Karen, Micah et al -  I have a rather focused need but I'll throw it
out....One thing that I'd like to at some point discuss is how the
fixity check information, if generated and reported by storage layer
(and trusted -i.e. using N-Once or similar) is best exposed out/up to
the front-end application or user of said storage.

PREMIS data dictionary/XML format could be used, but frankly I'm not
hearing people outside of libraries being aware of PREMIS. Which is
frustrating. 

Aside from this, the topics shared in this thread are great. I'm in!

Gail




Gail Truman
Truman Technologies, LLC

Protecting the world's digital heritage for future generations
www.trumantechnologies.com
facebook/TrumanTechnologies

510 502 6497




-------- Original Message --------
Subject: Re: [NDSA-INFRASTRUCTURE] Fixity check project
From: Karen Cariani <[log in to unmask]>
Date: Sat, October 05, 2013 10:29 am
To: [log in to unmask]

Hi everyone,

I'm trying to pick this conversation up again. We can discuss on our
next call. Anyone have any other thoughts to add to Micah's?

Karen

From: "Dr. Micah Altman"
<[log in to unmask]><mailto:[log in to unmask]>>
Date: Friday, September 20, 2013 4:14 PM
To: Karen Cariani
<[log in to unmask]><mailto:[log in to unmask]>>
Cc: NDSA list serv
<[log in to unmask]><mailto:[log in to unmask]>>
Subject: Re: [NDSA-INFRASTRUCTURE] Fixity check project


 2. Fixity trade offs decision tool. Given different systems, different
kinds of content, different scales of content etc. there should be
different approaches to the frequency of fixity checking. There is
interest in developing some kind of grid, or decision tree that could
help orgs decide the best approach to how frequently to check the fixity
of their content.

It seems to me that 2 is the logical foundation for 1. That is -- one
should have a desired strategy for fixity checking in mind before
developing guidance aimed at helping those new to the area to implement
such a strtagey.

Anyone interested in number 1 specifically or number 2? Should we start
on both and see how it breaks out?
For number 2 were a number of ways we could break this out and look at
it, or rather a number of parameters to frame it. Here are the ones
listed above:

System type
Type of content
Scale of content (not sure what this means)
Frequency based on those factors
Any others?

(I'm not sure what is meant by "system type". )

My hypothesis is that the factors that drive an appropriate choice of
strategies are:
 - number of objects in collections
 - number of collections
 - size of objects
 - willingness to accept risk of loss ( or alternatively, budget --
which will indirectly bound risk acceptance)
 - content type / structure
 - trust model

Based on these factors the strategy at the "leaf" nodes of the tree
might involve recommended combinations of parameters :
 - compression algorithm, number of replication, fixity computation
algorithm, verification algorithm, verification frequency, repair
frequency

best,

Micah


Karen



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--
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Micah Altman, Ph.D. <http://micahaltman.com> Twitter: @drmaltman
Director of Research -- MIT Libraries; Head/Scientist, Program on
Information Science
Non-Resident Senior Fellow, Brookings Institution
"Entia non sunt multiplicanda sine necessitate" - Doctor Invincibilis
(Corollary, "Ad indicia spectate.")


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