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Featured Items of the Collection
Jul
10
Standards and Best Practices
July 10, 2012 | | Leave a Comment
This website contains resources developed and adopted by the Queens Memory Project team to create and maintain our collaborative digital archives. Each blog post (listed in the column to the right) is dedicated to a different aspect of the project. Our intent is to make this information available to other organizations developing similar projects and also to students interested in our process.
The other goal for this website is to provide community members with simple guidelines to help them produce and donate records to the QMP. The “Forms for Participants” menu (to the right) provides easy access to the guidelines and forms needed to participate in the Queens Memory Project.
Among the contents of these blogposts are training materials, a cataloging manual for our CollectiveAccess database, and digitization guidelines. If you are interested in learning more about the Queens Memory Project, please contact QMP Director, Natalie Milbrodt, Natalie.Milbrodt@qc.cuny.edu.
Apr
28
Using Analytics
April 28, 2012 | Tagged analytics, social networking, user tracking | Leave a Comment
By: Kristin Resurreccion
An online digital archive like the Queens Memory Project is constantly evolving with every user interaction and administrative mediation, in addition to the ever-shifting environment of the World Wide Web. In an effort to improve the QMP’s relevance and effectiveness online, we have recently applied the use of free Web analytics software to track activity on the project’s website and social networking accounts.
Site Tracking with Google Analytics
Google Analytics installation is as simple as creating an account and copying and pasting a few lines of code from Google Analytics to the site itself. The software then begins tracking site usage statistics and translates them into easily interpretable charts and graphs.
Some essential questions that can be answered by using analytics include the following:
Where are our users coming from? If they are coming from a search engine, what were they searching for?
How many unique users visit the site? How many returnees?
How are users navigating through the site? Through which pages are they entering the site? What subsequent pages are they visiting?
How long are users on the site? On individual pages?
Where are they dropping out/signing off?
Which pages are getting the most traffic?
What internet browsers and devices are most popular among our users?
Some more advanced features on Google Analytics include the ability to set and track specific conversion goals and funnels. According to Google, goals are website pages that serve as conversions for your site, like an About page or a confirmation page following site registration. A funnel represents the path that users take on the way to reaching that particular conversion goal.
For example, we can set up a conversion funnel for the manner in which we anticipate our users navigating through the site. The first step in the funnel is the homepage, followed by a browsing option and a search result page, which will, hopefully lead to the end goal of accessing an individual record page. Setting up a conversion funnel like this one will allow you to see if visitors are actually using the site in the manner that you have anticipated by showing what percentage of users are making it all the way through the funnel and where they are dropping off along the way.
Another relatively new feature allows for tracking specific events. These include user interactions that are not directly related to pageviews. For example, you can set up a custom report to track how many users are downloading materials from your site, or how long users spend listening to an audio file.
User Tracking on Facebook & Twitter
Social networking metrics demonstrate the manner in which users respond to our various social networking outlets. QMP has employed the use of various metrics-gathering applications for these accounts. Facebook offers built-in metrics for its users via Insights, and while Twitter Analytics is still currently in development, other third-party applications like TwentyFeet offer comparable services. Find out what kind of exposure your site is getting via social networking outlets and whether or not the activity on your social networking accounts is corresponding to an increase in site visits.
With even this basic understanding of our users provided by analytics (What is popular?), and the potentially problematic areas that arise (Where are they dropping off? What isn’t being used?), we can already begin to tweak and redesign aspects of the site and use the information to guide future content development. While tracking use through analytics software constitutes only one small part of project evaluation, it can be the first positive step in keeping current and optimizing both your site design and social networking strategies for improved access, project administration, and user satisfaction.
For more on the useful applications of analytics in online archives, see Chris Prom’s Using Web Analytics to Improve Online Access to Archival Resources, available from American Archivist.
Nov
14
Timecode Outlines for Interviews
November 14, 2011 | Tagged timecode, transcription | Leave a Comment
There is an ongoing debate amongst oral history practicitioners about the value of creating transcripts for oral history collections. The Oral History Association has an excellent wiki article on this debate.
The Queens Memory Project considers each oral history recording an important historical record and has a policy of creating timecode outlines instead of transcriptions for our interviews. Timecode outlines summarize the topics discussed during the interview with their corresponding timecode “in” points. The timecode outline along with edited audio clips (generally one to three minutes in duration) are accessible on the public QMP site. Full interviews are available upon request to researchers who can use the timecode outlines and a digital media player in the archives reading room to jump to sections of interest within the interview.
QMP template for oral history interview timecode outlines
Sample of a completed timecode outline for oral history interview with Carol Lee Whiting.
Nov
6
Cataloger Guide
November 6, 2011 | Tagged cataloging, metadata, standards | Leave a Comment
In developing the Queens Memory Project, we had to provide our catalogers with rules to follow when creating new records to ensure consistency across the catalog. This guide provides detailed instructions for catalogers on how to create and manipulate records in our customized version of CollectiveAccess, the open source software we use.
Our task in developing these cataloging rules was to select a set of standards that were appropriate for our project. Our first priority was to use Queens Library’s cataloging standards since QL would be the long-term repository for the records. Where there was not yet a policy to follow, we had to draw from standards adopted by professional associations and other institutions. A wonderful resource for finding standards is Jenn Riley’s Glossary of Metadata Standards.
Our cataloger’s guide for the Queens Memory Project (linked below) is constantly evolving as we encounter new situations and have to establish rules for how we want to catalog something similar in the future.
Nov
6
Metadata Crosswalk
November 6, 2011 | Tagged cataloging, metadata, standards | Leave a Comment
It is important to remember that you don’t have to use every field in a metadata standard. But you do have to use each field accurately so your records make sense next to other records created using the same fields.
When a digital archive contains records using different metadata standards, it is important to create a map or “crosswalk” between the fields in each type of record. That is what we did for the Queens Memory Project.
If you click the link above, it will lead you to a crosswalk I developed with Julia Weist, the cataloger/programmer who configured the open source software, CollectiveAccess, for The Queens Memory Project. If you use your web browser to zoom in for greater detail, you’ll see a series of columns for each type of record we create in the cataloging database, “maps,” “images,” etc.
The challenge in creating this crosswalk was to decide first what metadata fields were important to capture based on three factors:
1. Cataloging standards at our two partnering institutions
2. Our best guess about what our users would want to know about records
3. The quantity of metadata we could afford to pay catalogers to generate for each record given our small budget
Once we figured out what information was important, we had to unify our metadata across record types. Since Queens Library is the institution providing long-term preservation and we hope to someday get records from the Queens Memory Project into their general catalog, we wanted to conform to their metadata standards. This meant creating VRA records for images and MARC records for everything else. The MARC and VRA records we create for the Queens Memory Project are minimal compared to the detailed records using many more fields that the library’s catalogers create. This is fine as long as the fields that we do create, map correctly when Queens Library ingests them.
You’ll notice three-digit numbers next to many of the field names – these are MARC field numbers. If you follow the same field from left to right across the page, you will see how the same information is captured in each record, but because we’re working with different kinds of materials and with different metadata standards, they might have slightly different names or different numbers.
For example, the “300 Physical Description” field in records for maps, books, and news clippings (MARC) = “Recording Format” for oral history and wild sound recordings (MARC) = ” Material and Measurements” in image records (VRA) = the “Physical Description” field in the CollectiveAccess cataloger’s interface screen.
By unifying these fields, we’re able to create a digital archives that gives users a consistent set of fields when they retrieve any record in the system. We provide Queens Memory Project catalogers with metadata field titles that are as consistent and descriptive as possible. And finally, we end up with records that will ingest correctly into the Queens Library catalog.