| Title |
Determining general 'document' properties |
| Detailed description | Large scale migration tasks require automated quality assurance to ensure migration was successful, e.g. PDF to PDF/A, or DOC to PDF/A migration. Quality Assurance could be performed by comparing relevant properties from the before and after documents, to ensure these are unchanged. Appropriate properties need to be identified for such comparisons, probably on a "per format" basis. Such properties should be quantifiable, although obvious candidates may not always be suitable, e.g. word counts may differ due to migration tools adding headers/footers (indicating file is a migration, copyright statement, etc.) |
| Scalability Challenge |
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| Issue champion |  Peter May |
| Other interested parties |
Any other parties who are also interested in applying Issue Solutions to their Datasets. Identify the party with a link to their contact page on the SCAPE Sharepoint site, as well as identifying their institution in brackets. Eg: Schlarb Sven (ONB) |
| Possible Solution approaches | Notes and discussion on similar issue: http://wiki.opf-labs.org/display/AQuA/Born-digital+-+migration+success |
| Context | Details of the institutional context to the Issue. (May be expanded at a later date) |
| Lessons Learned | Notes on Lessons Learned from tackling this Issue that might be useful to inform the development of Future Additional Best Practices, Task 8 (SCAPE TU.WP.1 Dissemination and Promotion of Best Practices) |
| Training Needs | Is there a need for providing training for the Solution(s) associated with this Issue? Notes added here will provide guidance to the SCAPE TU.WP.3 Sustainability WP. |
| Datasets | Reference to the appropriate Collection page, by hyperlink. Note that all Issues MUST be linked to at least one Dataset! |
| Solutions | Reference to the appropriate Solution page(s), by hyperlink |
Evaluation
| Objectives | Which scape objectives does this issues and a future solution relate to? e.g. scaleability, rubustness, reliability, coverage, preciseness, automation |
| Success criteria | Describe the success criteria for solving this issue - what are you able to do? - what does the world look like? |
| Automatic measures | What automated measures would you like the solution to give to evaluate the solution for this specific issue? which measures are important? If possible specify very specific measures and your goal - e.g. * process 50 documents per second * handle 80Gb files without crashing * identify 99.5% of the content correctly |
| Manual assessment | Apart from automated measures that you would like to get do you foresee any necessary manual assessment to evaluate the solution of this issue? If possible specify measures and your goal - e.g. * Solution installable with basic linux system administration skills * User interface understandable by non developer curators |
| Actual evaluations | links to acutual evaluations of this Issue/Scenario |