Duke University Libraries (DUL) is recruiting two (2) Repository Services Analysts to ingest and help collaboratively manage content in their digital preservation systems and platforms. These positions will partner with the Research Data Curation, Digital Collections, and Scholarly Communications Programs, as well as other library and campus partners to provide digital curation and preservation services. The Repository Services Analyst role is an excellent early career opportunity for anyone who enjoys managing large sets of data and/or files, working with colleagues across an organization, preserving unique data and library collections, and learning new skills.
DUL will hold an open zoom session where prospective candidates can join anonymously and ask questions. This session will take place on Wednesday January 12 at 1pm EST; the link to join is posted on the libraries’ job advertisement.
The Research Data Curation Program has grown significantly in recent years, and DUL is seeking candidates who want to grow their skills in this area. DUL is a member of the Data Curation Network (DCN), which provides opportunities for cross-institutional collaboration, curation training, and hands-on data curation practice. These skills are essential for anyone who wants to pursue a career in research data curation.
Ideal Repository Services Analyst applicants have been exposed to digital asset management tools and techniques such as command line scripting. They can communicate functional system requirements between groups with varying types of expertise, enjoy working with varied kinds of data and collections, and love solving problems. Applicants should also be comfortable collaboratively managing a shared portfolio of digital curation services and projects, as the two positions work closely together. The successful candidates will join the Digital Collections and Curation Services department (within the Digital Strategies and Technology Division).
Please refer to the DUL’s job posting for position requirements and application instructions.
Featured image – screenshot from the Sunset Tripod2 project charter.
Realizing that my most recent post here went up more than a year ago, I pause to reflect. What even happened over these last twelve months? Pandemic and vaccine, election and insurrection, mandates and mayhem – outside of our work bubble, October 2020 to October 2021 has been a churn of unprecedented and often dark happenings. Bitstreams, however, broadcasts from inside the bubble, where we have modeled cooperation and productivity, met many milestones, and kept our collective cool, despite working nearly 100% remotely as a team, with our stakeholders, and across organizational lines.
Last October, I wrote about Sunsetting Tripod2, a homegrown platform for our digital collections and archival finding aids that was also the final service we had running on a physical server. “Firm plans,” I said we had for the work that remained. Still, in looking toward that setting sun, I worried about “all sorts of comical and embarrassing misestimations by myself on the pages of this very blog over the years.” I was optimistic, but cautiously so, that we would banish the ghosts of Django-based systems past.
Reader, I have returned to Bitstreams to tell you that we did it. Sometime in Q1 of 2021, we said so long, farewell, adieu to Tripod2. It was a good feeling, like when you get your laundry folded, or your teeth cleaned, only better.
However, we did more in the past year than just power down exhausted old servers. What follows are a few highlights from the work of the Digital Strategies and Technology division of Duke University Libraries’ software developers, and our collaborators (whom we cannot thank or praise enough) over the past twelve months.
In November, Digital Projects Developer Sean Aery posted on Implementing ArcLight: A Reflection. The work of replacing and improving upon our implementation for the Rubenstein Library’s collection guides was one of the main components that allowed us to turn off Tripod2. We actually completed it in July of 2020, but that team earned its Q4 victory laps, including Sean’s post and a session at Blacklight Summit a few days after my own post last October.
As the new year began, the MorphoSource team rolled out version 2.0 of that platform. MorphoSource Repository Developer Jocelyn Triplett shared a A Preview of MorphoSource 2 Beta in these pages on January 20. The launch took place on February 1.
After more than two years of work, we are happy to announce MorphoSource 2.0 is available! Includes color mesh and CT scan web previews, expanded metadata for non-CT modalities, and a greatly improved UI. Let us know what you think! https://t.co/D0zx9PDDE3
One project we had underway as I was writing last October was the integration of Globus, a transfer service for large datasets, into the Duke Research Data Repository. We completed that work in Q1 of 2021, prompting our colleague, Senior Research Data Management Consultant Sophia Lafferty-Hess, to post Share More Data in the Duke Research Data Repository! in a neighboring location that shares our charming cul-de-sac of library blogs.
The seventeen months since the murder of George Floyd have seen major changes in how we think and talk about race in the Libraries. We committed ourselves to the DUL Racial Justice Roadmap, a pathway for recognizing and attacking the pervasive influence of white supremacy in our society, in higher education, at Duke, in the field of librarianship, in our library, in the field of information technology, and in our own IT practices. During this time, members of our division have also participated broadly in DiversifyIT, a campus-wide group of IT professionals who seek to foster a culture of inclusion “by providing professional development, networking, and outreach opportunities.”
Digital Projects Developer Michael Daul shared his own point of view with great thoughtfulness in his April post, What does it mean to be an actively antiracist developer? He touched on representation in the IT industry, acknowledging bias, being aware of one’s own patterns of communication, and bringing these ideas to the systems we build and maintain.
One of the ideas that Michael identified for software development is web accessibility; as he wrote, we can “promote the benefits of building accessible interfaces that follow the practices of universal design.” We put that idea into action a few months later, as Sean described in precise technical terms in his July post, Automated Accessibility Testing and Continuous Integration. Currently that process applies to the ArcLight platform, but when we have a chance, we’ll see if we can expand it to other services.
The question of when we’ll have that chance is a big one, as it hinges on the undertaking that now dominates our attention. Over the past year we have ramped up on the migration of our website from Drupal 7 to Drupal 9, to head off the end-of-life for 7. This project has transformed into the raging beast that our colleagues at NC State Libraries warned us it would at the Code4Lib Southeast in May of 2019.
We are on a path to complete the Drupal migration in March 2022 – we have “firm plans,” you could say – and I’m certain that its various aspects will come to feature in Bitstreams in due time. For now I will mention that it spawned two sub-projects that have challenged our team over the past six months or so, both of which involve refactoring functionality previously implemented as Drupal modules into standalone Rails applications:
Quicksearch, aka unified search, aka “Bento search” – see Michael’s Bento is Coming! from 2014 – is now a standalone app; it also uses the open-source tool Apache Nutch, rather than Google CSE.
Each of these implementations was necessary to prepare the way for a massive migration of theme and content that will take place over the coming months.
When it’s done, maybe we’ll have a chance to catch our breath. Who can really say? I could not have guessed a year ago where we’d be now, and anyway, the period of the last twelve months gets my nod as the shortest year ever. Assuming we’re here, whatever “here” means in the age of remote/hybrid/flexible work arrangements, then I expect we’ll be burning down backlogs, refactoring this or that, deploying some service, and making firm plans for something grand.
This post was written by Jen Jordan, a graduate student at Simmons University studying Library Science with a concentration in Archives Management. She is the Digital Collections intern with the Digital Collections and Curation Services Department. Jen will complete her masters degree in December 2021.
The Digital Production Center (DPC) is thrilled to announce that work is underway on a 3-year long National Endowment for the Humanities (NEH) grant-funded project to digitize the entirety of Behind the Veil: Documenting African-American Life in the Jim Crow South, an oral history project that produced 1,260 interviews spanning more than 1,800 audio cassette tapes. Accompanying the 2,000 plus hours of audio is a sizable collection of visual materials (e.g.- photographic prints and slides) that form a connection with the recorded voices.
We are here to summarize the logistical details relating to the digitization of this incredible collection. To learn more about its historical significance and the grant that is funding this project, titled “Documenting African American Life in the Jim Crow South: Digital Access to the Behind the Veil Project Archive,” please take some time to read the July announcementwritten by John Gartrell, Director of the John Hope Franklin Research Center and Principal Investigator for this project. Co-Principal Investigator of this grant is Giao Luong Baker, Digital Production Services Manager.
Digitizing Behind the Veil (BTV) will require, in part, the services of outside vendors to handle the audio digitization and subsequent captioning of the recordings. While the DPC regularly digitizes audio recordings, we are not equipped to do so at this scale (while balancing other existing priorities). The folks at Rubenstein Library have already been hard at work double checking the inventory to ensure that each cassette tape and case are labeled with identifiers. The DPC then received the tapes, filling 48 archival boxes, along with a digitization guide (i.e. – an Excel spreadsheet) containing detailed metadata for each tape in the collection. Upon receiving the tapes, DPC staff set to boxing them for shipment to the vendor. As of this writing, the boxes are snugly wrapped on a pallet in Perkins Shipping & Receiving, where they will soon begin their journey to a digital format.
The wait has begun! In eight to twelve weeks we anticipate receiving the digital files, at which point we will perform quality control (QC) on each one before sending them off for captioning. As the captions are returned, we will run through a second round of QC. From there, the files will be ingested into the Duke Digital Repository, at which point our job is complete. Of course, we still have the visual materials to contend with, but we’ll save that for another blog!
As we creep closer to the two-year mark of the COVID-19 pandemic and the varying degrees of restrictions that have come with it, the DPC will continue to focus on fulfilling patron reproduction requests, which have comprised the bulk of our work for some time now. We are proud to support researchers by facilitating digital access to materials, and we are equally excited to have begun work on a project of the scale and cultural impact that is Behind the Veil. When finished, this collection will be accessible for all to learn from and meditate on—and that’s what it’s all about.
This post was written by Miriam Shams-Rainey, a third-year undergraduate at Duke studying Computer Science and Linguistics with a minor in Arabic. As a student employee in the Rubenstein’s Technical Services Department in the Summer of 2021, Miriam helped build a tool to audit archival description in the Rubenstein for potentially harmful language. In this post, she summarizes her work on that project.
The Rubenstein Library has collections ranging across centuries. Its collections are massive and often contain rare manuscripts or one of a kind data. However, with this wide-ranging history often comes language that is dated, harmful, often racist, sexist, homophobic, and/or colonialist. As important as it is to find and remediate these instances of potentially harmful language, there is lot of data that must be searched.
With over 4,000 collection guides (finding aids) and roughly 12,000 catalog records describing archival collections, archivists would need to spend months of time combing their metadata to find harmful or problematic language before even starting to find ways to handle this language. That is, unless there was a way to optimize this workflow.
Working under Noah Huffman’s direction and the imperatives of the Duke Libraries’ Anti-Racist Roadmap, I developed a Python program capable of finding occurrences of potentially harmful language in library metadata and recording them for manual analysis and remediation. What would have taken months of work can now be done in a few button clicks and ten minutes of processing time. Moreover, the tools I have developed are accessible to any interested parties via a GitHub repository to modify or expand upon.
Although these gains in speed push metadata language remediation efforts at the Rubenstein forward significantly, a computer can only take this process so far; once uses of this language have been identified, the responsibility of determining the impact of the term in context falls onto archivists and the communities their work represents. To this end, I have also outlined categories of harmful language occurrences to act as a starting point for archivists to better understand the harmful narratives their data uphold and developed best practices to dismantle them.
Building an automated audit tool
I created an executable that allows users to interact with the program regardless of their familiarity with Python or with using their computer’s command line. With an executable, all that a user must do is simply click on the program (titled “description_audit.exe”) and the script will load with all of its dependencies in a self-contained environment. There’s nothing that a user needs to install, not even Python.
Within this executable, I also created a user interface to allow users to set up the program with their specific audit parameters. To use this program, users should first create a CSV file (spreadsheet) containing each list of words they want to look for in their metadata.
In this CSV file of “lexicons”, each category of terms should have its own column, for example RaceTerms could be the first row in a column of terms such as “colored” or “negro,” and GenderTerms could be the first row in a column of gendered terms such as “homemaker” or “wife.” See these lexicon CSV file examples.
Once this CSV has been created, users can select this CSV of lexicons in the program’s user interface and then select which columns of terms they want the program to use when searching across the source metadata. Users can either use all lexicon categories (all columns) by default or specify a subset by typing out those column headers. For the Rubenstein’s purposes, there is also a rather long lexicon called HateBase (from a regional, multilingual database of potential hate speech terms often used in online moderating) that is only enabled when a checkbox is checked; users from other institutions can download the HateBase lexicon for themselves and use it or they can simply ignore it.
In the CSV reports that are output by the program, matches for harmful terms and phrases will be tagged with the specific lexicon category the match came from, allowing users to filter results to certain categories of potentially harmful terms.
Users also need to designate a folder on their desktop where report outputs should be stored, along with the folder containing their source EAD records in .xml format and their source MARCXML file containing all of the MARC records they wish to process as a single XML file. Results from MARC and EAD records are reported separately, so only one type of record is required to use the program, however both can be provided in the same session.
How archival metadata is parsed and analyzed
Once users submit their input parameters in the GUI, the program begins by accessing the specified lexicons from the given CSV file. For each lexicon, a “rule” is created for a SpaCy rule-based matcher, using the column name (e.g. RaceTerms or GenderTerms) as the name of the specific rule. The same SpaCy matcher object identifies matches to each of the several lexicons or “rules”. Once the matcher has been configured, the program assesses whether valid MARC or EAD records were given and starts reading in their data.
To access important pieces of data from each of these records, I used a Python library called BeautifulSoup to parse the XML files. For each individual record, the program parses the call numbers and collection or entry name so that information can be included in the CSV reports. For EAD records, the collection title and component titles are also parsed to be analyzed for matches to the lexicons, along with any data that is in a paragraph (<p>) tag. For MARC records, the program also parses the author or creator of the item, the extent of the collection, and the timestamp of when the description of the item was last updated. In each MARC record, the 520 field (summary) and 545 field (biography/history note) are all concatenated together and analyzed as a single entity.
Data from each record is stored in a Python dictionary with the names of fields (as strings) as keys mapping to the collection title, call number, etc. Each of these dictionaries is stored in a list, with a separate structure for EAD and MARC records.
Once data has been parsed and stored, each record is checked for matches to the given lexicons using the SpaCy rule-based matcher. For each record, any matches that are found are then stored in the dictionary with the matching term, the context of the term (the entire field or surrounding few sentences, depending on length), and the rule the term matches (such as RaceTerms). These matches are found using simple tokenization from SpaCy that allow matches to be identified quickly and without regard for punctuation, capitalization, etc.
Although this process doesn’t necessarily use the cutting-edge of natural language processing that the SpaCy library makes accessible, this process is adaptable in ways that matching procedures like using regular expressions often isn’t. Moreover, identifying and remedying harmful language is a fundamentally human process which, at the end of the day, needs a significant level of input both from historically marginalized communities and from archivists.
Matches to any of the lexicons, along with all other associated data (the record’s call number, title, etc.) are then written into CSV files for further analysis and further categorization by users. You can see sample CSV audit reports here. The second phase of manual categorization is still a lengthy process, yielding roughly 14600 matches from the Rubenstein Library’s EAD data and 4600 from its MARC data which must still be read through and analyzed by hand, but the process of identifying these matches has been computerized to take a mere ten minutes, where it could otherwise be a months-long process.
Categorizing matches: an archivist and community effort
To better understand these matches and create a strategy to remediate the harmful language they represent, it is important to consider each match in several different facets.
Looking at the context provided with each match allows archivists to understand the way in which the term was used. The remediation strategy for the use of a potentially harmful term in a proper noun used as a positive, self-identifying term, such as the National Association for the Advancement of Colored People, for example, is vastly different from that of a white person using the word “colored” as a racist insult.
The three ways in which I proposed we evaluate context are as follows:
Match speaker: who was using the term? Was the sensitive term being used as a form of self-identification or reclaiming by members of a marginalized group, was it being used by an archivist, or was it used by someone with privilege over the marginalized group the term targets (e.g. a white person using an anti-Black term or a cisgender straight person using an anti-LGBTQ+ term)? Within this category, I proposed three potential categories for uses of a term: in-group, out-group, and archivist. If a term is used by a member (or members) of the identity group it references, its use is considered an in-group use. If the term is used by someone who is not a member of the identity group the term references, that usage of the term is considered out-group. Paraphrasing or dated term use by archivists is designated simply as archivist use.
Match context: how was the term in question being used? Modifying the text used in a direct quote or a proper noun constitutes a far greater liberty by the archivist than removing a paraphrased section or completely archivist-written section of text that involved harmful language. Although this category is likely to evolve as more matches are categorized, my initial proposed categories are: proper noun, direct quote, paraphrasing, and archivist narrative.
Match impact: what was the impact of the term? Was this instance a false positive, wherein the use of the term was in a completely unrelated and innocuous context (e.g. the use of the word “colored” to describe the colors used in visual media), or was the use of the term in fact harmful? Was the use of the term derogatory, or was it merely a mention of politicized identities? In many ways, determining the impact of a particular term or use of potentially harmful language is a community effort; if a community member with a marginalized identity says that the use of a term in that particular context is harmful to people with that identity, archivists are in no position to disagree or invalidate those feelings and experiences. The categories that I’ve laid out initially–dated original term, dated Rubenstein term, mention of marginalized issues, mention of marginalized identity, downplaying bias (e.g. calling racism and discrimination an issue with “race relations”), dehumanization of marginalized people, false positive–only hope to serve as an entry point and rudimentary categorization of these nuances to begin this process.
Categorizing each of these instances of potentially harmful language remains a time-consuming, meticulous process. Although much of this work can be computerized, decolonization is a fundamentally human and fundamentally community-centered practice. No computer can dismantle the colonial, white supremacist narratives that archival work often upholds. This work requires our full attention and, for better or for worse, a lot of time, even with the productivity boost technology gives us.
Once categories have been established, at least on a preliminary level, I found that about 100-200 instances of potentially harmful language could be manually parsed and categorized in an hour.
Decolonization and anti-racist efforts in archival work are an ongoing process. It is bound to take active learning, reflection, and lots of remediation. However, using technology to start this process creates a much less daunting entry point. Anti-racism work is essential in archival spaces.
The ways we talk about history can either work to uphold traditional white supremacist, racist, ableist, etc. narratives, or they can work to dismantle them. In many ways, archival work has often upheld these narratives in the past, however this audit represents the sincere beginnings of work to further equitable narratives in the future.
On January 20, 2020, we kicked off our first development sprint for implementing ArcLight at Duke as our new finding aids / collection guides platform. We thought our project charter was solid: thorough, well-vetted, with a reasonable set of goals. In the plan was a roadmap identifying a July 1, 2020 launch date and a list of nineteen high-level requirements. There was nary a hint of an impending global pandemic that could upend absolutely everything.
The work wasn’t supposed to look like this, carried out by zooming virtually into each other’s living rooms every day. Code sessions and meetings now require navigating around child supervision shifts and schooling-from-home responsibilities. Our new young office-mates occasionally dance into view or within earshot during our calls. Still, we acknowledge and are grateful for the privilege afforded by this profession to continue to do our work remotely from safe distance.
So, a major shoutout is due to my colleagues in the trenches of this work overcoming the new unforeseen constraints around it, especially Noah Huffman, David Chandek-Stark, and Michael Daul. Our progress to date has only been possible through resilience, collaboration, and willingness to keep pushing ahead together.
Three months after we started the project, we remain on track for a summer 2020 launch.
As a reminder, we began with the core open-source ArcLight platform (demo available) and have been building extensions and modifications in our local application in order to accommodate Duke needs and preferences. With the caveat that there’ll be more changes coming over the next couple months before launch, I want to provide a summary of what we have been able to accomplish so far and some issues we have encountered along the way. Duke staff may access our demo app (IP-restricted) for an up-to-date look at our work in progress.
Featured Items. Built a configurable set of featured items from the collections (with captions), to be displayed randomly (actual selections still in progress).
Dynamic Content. Provided a live count of collections; we might add more indicators for types/counts of materials represented.
Sidebar. Replaced the single-column tabbed layout with a sidebar + main content area.
Persistent Collection Info. Made collection & component views more consistent; kept collection links (Summary, Background, etc.) visible/available from component pages.
Width. Widened the largest breakpoint. We wanted to make full use of the screen real estate, especially to make room for potentially lengthy sidebar text.
Hierarchical Navigation. Restyled & moved the hierarchical tree navigation into the sidebar. This worked well functionally in ArcLight core, but we felt it would be more effective as a navigational aid when presented beside rather than below the content.
Tooltips & Popovers. Provided some additional context on mouseovers for some navigational elements.
List Child Components. Added a direct-child list in the main content for any series or other component. This makes for a clear navigable table of what’s in the current series / folder / etc. Paginating it helps with performance in cases where we might have 1,000+ sibling components to load.
Breadcrumb Refactor. Emphasized the collection title. Kept some indentation, but aimed for page alignment/legibility plus a balance of emphasis between current component title and collection title.
“Group by Collection” as the default. Our stakeholders were confused by atomized components as search results outside of the context of their collections, so we tried to emphasize that context in the default search.
Revised search result display. Added keyword highlighting within result titles in Grouped or All view. Made Grouped results display checkboxes for bookmarking & digitized content indicators.
Advanced Search. Kept the global search box simple but added a modal Advanced search option that adds fielded search and some additional filters.
Digital Objects Integration
DAO Roles. Indexed the @role attribute for <dao> elements; we used that to call templates for different kinds of digital content
Embedded Object Viewers. Used the Duke Digital Repository’s embed feature, which renders <iframe>s for images and AV.
Whitespace compression. Added a step to the pipeline to remove extra whitespace before indexing. This seems to have slightly accelerated our time-to-index rather than slow it down.
More text, fewer strings. We encountered cases where note-like fields indexed as strings by ArcLight core (e.g., <scopecontent>) needed to be converted to text because we had more than 32,766 bytes of data (limit for strings) to put in them. In those cases, finding aids were failing to index.
Underscores. For the IDs that end up in a URL for a component, we added an underscore between the finding aid slug and the component ID. We felt these URLs would look cleaner and be better for SEO (our slugs often contain names).
Dates. Changed the date normalization rules (some dates were being omitted from indexing/display)
Bibliographic ID. We succeeded in indexing our bibliographic IDs from our EADs to power a collection-level Request button that leads a user to our homegrown requests system.
EAD -> HTML. We extended the EAD-to-HTML transformation rules for formatted elements to cover more cases (e.g., links like <extptr> & <extref> or other elements like <archref> & <indexentry>)
Formatting in Titles. We preserved bold or italic formatting in component titles.
ArcLight Core Contributions
We have been able to contribute some of our code back to the ArcLight core project to help out other adopters.
Setting the Stage
The behind-the-scenes foundational work deserves mention here — it represents some of the most complex and challenging aspects of the project. It makes the application development driving the changes I’ve shared above possible.
Gathered a diverse set of 40 representative sample EADs for testing
Dockerized our Duke ArcLight app to simplify developer environment setup
Provisioned a development/demo server for sharing progress with stakeholders
Automated continuous integration and deployment to servers using GitLabCI
Performed targeted data cleanup
Successfully got all 4,000 of our finding aids indexed in Solr on our demo server
Our team has accomplished a lot in three months, in large part due to the solid foundation the ArcLight core software provides. We’re benefiting from some amazing work done by many, many developers who have contributed their expertise and their code to the Blacklight and ArcLight codebases over the years. It has been a real pleasure to be able to build upon an open source engine– a notable contrast to our previous practice of developing everything in-house for finding aids discovery and access.
Still, much remains to be addressed before we can launch this summer.
The Road Ahead
Here’s a list of big things we still plan to tackle by July (other minor revisions/bugfixes will continue as well)…
ASpace -> ArcLight. We need a smoother publication pipeline to regularly get data from ArchivesSpace indexed into ArcLight.
Access & Use Statements. We need to revise the existing inheritance rules and make sure these statements are presented clearly. It’s especially important when materials are indeed restricted.
Relevance Ranking. We know we need to improve the ranking algorithm to ensure the most relevant results for a query appear first.
Analytics. We’ll set up some anonymized tracking to help monitor usage patterns and guide future design decisions.
Sitemap/SEO. It remains important that Google and other crawlers index the finding aids so they are discoverable via the open web.
Accessibility Testing / Optimization. We aim to comply with WCAG2.0 AA guidelines.
Single-Page View. Many of our stakeholders are accustomed to a single-page view of finding aids. There’s no such functionality baked into ArcLight, as its component-by-component views prioritize performance. We might end up providing a downloadable PDF document to meet this need.
More Data Cleanup. ArcLight’s feature set (especially around search/browse) reveals more places where we have suboptimal or inconsistent data lurking in our EADs.
More Community Contributions. We plan to submit more of our enhancements and bugfixes for consideration to be merged into the core ArcLight software.
If you’re a member of the Duke community, we encourage you toexplore our demo and provide feedback. To our fellow future ArcLight adopters, we would love to hear how your implementations or plans are shaping up, and identify any ways we might work together toward common goals.
It’s been just over a year since we launched our new catalog in January of 2019. Since then we’ve made improvements to features, performance, and reliability, have developed a long term governance and development strategy, and have plans for future features and enhancements.
During the Spring 2019 semester we experienced a number of outages of the Solr index that powers the new catalog. It proved to be both frustrating and difficult to track down the root cause of the outages. We took a number of measures to reduce the risk of bot traffic slowing down or crashing the index. A few of these measures include limiting facet paging to 50 pages and results paging to 250 pages, as well as setting limits on OpenSearch queries. We also added service monitoring so we are automatically alerted when things go awry and automatic restarts under some known bad system conditions. We also identified that a bug in the version of Solr we were running was vulnerable to causing crashes for queries with particular characteristics. We have since applied a patch to Solr to address this bug. Happily, the index has not crashed since we implemented these protective measures and bug fixes.
Over the past year we’ve made a number of other improvements to the catalog including:
Caching of the home page and advanced search page have reduced page load times by 75%.
Subject searches are now more precise and do not include stemmed terms.
CDs and DVDs can be searched by accession number.
When digitized copies of Duke material are available at the Internet Archive, links to the digital copy are automatically generated.
Records can be saved to a bookmarks list and shared with others via a stable URL.
Eligible records now have a “Request digitization” link.
Many other small improvements and bug fixes.
We sometimes get requests for features that the catalog already supports:
Anchor links for quick access to record metadata, and a jump to top link.
While development has slowed, the core TRLN team meets monthly to discuss and prioritize new features and fixes, and dedicates time each month to maintenance and new development. We have a number of small improvements and bug fixes in the works. One new feature we’re working on is adding a citation generator that will provide copyable citations in multiple formats (APA, MLA, Chicago, Harvard, and Turabian) for records with OCLC numbers.
We welcome, read, and respond to all feedback and feature requests that come to us through the catalog’s feedback form. Let us know what you think.
Here at Duke, the buzz continues around FOLIO. We have continued to contribute to the international project as active participants on the FOLIO Product Council, special interest groups, and contribute development resources. You can find links to the various groups on the FOLIO wiki.
We’ve also committed to implementing the electronic resource management (ERM)-focused apps in summer of 2020. Starting with the ERM-focused apps will give us the opportunity to use FOLIO in a production environment, and will be a benefit to our Continuing Resource Acquisitions Department since they are not currently using software dedicated to electronic resources to keep track of licences and terms.
Our local project planning has come more into focus as well. We have gathered names for team participants and will be kicking off our project teams in January. As we’ve talked about the implementation here, we’ve realized that we have a number of tasks that will need to be addressed, regardless of subject matter. For example, we’re going to need to map data – not just bibliographic, holdings and item data, but users, orders, invoices, etc. We’ll also need to set up configurations and user permissions for each of the apps, and document, train, and develop new workflows. Since our work is not siloed in functional areas, we need to facilitate discussions among the functional areas. To do that, we’re going to create a set of functional area implementation teams, and work groups around the task areas that need to be addressed.
To learn more about the FOLIO project at Duke, fly on over to our WordPress site and read through our past newsletters, look through slides from past presentations, and check out some fun links to bee facts.
Post contributed by Claire Cahoon, student in the master’s program at the School of Information and Library Science, UNC-Chapel Hill.
This summer I worked as a field experience student in the Software Services department migrating digital exhibits into Omeka 2, Duke’s most current platform. The ultimate goal was to start and document the process of moving exhibits from legacy platforms into Omeka 2.
The reasoning behind the project became clear as we started creating an index of all of the digital exhibits on display in the exhibits website. Out of 97 total exhibits, there were varying degrees of functionality, from the most recent and up-to-date exhibits, to sites with broken links and pages where only text would display, leaving out crucial images. Centralizing these into a single platform should make it easier to create, support, and maintain all of these exhibits.
I found exhibits in Omeka 1, Cascade, Scriptorium, JAlbum, and even found a few mystery platforms that we never identified. Since it was the largest, we decided to work on the Omeka 1 group over the summer, and this week I finished migrating all 34 exhibits – that means that after a few adjustments to make the new exhibits available, Omeka 1 can be shut off!
We worked with Meg Brown, Exhibits Coordinator for the Libraries, and the exhibits department to figure out how each exhibit needed to be represented. Since we were managing expectations from lots of different stakeholders, we landed on the idea to include a link to the archived version of each exhibit in the WayBack machine, in case the look and feel of the new exhibits is limiting for anyone used to Omeka 1.
Working with the internet archive links and sorting through broken pieces of these exhibits really put into perspective how impermanent the internet is, even for seemingly static information. Without much maintenance, these exhibits lost some of the core content when video links changed, references were lost, and even the most well-written custom code stopped working. I hope that my work this summer will help keep these exhibit materials in working order while also eliminating the need to continue supporting for Omeka 1.
While migrating, I came across a few favorite exhibits and items that combined interesting content and some updated features in Omeka 2:
Omeka still has some quirks to work out, and the accessibility of the pages and the metadata display are still in the works. However, migrating these exhibits into Omeka 2 will make them much easier to support and change for improvements. Thanks to the team that worked with me and taught me so much this summer: Will Sexton, Michael Daul, and Meg Brown!
Last week, it was brought to our attention that Duke Digital Collections recently passed 100,000 individual items found in the Duke Digital Repository! To celebrate, I want to highlight some of the most recent materials digitized and uploaded from our Section A project. In the past, Bitstreams has blogged about what Section A is and what it means, but it’s been a couple of years since that post, and a little refresher couldn’t hurt.
What is Section A?
In 2016, the staff of Rubenstein Research Services proposed a mass digitization project of Section A. This is the umbrella term for 175 boxes of different historic materials that users often request – manuscripts, correspondence, receipts, diaries, drawings, and more. These boxes contain around 3,900 small collections that all had their own workflows. Every box needs consultations from Rubenstein Research Services, review by Library Conservation Department staff, review by Technical Services, metadata updates, and more, all to make sure that the collections could be launched and hosted within the Duke Digital Repository.
In the 2 years since that blog post, so much has happened! The first 2 Section A collections had gone live as a sort of proof-of-concept, and as a way to define what the digitization project would be and what it would look like. We’ve added over 500 more collections from Section A since then. This somehow barely even scratches the surface of the entire project! We’re digitizing the collections in alphabetical order, and even after all the collections that have gone online, we are currently still only on the letter “C”!
Nonetheless, there is already plenty of materials to check out and enjoy. I was a student of history in college, so in this blog post, I want to particularly highlight some of the historic materials from the latter half of the 19th century.
Showing off some of Section A
In 1869, after her work as a nurse in the Civil War, Clara Barton traveled around Europe to Geneva, Switzerland and Corsica, France. Included in the Duke Digital Collections is her diary and calling cards from her time there. These pages detail where she visited and stayed throughout the year. She also wrote about her views on the different European countries, how Americans and Europeans compare, and more. Despite her storied career and her many travels that year, Miss Barton felt that “I have accomplished very little in a year”, and hoped that in 1870, she “may be accounted worthy once more to take my place among the workers of the world, either in my own country or in some other”.
Back in America, around 1900, the Rev. John Malachi Bowden began dictating and documenting his experiences as a Confederate soldier during the Civil War, one of many that a nurse like Miss Barton may have treated. Although Bowden says he was not necessarily a secessionist at the beginning of the Civil War, he joined the 2nd Georgia Regiment in August 1861 after Georgia had seceded. During his time in the regiment, he fought in the Battles of Fredericksburg, Gettysburg, Spotsylvania Court House, and more. In 1864, Union forced captured and held Bowden as a prisoner at Maryland’s Point Lookout Prison, where he describes in great detail what life was like as a POW before his eventual release. He writes that he was “so indignant at being in a Federal prison” that he refused to cut his hair. His hair eventually grew to be shoulder-length, “somewhat like Buffalo Bill’s.”
Speaking of whom, Duke Digital Collections also has some material from Buffalo Bill (William Frederick Cody), courtesy of the Section A initiative. A showman and entertainer who performed in cowboy shows throughout the latter half of the 19th century, Buffalo Bill was enormously popular wherever he went. In this collection, he writes to a Brother Miner about how he invited seventy-five of his “old Brothers” from Bedford, VA to visit him in Roanoke. There is also a brief itinerary of future shows throughout North Carolina and South Carolina. This includes a stop here in Durham, NC a few weeks after Bill wrote this letter.
Around this time, Walter Clark, associate justice of the North Carolina Supreme Court, began writing his own histories of North Carolina throughout the 18th and 19th centuries. Three of Clark’s articles prepared for the University Magazine of the University of North Carolina have been digitized as part of Section A. This includes an article entitled “North Carolina in War”, where he made note of the Generals from North Carolina engaged in every war up to that point. It’s possible that John Malachi Bowden was once on the battlefield alongside some of these generals mentioned in Clark’s writings. This type of synergy in our collection is what makes Section A so exciting to dive into.
As the new Still Image Digitization Specialist at the Duke Digital Production Center, seeing projects like this take off in such a spectacular way is near and dear to my heart. Even just the four collections I’ve highlighted here have been so informative. We still have so many more Section A boxes to digitize and host online. It’s so exciting to think of what we might find and what we’ll digitize for all the world to see. Our work never stops, so remember to stay updated on Duke Digital Collections to see some of these newly digitized collections as they become available.
The ongoing tensions between academic institutions and publishers have been escalating the last few months, but those tensions have existed for many years. The term “Big Deal” has been coined to describe a long-standing, industry-wide practice of journal bundling that forces libraries to subscribe to unwanted and unneeded publications rather than paying more for a limited number of individual subscriptions. This is a practice you see in other industries – for example, cable packages that provide hundreds of channels, even if you only want one or two specific channels.
What is especially problematic in higher education is that academics produce and review the content that gets published in the journals (for free), and then the universities have to pay the publishers a subscription fee to access the content. Imagine if YouTube required a subscription fee to watch any videos, including the ones you had posted. It’s a system that makes research harder to access and inhibits global scientific progress, all so publishers can earn an enormous profit margin.
Right now, academic publishing is controlled by five publishers (the “Big Five”) – a monopoly that makes it very difficult for libraries to negotiate better deals. Only very large organizations or consortia, like the University of California, have been able to start pushing back against the system. It will likely take large shake-ups like this for any large changes to take hold, but it in the meantime there may be ways to situate ourselves for making better purchasing decisions.
At Duke, we often review our usage of specific journal titles as we prepare to make purchasing decisions. Usage data comes in a variety of forms, but the most popular are counts of Duke views and downloads that come directly from the publishers and the number of times Duke authors publish in or cite a particular journal. There are many other kinds of data that might be of interest, however, including Duke participation on editorial boards, usage differences across disciplines, and even whether or not the journal is fully open access. Blending various data sources and optimizing the search decisions for a given budget cycle can be overwhelming.
Last fall, Duke University Libraries decided to propose a project for Duke’s Data+ summer program – a summer research experience in data science for undergraduate students. Our project, “Breaking the Bundle: Analyzing Duke’s Journal Subscriptions“, focuses on Duke’s subscriptions to journals published by Elsevier. The program is in its third week, and our team of two incredibly-sharp undergraduates has been hard at work building and blending our datasets. Our goal by the end of summer is to have a proof-of-concept dashboard that lets collection managers adjust the weights of various usage measures to generate an ideal collection of journals for a particular budget.
It is still very early in the process, but the students have been hard at work and have made great progress. We decided it would be best to develop the analysis software and dashboard using R, a statistical computing project with a rich history and many helpful development tools. In addition to publisher-provided views and downloads, the students have been able to use websites and APIs to collect data on journal open access status, editorial boards, numbers of publications, and numbers of citations. All Data+ teams present publicly on the projects twice during the summer, and we hope to schedule a third talk for a library audience before the end of the program on August 2.
We look forward to seeing what the summer will bring! While this project is just one small step, automating the collection and analysis of journal usage will position us well, both for responsible purchases and for a hopefully-changing publishing landscape.
Notes from the Duke University Libraries Digital Projects Team