I did a quick search of the ground level feeds and information for the attacks. I’ll add more as I find them.

The map below of the attacks is linked on a number of posts and is from http://tr.im/1jj1

View Larger Map

Twitter Feeds:

• http://twitter.com/mumbaiattack
• http://twitter.com/Gauravonomics
• http://twitter.com/mumbai

Blogs:

• http://indiauncut.com/iublog/article/a-night-out-in-mumbai/

Mumbai Help Blog: http://mumbaihelp.blogspot.com/2008/11/can-we-help.html

Photos

• http://www.flickr.com/photos/vinu/show/with/3061372661/

News:

• http://www.mahalo.com/Mumbai_Terrorist_Attacks

Lela

NiJeL will be starting a refugee mapping project in Seattle and I have been assigned to begin researching for information.  I will be looking for data sets that include low-income housing, food banks, hospitals, esl classes, and schools to name a few things I am searching for.  There are many other data sets to find for this project but we will start with those.  I will be saving the links of the data on google notebook so the team will all have access.  I am excited to be apart of this project because I am from Seattle.  Hopefully there will be data sets already available. If not, I may have to manually find the information to then convert and creating it into a file. I will be posting updates regularly on the status of this project. Be sure to check back for updates!

-Richard

I want to wish everyone a Happy GIS Day! November 19th is the National GIS day. 2008 is the tenth anniversary of GIS day.  The convention this year is held by Abu Dhabi or ADSIC (Abu Dhabi Systems and Information Committee).  It will be held at the Abu Dhabi National Exhibition Center and will showcase projects currently being carried out by more than 17 organizations that are leading the way in GIS-development in Abu Dhabi.  For more information you can visit www.gisday.com

-Richard

Since my last experience with batchgeocoder I have made it my goal to find the quickest way possible to geocode large amounts of data.  Although the batchgeocode.com website recommends you do no more than 500 data sets at a time, I still found that it is relatively slow to do 500.  After careful observations I have found that the larger amounts of data sets you put in the more inaccurate the data is.  There is also more chances of missed data sets that don’t get geocoded.  While observing the geocoder at work, I have discovered that the first 100 data sets get geocoded fairly fast while anything afterwards moves like a slug.  For my work this week I had to geocode more data sets for afterschool programs in Arizona.  There was 2055 data sets this time.  From the troubles of the last assignment I figured I had to do something different.  So with my observations I decided that I would geocode the data 100 at a time.  It turns out that this method was most efficient because the data was geocoded quickly and the percent error rate of uncoded data was slim to none.

-Richard

The new QGIS program seems to be some bugs that they are not aware of.  I’ve been using QGIS to convert csv files into shapefiles. The problem at hand is that after I convert the csv file into a shapefile the data for the coordinates truncates the original six decimal point data to three.  I have tried adjusting the option settings of decimal places in QGIS but it does not appear to change anything.  The only solution I have found to this problem was to use an older version of QGIS.

Richard

So I have been recently working on a project of Daycare centers throughout Arizona. The goal of the project was to transform raw text data into a Shapefile.  Problems I ran into while working on this project were that there were an extremely large amounts of datasets that I had to geocode.  It took my laptop more than a day and a half to geocode.  I finally decided to geocode it on a school computer since my laptop was taking so long.  Another problem I ran into was that the raw text data did not have proper headings for each catergory. So after separating the data with comma delimited text I did not realize that there were some data sets with extra information that had extra columns in the data. This placed some data in the wrong categories so after geocoding the data some of them were geocoded with the wrong coordinates.  I had to manually go in and fix the data. This was very repetitive and intense labor of staring at the computer screen for hours.

Richard