DIAP Rule of Thumb
Circumstantial observation of my email archive, at 272MBytes, having never deleted an email permanently and the file, ../mail, has been in use for 4 years. During this time my available xDSL line Bandwidth has increased, 2004 500MBits/sec to 1GBit/sec, 2008 1GBit/sec to 6GBits/Sec this is about 150% yearly increase whereas my mailbox has increased yearly by about 50%. It is this difference which DIAP attempts to use classing my email record as ‘mission critical’. Other record types will increase at different rates, as will bandwidth depending on location, but probably less than the average yearly bandwidth increase. This idea needs expanding but forms the foundation for the usefulness of DIAP, describing a DIAP rule of thumb. DIAP can also be viewed as a technique.
A pilot survey was run between June 08 and Aug 08 on Hampshire Lug ML named:- ‘[Hampshire] [OT] Identifying the importance and value of data’. This form the basis of a decision matrix tool to help DIAP ® users select data to use in DIAP ® system.Question 2)
“Following on from a survey I posted back in June, see below, designed to help make decisions about data vitality and importance to individuals and organisations, as well as find out a little bit more about the relationship between the importance of data types and their size, I have some results to publish. The survey was exclusive to Hants Lug and deliberately kept low key and has been a very useful exercise even though the number of participants has been relatively small – but very good for such a small readership, quality not quantity.
Thanks to those that took part and those that provided feedback and constructive criticism also thanks to HL ML readers for living with the thread. I will now design a new survey with some sort of incentive and float this to a much larger audience. The results I have are enough to incorporate a DIAP (R) decision matrix on the project website.
6 Participants:
Question 1)
Rate FIVE of these DATA TYPES if they were lost completely how best describes the effect to your users (and or yourself) organisation or home occupants.
Results:
*total damage – cost crippling – traumatic
2 [participants specified] Documents
1 Presentations
1 Photographs
1 Email boxes on a server
2 Code repository
1 Website code
*massive damage – high cost – devastating
1 Spreadsheets
1 .txt files
1 Email boxes on a server
*major damage – very costly – extremely upsetting
1 pdf documents
1 Photographs
*significant damage – significant cost – very upsetting
1 Spreadsheets
2 Accounting Software data
1 Photographs
1 server configuration files
1 music files
1 Virtual machine images
*damage – expensive – annoying
1 Documents
1 pdf documents
1 MS .pst file
1 Email boxes on a server
1 music files
1 ISO images
1 Virtual machine images
1 Code repository
Size the FIVE choices you made in the previous question
Results:
1 MB 100 MB 8 items
>100 MB 500 MB 1 item
>500 MB 1 GB 8 items
>1 GB 10 GB 8 items
>10 GB 50 GB 0 items
>50 GB 100 GB 2 items
>100 GB 1 item
So from just this small pilot survey I can deduce qualitatively with reasonable certainly that importance of data, subjective to the individual or organisation, does not depend heavily on the data type.
That importance of data in relation to file size is loosely inversely proportional. So the most important files are generally the smallest in size. This is very encouraging information for the DIAP (R) project.
Thanks again to readers and participants.”
Damian Brasher
