The Health 2.0 and Open Gov movements have helped unlock large repositories of data - from user-generated data in hundreds of online communities to mobile devices to federal quality indicators to medical record data within provider organizations. But much remains to be done to connect these disconnected islands of data to generate information that's meaningful and actionable by end users. And what happens when you link informed patient communities with their health data? As Clay Shirky says, it gets weird. And interesting.
A number of communities have cropped up to promote access to medical data and the integration of user-reported and behavioral data within the clinical decision stream including healthdatarights.org, #healthapps, #health2dev, #73cents, #getupandmove and #WhyPM. With the opening up of health datasets, platform APIs and increasingly sophisticated analytic engines to make user-generated health data clinically relevant, we can finally unleash the wider developer community to build robust and integrated tools to improve health and healthcare.
This session brings together some of the leading voices in the Health 2.0 movement to discuss and demo technologies that help access, mine, display and distribute control of health information across a wide variety of interfaces and devices. We will also hear how government is opening healthcare datasets for access by the developer community and how patients are increasingly becoming "n of 1" platforms.
Big Data creates problems and opportunities that do not exist when dealing with smaller datasets. You will learn how to scale, utilize, and visualize Big Data as well as create and integrate Big Data related APIs. We will talk about how to scale your data, expose your data through APIs, integrate existing data from the data marketplace, and communicate your data through visualization.You will find out what techniques and strategies work best when working with Big Data. Many developers have learned how to scale their systems for high levels of concurrency. However, scaling for Big Data has its own unique challenges. Sometimes strategies that would make no sense for smaller systems work great when dealing with larger datasets. This Workshop is geared towards PHP developers, but all are welcome.
by Chris Busse
There are many services that will generate wordclouds and simple graphs from the conversations on social media platforms such as Twitter and Facebook. These services use Application Programmer Interfaces (APIs) to access the data on the platforms then perform various analysis on that data. These tools are often very limited in their functionality, or are very expensive to use for large-scale ongoing analysis and even then they often don't cover all the needs of a dynamic organization.
This presentation will demonstrate how to programmatically access the APIs of several social media platforms to pull out specific data, store it in a database, and perform custom analysis on it to meet the needs of various business cases.
We'll take a look at how different social media platforms are better suited for gleaning different kinds of data. This includes Twitter and Facebook as well as various blog and location-based platforms. Specific business cases will be shown around marketing, communications, competitive intelligence, crisis management, and return on investment analysis.
Attendees of this presentation will leave with a better understanding of how looking at the universe of online conversation as a whole can provide valuable insight into what consumers are thinking and interested in at any given moment.
11th–15th March 2011