q - In your own words, what is the goal of Nordstrom Lab?
A - The goal of the Nordstrom Data Lab is to deliver data-driven products to inform business decisions internally, and to enhance customer experience externally.

Q - How would you describe your work to someone who is not familiar with it?
A - I recommend things! I would roughly describe my work as constructing and delivering data-driven products to the web for the purpose of making the customer experience online as enjoyable as it is in the store. Nordstrom has a reputation for best in class customer service in our stores, and as more people shop at nordstrom.com we’re trying to extend that legacy to serve those shoppers as well. Whether that’s by serving up recommendations to make products easier to find, or creating engaging new ways to interact with the website, it’s ultimately about creating a great shopping experience.

Q - Who does your work appeal to and why?
A - Well, I think my work is appealing to anyone who shops online and thinks there’s room for improvement in that experience.

Q - What does a typical day at work look like?
I come in, sit down and type symbols into vim all day. I also talk with tons of bright, motivated people all over the company and work on a wide range of data-driven projects. I build recommenders, but I’m a statistician so I also do data analysis. For example, I analyzed the data from the Nordstrom Pinterest Experiment we ran a few weeks ago. The experiment involved tagging products in the physical Nordstrom Store with the Pinterest logo as a kind of social proof for potential buyers.

Q - What tools do you use at work?
A - vim, tmux, Python, R, PostgreSQL, Heroku, Hadoop, Mahout

Q - What are your favorite tools to work with?
A - Historically my favorite tool has been R. I’ve been an R fanatic since I started using it in 2005, and it’s still my go-to for a lot of things. As I’ve started working on bigger problems however, I’ve been butting into R’s computational limitations so I’m adding new languages and technologies to my tool belt.

Q - What other mediums/tools are you working in?
A - I’m really excited to start working more with Mahout and am planning on using it for my next recommender.

Q - Whose work / tools do you admire?
A - I can’t say enough about the work of Hadley Wickham (@hadleywickham) and Mike Bostock (@mbostock). I use ‘ggplot2,’ ‘plyr’ and ‘lubridate’ everyday. I’m still learning d3.js so I’ve mostly made a few ugly figures at this point, but we’re all in love with it and it’s power in data storytelling and engagement can’t be understated.

Q - What is your process at Nordstrom Lab?
A - Our process in the lab is to get as quickly to a working prototype as possible. That helps us incorporate outside feedback quickly. We throw quick front-ends on all our recommenders so that people internally can see and interact with them, and that helps us get our work on the web faster, and results in a better final product.

Q - How long does it take to create a project?
A - We’re full of ideas so thinking up projects to work on takes as much time as it takes to drink a pint, or just short of two. Executing projects tends to vary a bit. The first project I worked on after joining the lab was a relatively simple recommendation engine and we had a working prototype of that built in about a week or so. Currently I’m on a more complicated, fully personalized recommender engine and it’s taking several weeks of mostly concentrated time.

Q - Where do you get your ideas for things to study / analyze at work?
A - We generate ideas internally through collaborations with people all over the company, from personalization to user experience. We also generate ideas at our weekly ‘retros,’ weekly retrospectives held over a beer. Retros are a tradition of the Nordstrom Innovation Lab that we quickly adopted.

Q - Before we get deeper into who you are as a Data Scientist and what drives you, what else should we know about Nordstrom Data Labs?
A - Well, one thing you should know about the NDL (oh snap, I really like that look of that), is that we’re hiring. If you’re part math/stats nerd, part programmer, part data storyteller hit us up. Also, we’re all really cool people who work on really cool projects. You can reach out to us through twitter or our website at nordstrominnovationlab.com. As we mentioned above, Jim Vallandingham (@vlandham) recently joined our group - so it is a very exciting place to be right now.

Nordstrom Data Labs (NDL!) sounds like a great place to work. Readers: Definitely reach out to them. Erin, next, let's talk about you a little more.

Q - Who or what is your greatest inspiration?
A - I’m inspired everyday by the communities working to promote women and girls in STEM fields. In particular Black Girls Code, Lady Coders, Girl Develop It, and the Association for Women in Mathematics, where I mentor young women and girls interested in pursuing degrees and careers in mathematical fields. I understand first-hand the challenges of staying motivated in a program or career that is intellectually demanding when mentors who understand your unique perspective are difficult to find. I’ve been in classes where I was the only women, but that’s changing everyday because women working in the industry are educating girls and women about the massive benefits available to them in highly technical industries.

Q - What is your personal process?
A - I like doing things the old-timey way, so I write ideas down a lot...like with a pen. I like to diagrammatically write out how my product would look from start to finish and that helps me organize my product into discrete, completable units. Of course that map gets re- drawn a lot as the project evolves, so I go through a lot of paper.

Q - What do you consider to be the most important aspects of your work?
A - Attention to detail and curiosity tempered with the ability to formulate research questions.

Q - What do you see as weaknesses in your work?
A - I think the biggest weakness in my work, and probably in my line of work generally, is the amount of time spent really trying to understand the problems. As an industry, we’re always moving to test this against that, and measuring lift and hitting various metrics, but very little time is spent in research trying to understand the mechanisms that drive differences in lift or whatever metric. In a world where you’re always trying to release the latest and greatest, you don’t spend a lot of time reflecting on why the stuff is working (or not).

Q - What in your career are you most proud of so far?
A - Besides finishing my PhD, I’m most proud of the first recommender David, Paul and I built because it’s the first thing I’ve built for the web that so many people have used. It’s an amazing feeling to create something that people actually see and use.

Q - Do you have any regrets?
A - None. I think it’s an exciting time to be in the industry and there is a seemingly infinite supply of new technology to learn about and to develop. The best part about this field is that everything is changing all the time and there are tons of important problems yet to be solved, so there’s lots of potential to make a big contribution.

Q - How about - what mistakes have you made?
A - How much space do you have? I’m primarily a statistician, so all the “big data” stuff is pretty new to me. I’m learning a lot of stuff, and making tons of mistakes along the way.

Q - What conditions do you need in order to work to your full capacity?
A - I need to be around great people. I like to be always learning new things, and it’s most fun to learn from others.

Q - What distinguishes your work from that of your contemporaries?
A - Hmm, well I think perhaps I have a more developed aesthetic than many of my contemporaries. I spend a lot of time with ‘ggplot’ making axes and labeling perfect and making sure that anyone could get the entire story from each figure I make, even without a caption. I don’t always accomplish that, but it’s what I strive for. I write up all my documents in LaTeX and TikZ because it’s just too pretty and I’m of the opinion that your point will come across much more effectively it’s easy on the eyes.

Q - How would you describe your style as Data Visualizer/Scientist?
A - I prefer a classic look, with neutral colors and clean lines... Data-wise, I’m a statistical pragmatist and an open-source purist. In general, I care about delivering high-quality results and not about the various philosophical arguments between statisticians, and I think embracing open-source technology is the best way to move fast.

Q - How important is Data to you in your personal life?
A - We’re currently running a little experiment in the lab to see what we can learn about ourselves through new technology like Jawbone UP, so I’ve been collecting loads of data on myself.

Very thought-provoking. Really appreciate your honesty. Next, let's talk about Data Science and your thoughts on it.

Q - What work is currently inspiring you?
A - There’s tons of amazing content out there being generated in d3.js and others. Obviously, I love Mike Bostock’s blocks page.

Q - What pisses you off most in the data science world?
A - The never-ending flow of idiotic data articles written by popular news outlets.

Q - What is one problem you think the world of data science needs to fix?
A - Well, I don’t think data science can fix anything really. The primary power of data is illumination of things that are already happening, so by it’s very nature it is reactive...unless you’re talking about forecasting and most of that is rubbish. That said there are lots of areas that could use an injection of data.

Q - What do you look for in other peoples work?
A - I guess I harp on this a lot, but I’m always looking for the story. What’s the point if you can’t tell a compelling story or engage me to think about or interact with the data. I’m also always looking at presentation. I instantly dismiss work where axes aren’t labeled or legends don’t appear where they should. It’s about craftsmanship as much as anything and why would I believe that you did a careful, valid analysis if you can’t even be bothered to correctly label your results?

Q - How can someone do work like you?
A - There’s a ton of material on the web today about data science, machine learning, Hadoop, whatever data buzzword you want, but I think the most valuable asset to have in this field is deep expertise in mathematics and statistics. I might get in trouble saying this, but I think it’s easier to pick up the programming than it is to learn the math. It can take a long time to develop an intuition for mathematical problem solving and I think that people with those skills are relatively few compared with those who are solid programmers. I’d say if you’re in college and thinking about what to study, I’d focus hard on your stats and math curriculum because those skills are valuable in every industry and highly transferable across industries.

Q - What does it take to do great data science?
A - First it takes a curious mind. You have to care about answering questions and telling stories. Second you have to temper your curiosity with what I loosely call “mathematical thinking.” I don’t mean anything formal by that, really I should say “reasoned thinking.” The ability to prioritize your research questions and see your way to a solution through the constituent parts is the most valuable skill. I’m constantly asking myself “what question am I answering by doing this?” and that mindset is critical when you have essentially infinite questions your data could attempt to answer.

Q - Do you have any words of wisdom for data science students or practitioners starting out?
A - Read a lot. Go to meet-ups. Go to seminars and talks when you can. Work with public data, there’s more than ever so go build something!

Q - What blogs do you think are hidden gems??
A - http://flowingdata.com/
http://www.datawrangling.com/
http://rfunction.com/
http://learnr.wordpress.com/
http://bost.ocks.org/mike/

Very insightful. Thank you. Last but not least, let's discuss your upcoming presentation at Strata Conf NY.

Q - What is the title of your talk?
A - "How Nordstrom utilizes humans as learning machines to blend brick-and-mortar with online commerce"

Q - Who is the talked aimed at?
A - This talk is for people with large and varied data who are interested in novel applications of data analytics, machine learning, and visualization to influence stakeholders and put the power of data to work for their businesses. We’ll walk through three case studies where we have delivered insights and/or products that blend data and experiences from physical and online commerce: A recommender system powered by the collective fashion expertise of our personal stylists, Social media sentiment and activity analyzer and Clothing color trend visualizer.

Q - What technologies will be covered?
A - Some of the technologies that will be discussed include: R, Python, Ruby, D3, Node.js and Hadoop.

Q - Why are you and your colleague David Von Lehman excited to give this talk?
A - Yeah! I’m super pumped for this! I think Nordstrom has a really interesting story to tell about how to transform a traditional retail model into a data-driven, e-commerce-loving retail model. We’re going to share a few case studies illustrating how we use behavior from our stores to construct the customer experience on the web, and on the flip side, how we’re using data from the web to improve the customer experience in our stores.

Q - Where can we find out more?
A - The Strata Conference NY Website => Nordstrom Innovation Labs Strata Talk.

Thanks - excited for your talk!

.............

Erin – Thank you so much for your time! Really enjoyed speaking with you, learning more about Nordstrom Innovation Labs, understanding more about how you view Data Science as well as your upcoming presentation at the Strata Conference NY.

Nordstrom Innovation Labs can be found online at http://nordstrominnovationlab.com/ and the Erin Shellman can be found online at @erinshellman.


OpenVis Conf and Bocoup Interview


OpenVis Conf


BOCOUP is an Open Web technology company by and for programmers. Self-described on Twitter as an Open Web technology standup comedy troupe, Bocoup not only contributes to open source, does consulting, and runs workshops and trainings, they also run four different developer conferences. These conferences include Roost for Front-end Devs, OpenVis Conf for Data Visualizers, Backbone Conf for Web Devs (Backbone, Ember, Knockout and other frameworks covered) and NewGame Conf for Game Devs.

We recently caught up with Irene Ros and Jory Burson from Bocoup to hear more about OpenVis Conf and Bocoup. The format below is based on question / answer.

Q: OpenVis Conf - What is it?
A: OpenVis Conf is the first-ever conference for developers, designers, engineers, data scientists, and managers working to push data visualization forward on the Open Web.

Q: OpenVis Conf - When is it?
A: May 16 & 17, 2013

Q: OpenVis Conf - Where is it?
A: At the Museum of Science in Boston. We’re extremely grateful to the Museum of Science for hosting us and can’t wait to share the sorts of activities you can only participate in thanks to the wonderful venue.

Q: OpenVis Conf - Speakers?
A:
Amanda Cox, New York Times
Juan Velasco, National Geographic
Tom MacWright, MapBox
Kim Rees, Periscopic
Santiago Ortiz
Shawn Allen, Stamen
Jesse Kriss, NASA
Lynn Cherny
Jim Vallandingham, Stowers Institute
Doug Schepers, W3C
Abe Stanway, Etsy
Miguel Rios, Twitter
Alex Graul, Crowdstrike
Dominikus Baur
Kai Chang
Gabriel Florit, Boston Globe

Q: OpenVis Conf - What are the goals?
A: OpenVis Conf aims to share high-quality resources and best practices in the emerging field of Open Web data visualization with practitioners. OpenVis Conf brings together people who have demonstrated excellence in their work and are excited to share their discoveries, process, and contributions to the Open Web and data visualization.

Q: OpenVis Conf - Who should attend?
A: The conference is targeted at all practitioners of data visualization - from data researchers to designers to developers. The focus is very much on acquiring new skills in a variety of data visualization topics, including architecture, mapping, d3.js and multi-dimensional data to name a few.

Q: OpenVis Conf - Why put on a conference for JS Data Vis practitioners?
A: The conference isn’t just for JS practitioners - in fact, there will be a number of folks at OpenVis for whom JS is new. While building data visualizations for the web requires JS, there are many other open tools along the way that practitioners use - such as R and Nodebox - and we’re excited to share the diversity along that toolchain. That said, we hope that OpenVis Conf inspires attendees to fully explore JavaScript, and discover how they can push the boundaries of data visualization on the web with it.

Q: OpenVis Conf - Why now?
A: In practice, most data visualizations end up on the web. It’s also becoming increasingly important to target a variety of devices, from mobile to Google Glass! There a number of competing technologies and methods for creating data visualizations - from proprietary and desktop softwares to Open Web methods such as svg, canvas, webgl, and so on (a topic which Miguel Rios from Twitter will speak about.) Because this space is evolving fast, we’re excited to gather people who can offer a set of best practices and inspiration and help shape the future of the Open Web data visualization.

Q: OpenVis Conf - Why are you (Bocoup, Irene, Jory) the right people to put this on?
A: Bocoup is known for its dedication to growing, stabilizing, and standardizing the Open Web across a variety of industries. The field of data visualization is greatly impacted by Open Web technologies as a relative newcomer to the web platform. Bocoup is in a unique position to support data visualization tools and practitioners on the web, given its demonstrated commitment to moving the field forward. Irene Ros and Jory Burson have made an ideal team for organizing OpenVis Conf - Irene is a globally recognized expert in the field and leads Bocoup’s research and development efforts in Open Web data visualization. Jory, managing the growing and highly successful educational programs at Bocoup, rounds out this effort, providing community development and outreach for the Open Web.

Q: OpenVis Conf - What excites you about the speakers?
A: Um, everything?! In seriousness, there are a lot of different backgrounds and experiences represented in the OpenVis Conf speaker line-up. We have 15+ year veterans in the field as well as rising stars who are all helping to shape the conversation about open web data visualization. While this level of variety ensures that there are plenty of different perspectives represented, all the speakers have demonstrated deep commitment to creating and standardizing open web data visualization tools. We are also incredibly excited to host OpenVis Conf at the Museum of Science in Boston. Conference venues normally serve as no more than a container for its attendees, but in this case we have an entire museum full of inspiration to the very field we’re in! Not to mention all the exciting activities that our attendees will get to partake in...

Q: OpenVis Conf - Why should people care?
A: Because the speakers and attendees at OpenVis Conf will play an immediate and integral role in shaping the conversation about open web data visualization over the coming years. These topics will continue to grow in relevance and importance to data vis practitioners. Anyone who cares about the future of the field should pay close attention to the themes and discussions that will arise from OpenVis Conf and join us in shaping the future of data visualization on the web.

Q: Tell us about you - What does Bocoup do?
A: Bocoup is an Open Web technology and software development company working to move the web forward through consulting, education, and community development.

Q: How are you, Irene and Jory, involved with Bocoup?
A: Irene Ros leads Bocoup’s growing data visualization initiative and is a Senior Software Engineer at Bocoup. Irene has been working in the data visualization field for the last 5 years, on projects like Many Eyes, an early comer to data visualization on the web, that pushed the boundaries of what was possible. As Director of Education, Jory Burson directs Bocoup’s Open Web community and training initiatives and works with Irene to support the data vis community through open source and sponsorship.

Q: What are your favorite (for each of you) client/student success story?
A: For Jory - it’s been watching people grow and flourish in the community. The ‘student success story’ that sticks out most for has to be Adam Hyland. Adam was new to Boston when he came to Roost, a two-day front-end development training conference we created, and from there I introduced him to Irene and the Data Vis community here. Adam has since become a strong voice in the community on data science and analysis, and has gone on to work with Irene on important projects such as OpenGenderTracker while working as an apprentice at Bocoup
For Irene - One of my favorite projects we were lucky to help with was Reconstitution2012 by the amazing folks at Sosolimited. Reconstitution2012 was an immensely successful, large-scale, real-time Presidential debate visualization Sosolimited took on building after their live performance of Reconsitition2008. With the 2012 version, they wanted to build a system on the web. A few of us at Bocoup jumped in to help with everything from the implementation of their incredible design, to code organization, to optimizing performance. It was incredibly rewarding to see it live and watch the debates with it on! It’s an incredible piece of work and a confirmation that building data visualization on the web is much more complicated than “how do I make this look good.”

Q: What excites you about the open web?
A: The web has limitless potential - new ideas, tools, and technologies are born in to it everyday. The communities that sprout around Open Web technologies have been pushing the limits of the web so much faster than closed communities are able to, and we’ve seen that especially in data visualization. A great example of that is d3.js, which has a thriving community that is responsible for everything from charting libraries to new visualization methods.

The Open Web stands for democratizing and standardizing technology while at the same time keeping low the costs and barriers to entry. Developing on the Open Web results in so much innovation, and that’s a very exciting place to be.

Q: What excites you about JavaScript?
A: We’re excited about creating for the web, and JavaScript is the language of the web. The JavaScript communities we participate in, including ones like d3.js, are incredibly vibrant and have been producing a lot of tools and practices that really push the field forward.

Q: What excites you about data visualizations?
A: Wow, what doesn’t!? There’s so much variety and creativity that goes into not only building data visualizations, but also making the right technology and visual paradigm choices. We’re really excited to watch data visualization grow on the Open Web and be a part of that movement.

Q: Who do you like that is doing great work?
A: Well, our speakers of course! It’s also hard to ignore amazing work like Jason Davies’ mapping contributions to d3.js.

Q: What work is currently inspiring you?
A: We’re inspired by how far mapping has evolved on the web. It wasn’t long ago that Google Maps was the defacto standard, and now we have incredibly innovative and beautiful maps (such as the water color maps from Stamen) and many more libraries to chose from. We are also really grateful for all the support the Open Web is getting from organizations like the Knight Foundation, which has been graciously sponsoring the development of tools and practices that directly push our field forward.

Q: What blogs do you think are hidden gems?
A: Well, inspiration is everywhere! As it turns out, just about everything we build on the web has some elements of data visualization to it - even your facebook feed is visualizing data if you think about it. There are too many sources to list that inspire us, but we are big fans of CreativeJS and of course the DashingD3 newsletter!

Q: What's been the most surprising thing for you that's happened in the last year related to the Open Web?
A: For us, it’s been the explosion of learning tools, websites, and localized resources focused on the Open Web. The past year has seen a number of additions to the space, all of which are inspiring people from all walks of life to learn more about programming, engineering and the Open Web. We’re excited for the language of the web to become more prevalent in mainstream conversation, and Bocoup’s role in making that happen, over the coming years!

Q: What else should we know about you, OpenVis Conf, Bocoup and/or your passions and interests?
A: Hopefully it’s obvious by now that we’re passionate about Open Web development and developers - So much so that the Loft at Bocoup is always open to the community for meetups, hackdays, or just technical conversation. If you’re ever in Boston, send us an email or tweet and drop in to see us - we have free JS & Bob the Rooster stickers with every visit!

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Irene & Jory – Thank you so much for your time! Bocoup can be found online at http://www.bocoup.com and the OpenVis Conf can be found online at http://openvisconf.com.


From Small Beginnings


Hello Friends!


We are starting a blog to cover the past, present & future of D3.js and Data Visualization.


As our goal is to help you make amazing data visualizations with D3.js, we will be doing interviews of companies and programmers, how-to articles, answering reader questions and much more.


Thanks for joining us!


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