metaLayer

New Website, Check it Out!

This weekend we relaunched metaLayer.com.  The first thing you’ll notice is that our social community for data enthusiasts, deLv, is no longer the the landing page.  You can now register for deLv at the url deLv.co. There you’ll be able to explore all the web’s social data freely and visually.

The second thing you’ll notice is that there’s much more to do across the site. We’ve fleshed out the descriptions of all our products and updated the wiki.

You’ll also find some great tools for developers and other technical people who want to delve deeper into our technology stack and research. 

Real-Time Awareness

Various individuals from @TechAtState’s February “Real-Time Awareness” conference speak about the new challenges of dealing with real-time data streams. This clip includes our own Jon Gosier (metaLayer), Jack Holt (Blue Ridge Information Systems), Dave Weinberger (author “Too Big to Know”), Patrick Scullin (Georgetown University), Andrew Turner (GeoIQ), Chris Damsen (NetVibes), Kim Rees (Periscopic) and more…

Watch the Video Here

What’s Next in Tech for Journalism?

Chris Burrage (Director of Biz Dev at metaLayer) presented along with a number of other emerging companies including: BiblioCrunch, Contently, NewsIT, Zeega and Engagio.

Colombia Journalism Review wrote a great summary of of the day:

This morning, The Paley Center for Media hosted a forum called “The Next Big Thing in Digital News Innovation,” with six presenters from “news and information startups.” Each speaker was given five minutes to explain their company and five minutes to answer questions.

The final presentation was from Christopher Burrage, the director of business development for MetaLayer, a platform for interpreting data, at this point mainly from Twitter, and analyzing it based on “sentiment analysis, influence detection, and optical character recognition.” Described as a “drag and drop experience,” Burrage says the tool is meant to allow journalists to be “their own data analysts.”

Can Data Visualization Augment Your Reality?

So at metaLayer we’re working very hard to bring you the best selection of algorithms, visualizations, and data manipulation techniques in a simple drag and drop interface. One feature that is occasionally asked about is offering data mashups that can control augmented reality platforms like Layar and Sekai.

For those of you who’ve been following us for a while, you’ll know that this would be a bit of a return home for us because we began by experimenting with AR technologies.

This would allow content publishers and developers to publish their datasets in ways that are presented on the canvas of the physical world, as opposed to the web. If you’d like to see such functionality in metaLayer or deLv, vote on our application for the Knight News Challenge!

The Next Big Thing at #PaleyNext

The Paley Center for Media and the John S. and James L. Knight Foundation present The Next Big Thing in Digital News Innovation, a series of forums in New York, Chicago, and Los Angeles showcasing news and information startups for an audience of high-level media executives and investors.

Chris Burrage, Director of Business Development at metaLayer, will talk about our community platform deLv, the Next Big Thing in visualization and data science.

Watch the live stream right now at - http://www.paleycenter.org/mc-paley-knight-news-innovation

Calculators for Data Science

The following was the keynote I delivered at STRATA 2012 entitled “Democratizing Data Platforms”. You can find the full set of accompanying slides here.

Data science should be more like art.  Not everyone understands art.  Not everyone appreciates art But whether you understand it or not you draw, you doodle. 


This is the Sistine Chapel in Vatican City. What’s interesting about this painting is that it was commissioned. It wasn’t the artist who approached the church with his idea for doing it, rather the church sought out the artist to fulfill a need.  

In the 15th century this was common practice - a working relationship with a wealthy patron or institution was the most an artist could hope to achieve. Artistry belonged to the elite.  

Science and technology has followed a similar trend over hundreds of years. Initially belonging only to the educated, which usually meant the wealthy, before later finding it’s way into the hands of the public. The sheer costs of education is what prevented studying maths and the sciences from spreading more widely. It wasn’t until simple tools like the abacus and the calculator were developed, followed by the spread of public education, that math became accessible to the general public.

Right now data science is a lot like art and math were in the 15th century. It’s a skill for those who’ve taken the time to study and specialize.  It’s for professionals.

But increasingly we’ve witnessed the repercussions of outsourcing our sole understanding of complex concepts and ideas to experts.

The sub-prime mortgage crisis in the U.S. was partly the result of homeowners not knowing, the details associated with loans. They didn’t share the expertise required to know any better. They didn’t, nor could they have, understand the greater system that they participated in.

The impact on society was obviously profound.  

On wall street algorithms outnumber, outpace, and outperform humans on a daily basis. Yet, in schools the knowledge that informs the construction of these types of systems belongs to a select few.  This is not a conspiracy.  The reality is, these types of careers are hard, and not everyone has the aptitude for them.

Therein lies the problem. In our lifetime, the world has shifted. Technology and the byproducts of technology have outpaced the average person’s understanding. If society is increasingly relying upon increasingly complex tools and systems, then this needs to change.

It’s no longer a luxury to be able to understand and contextualize data, especially the unstructured information that overwhelms us all.  It’s a necessity. 

The products we build as engineers need to cross this divide first.  Tools that enable the average person to perform with the efficiency of an expert.  Think of search engines.  When search was introduced to the mass market it took what was once the job of specialists (information retrieval) and it made it accessible for anyone to do. much like simple tools like calculators once did for math.

We need the equivalent of the calculator for data science.

This is because great things happen when people can make use of information at their own discretion.

For example, I had the pleasure of working with the founders of Ushahidi for the past few years. Ushahidi makes open source tools for disaster response (among other things), particularly for users in developing countries.  In only few years their platform become almost a standard tool deployed when faced with disaster.  From the devastating earthquakes in Japan and to the floods last year in Australia.

They make text messages easier to put on maps, which in turn offers a more efficient and cost effective way for emergency responders to serve the public. With a product that can be as easily deployed by the UN as it is by a small Congolese NGO. There should be more things like Ushahidi with simple interfaces that abstract the complicated processes and technologies that power them.  

So at metaLayer we feel it’s our responsibility to meet the untrained public half-way with products that echo this philosophy. We look big data solutions as a means to an end to help people solve their own problems.  Not simply collecting information and sharing it, but enabling our users to ask questions of the world’s unstructured data, visualize it, and review the insights discovered by others.

This is deLv, a community that we launched at Strata. Delv helps anyone draw insights from everyday information. deLv offers a dashboard that is essentially a canvas where anyone can experiment, ask questions of, and draw insight from the world’s information.  We want to make interacting with data more like art, by reducing complex technologies to gesture and simple motions.

Imagine if rather than relying upon Gallop polls, you could do your own digging to discover how people, or maybe just the people in your community feel about those political candidates. 

With deLv, users can actually do this do this.  Simply drag your data point to the canvas, input the term you care about or a way of filtering the content, add a data transformation like sentiment analysis, and add a visualization. 

At metaLayer we love data and we love what it can do for people.  But more importantly, what we aim to do is inspire, encourage, and enable a love of data by people who aren’t specialists.

If math was democratized through simple, accessible tools like the calculator, metaLayer aims to build the calculators of sorts for the world’s unstructured data.

Our Big Idea at GigaOM #DataConf

Team metaLayer is at GigaOM’s Structure:Data conference today presenting our big ideas for the Big Data space.  You can check out the live stream here. Our talk is at 5:25pm EST.

MetaLayer Wins the Startup Showcase at Strata!

We’re really excited to be here in San Jose at Strata 2012 and even more excited now that metaLayer’s won the Startup Showcase Audience Choice Award! As the winners, we’ll pitch in front of the Strata conference audience and a panel of esteemed judges during the keynote sessions on Day 2!