I stick by the notion that as long as a system can ingest/export data as well-formed RDF graphs, how you store it internally makes no difference.  As I've said before, our biggest product is modeled entirely using RDF, but we store the data in a MongoDB document database, because it fits our actual needs better than a triple store.

It is possible, btw, to produce an ordered list for author/editor names in RDF, but it's horribly ugly: you can use rdf:Seq or rdf:List  They each have their pluses and minuses: rdf:List is absolutely awful to work with in any serialization except Turtle (where it's super easy! see:, but has the downside of being semantically open.  That is, you cannot definitively say "these are *all* of the authors and there are no more".

rdf:Seq (which is an rdf:Container) is considered closed (i.e. there is no assumption that there would be anything else in the current container that appears somewhere else) but, unfortunately has no syntactic sugar like Collections in Turtle.

Containers and Collections being such major pain points in RDF, JSON-LD threw all of it away for a *much* simpler implementation:

All that said, as long as you can serialize your author lists as one of these, model it however suits your needs the best for your regular workflows/needs.


On Mon, Apr 13, 2015 at 6:12 AM Kelley McGrath <[log in to unmask]> wrote:
Although much of the discussion on storing bibframe data went over my head, some things have been niggling at me for a while that maybe are related to this thread.

I get that it would be good for us to publish our data as linked data. I get that it would be good for us to consume linked data. I get that we should re-use other people's URIs in our data to save time and reduce maintenance. I get that we should match our identifiers to other people's URIs in order to connect more information.

However, it has not been clear to me that it makes sense for us to store and maintain our data as linked data. And yet, I don't see any alternative plan being developed.

This may be sacrilege, but from what I understand there seem to be things that linked data isn't good at. For example, retaining the order of things like authors' names or connecting a specific place and publisher written on the title page or a book. Sometimes when this has been discussed on this list, I get the impression that we shouldn't want to do those things; that they're somehow obsolete.

I can't get my head around that. Maybe you don't need those things for linking, but I don't think linking is the only thing that we want to do with our data. For example, it emerged recently, when MPOW changed to a discovery layer that didn't do such a good job with this initially, that the ability to generate citations is hugely important to a significant portion of our patrons. If you want to generate an accurate citation, you need to know the order of the author's names.

It has been suggested to me that we shouldn't be generating citations, but rather storing them as strings. However, again I seem to be missing something because that doesn't seem very optimal to me. Do you store a separate string for every format: APA, MLA, Chicago, etc.? What do you do when a style guide gets updated? It might not be very easy to update millions of strings. What if a new citation style is invented and becomes popular? It just seems to me to be more flexible and powerful to store the individual pieces of data and generate the citations. On the other hand, publishing citations as strings might be okay for most use cases.

MARC records are a single unit. If a record has been edited by multiple parties, you can't tell who changed what when, which is a challenge for trouble-shooting and quality control. Linked data statements are atomistic, but it sounds to me like it is still hard to say anything much *about* the statement other than maybe the domain name used by whoever made it. It would be useful to track more about individual statements, such as when they are made and whether or not they are currently considered valid (one of the problems with bad data in the OCLC master record environment is that even if you take erroneous information out, all it takes is one batchload to put it right back in).

As some of you know, I have been working on a project to crowdsource the parsing of film credits in catalog records (help us out at ). One result of this is that we have links between transcribed names in records and their authorized form.  It occurs to me that this might be a useful thing to record proactively. For example, even in a world of identifiers, we still need to choose one of many possible versions of a name to display to the user (unless you're going to display them all at once in some kind of cluster, which is not very user-friendly in many situations). In library cataloging, traditionally, for people the most common or the most recent variation is chosen as the preferred one. However, if the math changes, you have to wait for a person with NACO powers to notice this and fix it. This doesn't always happen in a timely fashion. In his earliest movies, Laurence Fishburne was credited as Larry Fishburne so this is how his name was established. It then persisted in library catalogs as Larry Fishburne for long, long after after he made the change (I think ten years) . If you had data like this, the computer could do the math and display the most current form.

Name on piece   Year and work
Larry Fishburne 1984    The Cotton Club
Larry Fishburne         1985    The Color Purple
Laurence Fishburne      1993    Searching for Bobby Fischer
Laurence Fishburne      1999    The Matrix
Laurence Fishburne      2006    Mission: Impossible III

(if you look at IMDb's Laurence Fishburne page, they do track all this, along with the names of the characters he played: )

With linked data, you can say

Movie1  -- has actor  -- LF123
Movie1 -- has actor's name credited as  -- "Laurence Fishburne"
LF123  -- has been credited as -- "Laurence Fishburne"

But you can't get all three of those things to connect up, at least not without using blank nodes, which then makes your data not so shareable. So far as I can see, anytime you want to connect the dots between more than two pieces of information or say something about a statement, it doesn't work so well with triples. This might not be such a problem for linking, but I think there are other things we want to do with our data where we may want this ability.

What happens if we implement bibframe and we don't store and maintain our data as bibframe triples? We could just keep generating bibframe from MARC records, but then we haven't really replaced MARC or gotten more flexible, structured data than we already have.

Alternatively, ILS vendors could come up with another internal format for us to store data in. However, I don't know that they have the right expertise for this nor any economic incentives. If this happened, we would also end up with much less portable data. Imagine if bib records were like item records and every system had its proprietary format and unique combination of fields. Anytime you do an ILS migration, there is a lot of item data that can't be moved to the new system, either because it's structured differently or because there is no equivalent field.

This may be completely wrong-headed and I think I'm using the wrong vocabulary some places, but I thought I'd throw it out there in case someone can enlighten me.