Big Data Visualisation

  1. Set Up AWS EC2 Instance
    1. Go to https://aharth.signin.aws.amazon.com/console
    2. Create m4.xlarge instance in "US East (N. Virginia)", with Amazon Linux Image
    3. Add storage snap-882a8ae3 (DBpedia 3.5.1)
    4. Create key and download *.pem file, needed for ssh/putty
  2. Log In and Mount Volume
    1. Set correct permissions for pem file in .ssh directory (chmod 400)
    2. Log in to machine with the *.pem file (with ssh/putty), username ec2-user, e.g. $ ssh 54.84.56.174 -i ~/.ssh/amazon-aws.pem -l ec2-user (config pem files for putty)
    3. $ sudo mount /dev/sdb /mnt
  3. Run SPARQL Query
    1. $ wget -i http://harth.org/andreas/2016/bigdata/uris.txt
    2. $ tar -xzvf linked-data-fu-standalone-0.9.9-bin.tar.gz
    3. $ linked-data-fu-0.9.9/bin/ldfu.sh -i /mnt/en/geo_coordinates_en.nt.bz2 -q geo.rq geo.tsv
  4. Create Visualisation
    1. $ cat geo.tsv | sh tsv2json.sh > geo.json
    2. $ cat map-head.html geo.json map-tail.html > map.html
    3. Download map.html to your local machine; do on your computer: $ scp -i ~/.ssh/amazon-aws.pem ec2-user@54.84.56.174:map.html .
    4. View in SVG-capable browser