Timecode Metadata

Timecode metadata are the critical link in the between textual content and audio or video in digital environments. Different architectures for timecode deployment have evolved independently in the creation of digital oral history collections, and all help to significantly increase digital accessibility. With many models now on the table it is an appropriate time to take inventory of what approaches are available, closely evaluate the relationship between these models, understand the range or textual data they are linked to, and elucidate the current “state of the art” to find common ground for future developments. 

Timecodes are being put to use in two broad ways: 1.) as transcription timecodes, enhancing full text transcriptions with a cross-reference to time points in the source audio or video, and 2.) as audio or video file metadata enhancing a longer audio or video file, or A/V timecodes. Within A/V timecodes two basic models are emerging, one that uses timecodes pointing to a single point in time in the digital file, allowing the user to play forward from that point. (We might call these indexing point timecodes.)  In another model, (which we might call passage timecodes), timecodes are defined as inpoints and outpoints giving meaningful content within a longer digital file its own begining, middle and ending. 

The latter model of defining passage timecodes can take place in database environments where the in/out points are just references that move the listener digitally (hypertextually) to the passage of interest. In other contexts, practitioners manage oral histories by hard-editing passages permanently, thus creating segments or clips from the full length digital source file.   

All timecode deployments require choices to be made--regarding the frequency of transcription or indexing point timecodes, or the length and comprehensiveness of passages timecodes. No standards have been set as to how these choices are made and there are strengths and weaknesses of the different approaches. I hope to have the opportunity to compare notes with others using the various models, determine the trades-offs between models, establish what can and cannot be standardized, and allow digital oral history stewards to proceed with future investments in software more informed.

 

Video and Archive Retrieval Models # 3

Today I met with the program manager of a local arts organization that has a SAMMA video digitization system. SAMMA is now part of Front Porch Digital, and they now have a host of products and services. Prominently featured on their website is a cloud solution for storing all the digital video... looks progressive, but expensive!

Probably the most frightening and sobering thing I learned about digitizing with a SAMMA system today is that you can generate terabytes of data in a matter of days. Thus, not only is content management of digital video a critical concern--assuring he content is readily accessible withing and across tapes. There is a formidable challenge of how to deal with the uncompressed media once your work starts flowing. Do the costs of storage and raw data management ultimately dwarf the cost of digitization when you work with such a high end system?

Video and Archive Retrieval Models # 2

Today, Mike, Melanie and I ventured over to the Center for Documentary Media at the University at Buffalo. We wanted to learn more about Final Cut Pro and Avid, and think about ways in which their expanding metadata capacities might approach the database capabilities of Interclipper. In the process, we talked a lot about two types of Adobe Software: Bridge and Lightroom.

Both software come bundled with various Adobe Suites and both are heavily oriented toward photo management. As a follow up I checked out some random Youtube videos and eventually came to some put out by Adobe themselves--by their Evangelists & Experts. Short of going to lynda.com, this is a good place to look for quick tutorials on Adobe products (and some are produced by lynda).


One video stated that Lightroom uses a database whereas Bridge does not... I'll need to look into that. The most important thing I gathered from Lightroom is that you can make groupings without actually moving stuff around. This is really the key concept we're looking for in multi-media software. We have to be able to be able to "put" stuff in categories, without really putting them anywhere.

Bridge and Lightroom really caught my attention for photo management. But the search remains for management software that helps get video under control...

Video and Archive Retrieval Models # 1

Melanie and I wanted to have an understanding of what the pros to do retrieve archival and recent footage for news broadcasts. We went to WIVB TV Channel 4 here in Buffalo and talked to chief photographer Mike Mombrea and learned a few things..

• They use special software add-ons that are part of the AVID editing program (iNews, Interplay). 
• In the software, they can search the titles of clips (or slugs) from past programs but also by the scripts associated with those clips.
• The reporters develop the scripts in tandem with the editors, artfully sequencing video and audio as well as the newscasters' scripts.
• Full, uncompressed video does not go back far for retrieval--on the order of days. A lot is archived on Beta tape and more recently on DVD (BlueRay) disk. They can retrieve footage from the network (CBS) as well, which downloads in real time to their local drives.

Some overall impressions include the fact that chronology rules the day as the major organizational for a 24-hour news cycle operation as this... makes sense! If you know when something specifically was broadcast , it's easy to find. The set up is not for the average citizen (or even the newspeople) just to browse around in to find something interesting. Bringing the exploration concept to news footage will be one of our challenges in our new project with the Buffalo Broadcasters Association.

"Indocumentation" as the essense of Oral History

Digital Indexing enhances oral history collections that otherwise cannot be easily accessed. We often use a “shoebox” metaphor to emphasize the importance of indexing: A collection of digital audio or video that is not indexed is in a digital shoebox, which is not much better than a real shoebox of un-digitized cassette or video tapes forgotten in a closet somewhere. By annotating and indexing discrete passages of audio/video, we create access to collections that would otherwise be cumbersome if not impossible to make use of.

Today, I want to take a moment to talk about the recording: The recording itself not only provides “access” to some living memory because it is in a re-playable medium, but it is a form of documentation. It occurs to me that the creation of new documentation is the essential element that makes recorded interviews so powerful. The moment things take documentary form—whether and email, an oral history recording, or even a produced documentary film—is when they have the potential to become part of a larger discourse. This moment of incarnation, or perhaps “indocumentation,” is where ideas become things we can really talk about, but also do something about…

Locative Metadata

When we index at Randforce, we develop controlled vocabularies (also known as thesauri) for annotated passages of audio and video. Technically, the objects we are indexing are metadata themselves. (Thus we create meta-metadata!) For discussion purposes, the objects we are indexing are a/v clips.

We often conceptualize the process of indexing to be less like "labeling" something (i.e., what is it called?) and more like "putting it somewhere" (i.e., where does it belong?) and we sometimes call this "sorting the laundry." The proverbial laundry baskets are created by us indexers and the objects influence its creation in a meaningful way. It seems to me, that when these terms are fed back to the object, they are a unique type of metadata.

I'd like to propose that this type of metadata being created might be called "locative metadata". Locative metadata, conceptually, is more than an attribute of the object. Locative metadata implies "where it is" relative to other objects in the collection, not just what it is about. Locative metadata might also be a purely digital concept exactly because an object can reside in more than one location at a time (without needing to take up additional space). In this sense, library subject headings--from the book's perspective--is locative metadata, as are hyperlinks to an object from the objects' perspective.

Hello!

Welcome to the inaugural post to our Randforce blog! We look forward to using this medium as a place to share new ideas that have emerged in our practice of oral history content management.

The foundations of our work began when our Principal, Michael Frisch, adopted software to make long audio and video recordings accessible in new ways. As consultants on dozens of projects we have learned as much as we have taught in this world of “digital indexing”. The foundation of our work is in applying new methodology and technology for creating access to audio/video content for oral history collections. The controlled vocabularies we develop use a faceted indexing approach applicable to any digital content.

We plan to use this medium to publish ideas worth sharing that may not be ready for journal publication, that have emerged from our practice. Documenting our work is challenging because we are usually busy practicing it. Also, we are exploring work that lies between several worlds simultaneously, including oral history, library and information science, museum curation, database development, a/v content management, and multi-media publication. We hope for this to be a place where readers interested in these topics can keep track of what we are working on between the longer cycles of academic conferences and journal publication.