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Ice cream, Binaries, and Maybes

· 6 min read
Jingyi Long
LINCS Undergraduate Research Assistant

In my first meeting this summer as a data science research assistant, we each followed our personal introductions with declarations of our favourite ice cream flavours. Mine was and continues to be Häagen Dazs’ Strawberry Cheesecake ice cream, and I was pleasantly surprised to learn someone else on the team felt the same. However, the biggest surprise was learning that someone enjoyed microwaving their ice cream to change its texture. At that point is it still ice cream? Is it soup? Or a milkshake? What even counts as ice cream? ...

Jessica and Goliath: Learning 3M and CIDOC CRM

· 6 min read
Ze Xi (Jessica) Ye
LINCS Metadata Co-op

During my graduate courses in the Faculty of Information at the University of Toronto, I gained a high-level understanding of Linked Open Data (LOD) and the CIDOC CRM ontology, a theoretical and practical tool for information integration in the field of cultural heritage. Because I am an Archives & Records Management student, I never expected to understand LOD and CIDOC CRM to a significant degree, and certainly not to the degree that my position as a Metadata Specialist co-op at LINCS requires of me...

The “Good Enough” Metadata Specialist

· 4 min read
Emily McKibbon
LINCS Metadata Co-op

My first job in the museums field was in 2008, right at the height of the Great Recession. The digitization team I joined had just lost roughly a quarter of their staff in a series of buyouts and layoffs, and the mood was grim. We were tasked with getting a large collection of historic photographs online, and the sooner the better—the only rub was that the collection wasn’t fully catalogued, and doing so properly would take time that we did not have. The pressure was on to justify our jobs, and so the discussions we had about metadata leaned towards the provisional. If the database is unpopulated, does just the accession number suffice? Okay, what about the accession number and artist? The solutions we came up with reflected the stressors of that moment: we aimed for something good enough in lieu of something exemplary, carefully balancing data requirements with the drive to generate content.

For the next decade and a half or so, Winnicott’s “good enough” parent has been a guiding principle in my role as a data custodian...

What Is Extract Transform Load?

· 4 min read
Justin Francis
LINCS Junior Programmer

In data science there is a commonly used process called Extract-Transform-Load (ETL). ETL involves three main steps:

  1. Extract data from a source,
  2. Transform the data via data cleansing and data manipulation, and
  3. Load the transformed data to a data warehouse (the final collection of data) (Sethi, 2018)

Before having much experience in data processing, my colleague Devon and I were not sure what ETL was. Now, after jointly transforming an entire dataset from XML to a whole new structure utilizing triples using CIDOC CRM, we’re beginning to understand the process...

Creating Opportunities: Working Remotely with Canadian Art Collections

· 7 min read
Sarah Moussseau
LINCS Undergraduate Research Assistant

In the summer of 2020, I was hired as a research assistant with the University of Guelph’s Bachinski/Chu Print Study Collection. Initially, my job entailed the care and maintenance of the objects in the collection with a few other tasks as assigned. Of course, the arrival of the COVID-19 pandemic meant that I spent the entire summer not working with the objects themselves, but rather doing deep research from home, using whatever online sources I could find. This proved to be challenging because while the collection boasts objects from a variety of dates and creators, it is largely made up of the works of mid-to-late twentieth-century Canadian printmakers who have a limited online presence...

Breaking Down Barriers to Data Conversion

· 5 min read
Devon Hayley Farrell
LINCS Metadata Co-op

If there’s one thing I have learned during my library, archival, and information graduate studies, it is that information institutions are adverse to change. The archival profession progresses at a glacial pace. This is juxtaposed with the leaps and bounds made in information technology over the past twenty-five years. At first glance, it doesn’t make sense why many libraries are still using the antiquated MARC format for their bibliographic records, or why archival institutions in Canada are still mandated to use the 2008 release of Rules for Archival Description, which doesn’t have any real solution for describing electronic records...