488639 Check correctness and up to date of a few hundred subdomains

We need to check the correctness and up to date of a few hundred subdomains. There is a file, containing the list of subdomains and we need you to go through the list and confirm that they are up and running. If they are not, then we need you to gather some data (moved or dead, date, reason) Input: file [login to view URL] Instructions: Columns in the file ==subdomain: subdomains we have to gather data for Complete the fields below for every subdomain (there are around 800): Most of the subdomains will be fine, though, so it will be just copy+paste them on a browser and write OK down the corresponding field. ==status: Ok or Moved or Dead Ok: if the subdomain is up and running Moved: if the subdomain redirects to another one Dead: if the subdomain doesn't exist any more (ie. parked, domain searcher, not working, registered but not a website, ...). Just to clarify: [login to view URL] would fall in to the DEAD category. [login to view URL] MOVED to [login to view URL] because trovit is the brand [login to view URL] is OK [login to view URL] is OK [login to view URL] MOVED to [login to view URL] because it is their new site [login to view URL] is DEAD -If the subdomain is Ok (active and the website is working), then write OK down the status field and move on to the next subdomain. Otherwise: ==if moved: old subdomain column (the same. just copy+paste the value in the subdomain column where applies) ==if moved: new subdomain column(new subdomain you have been redirected to) ==if moved or dead: date moved column (current date) (date when you have checked) ==if moved or dead: reason column examples: if Dead the reason is 'not working any more' (for all Dead subdomains). if Moved the reason might be moved to a subfolders structure (eg. from [login to view URL] to [login to view URL] or moved to subdomain structure (eg. from [login to view URL] to [login to view URL] or moved to a domain which matches the brand or whatever reason you may find. Please, ignore the columns: category,type,content,indexation_group,frequency,below1000 but do not remove them. We believe this can be done in 4h, so will be paying $28 (USD) when the work is delivered. Output: file [login to view URL] with all fields completed. We will double-check the quality of the delivery before paying. Please, if something is not clear, ask before going ahead. Deadline: Wednesday 6th of April 2011 at 16:00 GMT