My impression is that the XC Metadata Toolkit makes no particular assumptions about "RDA's interpretation of the FRBR model", or really even the existence of a FRBR model. It's intended as a generalized toolkit for metadata normalization and transformation.

McGrath, Kelley C. wrote:
Thanks, Jonathan. I had thought about the XC Metadata Toolkit, but I think 
perhaps our use case is sufficiently non-standard that it might not be easier 
than starting from scratch. 1) The moving image cataloging community has 
significant disagreements with RDA's interpretation of the FRBR model and for 
this project we are using a modified FRBR model anyway; I think Rochester is 
using a more orthodox model. 2) I think we are trying to squeeze a lot more out 
of the metadata than most of the other FRBRizing applications I've seen. But 
it's probably worth checking out. I do think XC's OAI toolkit in particular and 
possibly the discovery layer could be useful to us when we get further along.

I think we are probably looking at hiring someone to do custom programming, but 
I feel that I am in a bit over my head knowing how to specify what to ask for, 
much less to come up with a realistic budget and timeline for a grant. And I 
guess the reason I was asking about tools was that I was getting the impression 
that we would have to specify something when advertising for a programmer. I 
obviously have no particular preferences except for not wanting to end up in a 
dead end.

Kelley

-----Original Message-----
From: Code for Libraries [mailto:[email protected]] On Behalf Of 
Jonathan Rochkind
Sent: Thursday, April 01, 2010 11:47 AM
To: [email protected]
Subject: Re: [CODE4LIB] Looking for advice for project to tranform MARC bib 
data into work records

I don't have enough experience with that problem area to be sure of what's out there and what would work, but I was pretty impressed with the presentation on the XC Metadata Toolkit at the recent Code4Lib conference, I think it is designed to do at least some, if not all, of your tasks you outline, and seems to be pretty solid. It might be worth contacting Jennifer Bowen to see what she has to say about your problem case and XC's ability to meet it, or if she has any other tool suggestions, she's pretty clever on this stuff. And XC is probably interested in getting their software used by folks like you.

Another alternative is simply hiring a programmer to write something custom to do exactly what you need; that's what most of us probably end up doing, because we don't know about suitable general-purpose metadata control software that's still customizable enough to do what we need. But I think the XC Metadata Toolkit is definitely _intended_ to fill that niche. If you can hire someone with experience with library metadata, and you can have people giving them requirements who understand what software can and can not actually do (like yourself Kelley), this is not TOO much of an unusual project, in just about any programming language (I'd do it in ruby, but let's not start THAT thread which has thankfully died again. ) ).

Jonathan

McGrath, Kelley C. wrote:
I am hoping someone can help me with my current conundrum. I am looking for 
recommendations for tools and methods for a project I am working on to try to 
implement some of the Online Audiovisual Catalogers (OLAC) work on FRBR works 
and moving images (http://www.olacinc.org/drupal/?q=node/27). I am not a 
programmer or coder, but we are going to have to hire someone to do this and 
give them some direction. So I am interested in what tools you would recommend 
for this purpose and why, as well as any other advice anyone can give me.

Basically what we want to do is take a large number of MARC bibliographic 
records for moving images, extract the information that might describe the FRBR 
Work and parse and normalize it. We then want to use this data to create 
provisional Work records. I am not so worried about getting the data out of 
MARC, but about how to work with the data once it's out. I have listed the main 
steps we anticipate needing in broad outlines below.

1.      Parsing and Normalizing Data

There are several types of situations from easiest to harder with examples:

a.       Data that is already in machine-comprehensible form:

Coded language data, e.g., an 041 $h of fre means the movie was originally in 
French

A 700 field with a $4 of drt means that the name in that in that 700 is 
(hopefully) the authorized form of the name of the director of the movie

A DateType fixed field of p means that the lower of Date1 and Date2 is the 
original date of the movie (technically this should always be Date2, but some 
libraries reverse the order to support sorting by original date in their OPACs)

b.      Data that can be extracted using keywords in textual fields

We can often extract an original date from a note field by identifying the combination of a year (18xx, 19xx, or 200x) 
and a keyword that signifies that it is an original production date note, such as "originally," 
"release," "broadcast," or "produced."

c.       Data that requires matching between information in more than one field

In order to identify the authorized form of the name of a person performing a particular function, 
in many cases we have to try to match the authorized form of the name to a transcribed statement 
including both the function and the name. Note that functions can be transcribed in many forms 
(directed by, director, direction) and languages (Regie, kantoku). Also the transcribed name may 
vary from the authorized name ("Andrei Tarkovsky" vs. "Tarkovskii, Andrei 
Arsenevich"). Neither of these is a practical problem to solve completely, but we would like 
to be able to make inferences as follows (probably starting from the 7xx fields and trying to find 
a matching transcribed statement).

245$c includes "directed by Steven Spielberg"
+ 700 Spielberg, Steven, $d 1946-
= n  79148103 (Spielberg, Steven, $d 1946-) is the director

2.      Ranking Information Sources Within Records

We have multiple possible methods for extracting most types of data. We plan to 
rank these data sources in terms of their probable accuracy. Some of the 
ranking we can predict up front and probably skip step 1 for the non-preferred 
data sources. Some data sources we can probably rank based on analysis of 
preliminary results. Some sources probably can't be ranked and we would want to 
know when a record presents conflicting data (e.g., one original date in a note 
and a different one in a fixed field)

3.      Clustering Records for the Same Work

In our data pool, we will have cases where multiple bibliographic records 
represent the same work. We need to cluster the ones that represent a given 
work based on data extracted in the above steps. Information such as title, 
original date, director, or production company is probably useful for this 
purpose.

4.      Creating Provisional Work Records by Identifying the Most Likely Value 
for Each Data Element from the Work Cluster

Once we have clustered the records for the works, we want to create a single 
composite work record from the data in the clustered records. We will need some 
algorithm, possibly as simple as a majority vote or perhaps a majority vote per 
manifestation rather than per record, to determine the probable best value for 
each field in our preliminary work record.

Thanks in advance for any advice on tools or general thoughts on this. Also, 
are there any particular skills or qualities we should be looking for in a 
programmer?

Kelley McGrath
[email protected]


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