4. Hurdles to Earth Information Access Application Data 1 User Stovepipe Value = 1 1 Data x 1 Program = 1 Enclosed Value-Creating Process - ‘Stovepipe’ “ The user cannot find the data; If she can find it, cannot access it; If she can access it, ; she doesn't know how good they are; if she finds them good, she can not merge them with other data” The Users View of IT, NAS 1989
13. #ESIPFed Hashtag Tweeting at semi-annual meetings allows attendees to share insights and others to learn about goings-on. Also providing web meeting capabilities for virtual participation.
17. Social Media as an Air Quality Sensor Air Twitter Aggregator Subscribe to RSS Feeds Air Twitter Filter ESIPAQWG Query sites for Smoke, Air Quality, Dust
18. Air Twitter – Event Identification August 2009, Los Angeles Fires Normal Weekly Trend
ESIP provides the Earth science informatics intellectual commons to drive innovation ESIP is the trusted community authority that supports the integration of science and data into mainstream use
ESIP provides the Earth science informatics intellectual commons to drive innovation ESIP is the trusted community authority that supports the integration of science and data into mainstream use Every group that shares interest on a website is called a community today, but communities of practice are a specific kind of community. They are focused on a domain of knowledge and over time accumulate expertise in this domain. They develop their shared practice by interacting around problems, solutions, and insights, and building a common store of knowledge.
The ability to easily expose content through the web using social media sites like youtube, flickr, and delicious has given the Earth a “skin” of photos, videos and citizen reporting Air Quality events like fires and dust storms are visible and impact daily life, thus the pictures, videos, blogs and tweets are shared through web within minutes of the event occuring.
Social Media listening takes advantage of all of the exposed content being in the collective ‘resource pool’ To listen for Air Quality-related content the first step is searching the social media sites for Air Quality and related terms. Delicious, Flickr, Google Blog Search, Google News Search, Twitter The different sites expose the results of these searches as RSS or Atom feeds. Those feeds are aggregated into a single RSS stream Then filters are applied to weed out unrelated content such as quality of Nike Air The result is one stream of content from multiple sources about air quality. One key difference between Air Twitter and other Social media listening tools is that we Re-Tweet all of the AQ content through a twitter account for ESIP AQ WG, so others interested in listening can also follow us.
To identify AQ events from background chatter, we display the # of tweets output daily and hourly from the consolidated AQ feed in a time series view. As we see an increase in tweets we click on the hour or day and see if there is a trending topic We see here that in August of 2009, the tweets responsbilbe for the increase were predominantly about the S. Cal Fire
we use the ESIP wiki to create an Eventspace – i.e. a collaborative workspace to fully describe the AQ Event with social media and air quality data The eventspace was created Aug. 30 for the California Fires. The Eventspace included pictures from twitter and flickr, video from youtube, and rss feeds from google blog search and google news The eventspace also included data from NRL NAAPS Smoke Model, Modis AQUA and Terra True Color satellites and fire pixels and the surface PM2.5 concentration from Airnow. The data layers were shared as KML and WMS and short screencasts were also made for those users that just wanted to preview the data. The eventspace link is then tweeted through the ESIP AQ WG account to alert our followers to the event. The eventspace is also shared on flickr to related photo groups and ireport if there is related content. User Requirements are Earth Observations or derived products needed
The LA Fires were identified by monitoring the Air Twitter time chart An Eventspace was created within the first day of significant burning and updated throughout the entire period The traffic to the ESIP wiki increased 5x The increase in traffic was entirely to the Eventspace page The top driver to the site was through twitter And the increased traffic was mostly from S. California
The LA Fires were identified by monitoring the Air Twitter time chart An Eventspace was created within the first day of significant burning and updated throughout the entire period The traffic to the ESIP wiki increased 5x The increase in traffic was entirely to the Eventspace page The top driver to the site was through twitter And the increased traffic was mostly from S. California
The LA Fires were identified by monitoring the Air Twitter time chart An Eventspace was created within the first day of significant burning and updated throughout the entire period The traffic to the ESIP wiki increased 5x The increase in traffic was entirely to the Eventspace page The top driver to the site was through twitter And the increased traffic was mostly from S. California