Title is evocative and short, but not too cute. If in doubt, keep it brief and descriptive.
TITLE Street Fighting Data Science
The description succinctly sets out the problem the talk addresses, and what attendees will learn.
DESCRIPTION New analysts or engineers are often lost when textbook approaches fail on real world data. Drawing inspiration from problem solving techniques in mathematics and physics, we will walk through examples that illustrate how come up with creative solutions and solve real world problems with data.
The abstract provides additional concrete details on what will be covered
ABSTRACT Practical problem solving with data involves more than just visualization or applying the latest machine learning techniques. Intuition, domain knowledge, and reasonable approximations can mean the difference between a successful model and a catastrophic failure. We'll dive into some best practices I've extracted from solving real world problems like computing trending topics, finding related searches, cleaning election data, and ranking experts on social networks.
New analysts or engineers are often lost when textbook approaches fail on real world data. Drawing inspiration from problem solving techniques in mathematics and physics, we will walk through examples that illustrate how come up with creative solutions and solve problems with big data.
TIP: Outline approach/bullet points is preferable to a long ramble
•Sampling & Approximation
•Finding Edge Cases
•Joining to External Data & Crowdsourcing
•Turning Errors into Improvements
The title embodies why anyone should care about a new programming language
TITLE Simple, Flexible Distributed Computing in Julia
The description elaborates why the audience should care.
TIP: Descriptions are also a good place to describe what attendees will learn.
DESCRIPTION Julia is a high-level, high-performance dynamic language for efficient, large-scale scientific and technical computing, which provides simple, flexible primitives for distributed computing, out of the box. These primitives allow various approaches to distributed computation to be implemented succinctly and easily, with high performance, entirely in Julia.
The abstract contains more specific details and demonstrates deep knowledge of the topic.
ABSTRACT Julia is a high-level, high-performance dynamic language for efficient, large-scale scientific and technical computing. It has been gaining traction as a an alternative to R, Matlab, and NumPy, especially in performance-demanding areas, such as "big statistics", bioinformatics, imaging, and linear algebra. Julia provides simple, flexible primitives for distributed computing, out of the box. Scalable distributed computation systems have typically either provided specialized parallel kernels to be composed by a control program—like ScaLAPACK for linear algebra—or provided specific but generalizable distributed frameworks like MapReduce or Pregel.
The computational kernel approach provides extreme performance, but sacrifices generality and assumes a fixed set of highly reliable computational resources. The framework approach gives up raw performance in exchange for fault tolerance, easier scaling, and greater generality. Julia provides a global distributed address space, a flexible futures mechanism, automatic serialization of user data and code, elastic parallelism, and simple, integrated fault handling. These primitives allow various approaches to distributed computation to be implemented succinctly and easily, with high performance, entirely in Julia.
Case Study Presentation
The title references a brand people have heard of and states clearly an attractive achievement with the promise of telling attendees how it was done
TITLE How Draw Something Absorbed 50 Million New Users, in 50 Days, With Zero App Downtime
The description is clear on what attendees will hear: a fun and useful case study with specific and relevant lessons for others.
DESCRIPTION OMGPOP's Draw Something broke all records when it went viral, skyrocketing to more than 50 million downloads and billions of drawings within a few weeks of launch—with no downtime. This session highlights the application architecture and data management technology that enabled this growth, and provides a real-time data management model for developers of any interactive web application.
The abstract makes it clear that the speaker intends to convey transferable knowledge—always a concern with case studies, which are only entertainment if you can't get anything out of it for your own use.
ABSTRACT Social and online games are a multi-billion market and one of the fastest growing sectors of the global economy. With the acceleration of social media, games can go from zero to millions of users overnight, the latest example being OMGPOP's Draw Something, a Pictionary-like game that broke all records when it went viral and skyrocketed to more than 50 million downloads and billions of drawings within a few weeks of launch.
If you are planning to build and launch a web application, growth is what you should be concerned with and prepared for. So how exactly can you architect an application, without breaking the bank, while sustaining a snappy and compelling application experience across the scaling spectrum?
In this presentation, Frank Weigel will focus specifically on the data management challenges web application developers face, and provide criteria for selecting a data management model that will provide the scalability and performance needed to support massive growth. The presentation will also highlight the architecture of OMGPOP's Draw Something, an example of a game that was prepared for growth.
Title is straightforward.
TITLE Designing Data Visualizations Workshop
Scope is clear and with a concise description of what will be taught.
DESCRIPTION This workshop is a jumpstart lesson on how to get from a blank page and a pile of data to a useful data visualization. We'll focus on the design process, not specific tools. Bring your sample data and paper or a laptop; leave with new visualization ideas.
What attendees should bring and what they should expect to leave with is clearly emphasized.
TIP: if the topic is deeply technical, a brief outline should be included.
ABSTRACTAttendees: All attendees should bring paper an pen for quick sketching. Attendees should bring their own data to work with. Alternately, they can download interesting data sets from sites such as infochimps.com, buzzdata.com, and data.gov. People with access to a windows machine might want to install Tableau Public.
We will discuss how to figure out what story to tell, select the right data, and pick appropriate layout and encodings. The goal is to learn how to create a visualization that conveys appropriate knowledge to a specific audience (which may include the designer).
We'll briefly discuss tools, including pencil and paper. No prior technology or graphic design experience is necessary. An awareness of some basic user-centered design concepts will be helpful.
Understanding of your specific data or data types will help immensely. Please do bring data sets to play with.
Many thanks to Jeff Bezanson, Wes Bos, Noah Iliinsky, Rachel Myers, Emily Nakashima, Stefan Karpinski, Peter Skomoroch, and Frank Weigel for allowing us to use their speaking proposal submissions.