Revision as of 00:30, 25 October 2018

Code4Lib Montreal 2018-10-23

Attendees

• Chris Trudeau - recent McGill SIS graduate
• Martin ?? - Health Sciences liaison, McGill
• Stephana Bretweiser - CCA
• Tim Walsh - Digital Preservation librarian, Concordia
• John ?? - Digital Archivist, Concordia
• Clara Turp - Metadata Analyst Librarian, McGill
• Jessica Reeve - Senior Electronic Resources
• Tomasz Langenbauer - Digital Projects, Concordia
• Rebecca Nicholson - Web group, McGill
• Eka Grigorik - Web Librarian, McGill
• Dan Scott - Systems librarian, Laurentian / McGill student

Mandat du groupe et description / Group's description and mandate

Brief discussion about what the mandate of the group should be:

• Learning about technology and coding through doing; workshops
• Building a community - across universities, colleges, public institutions in Montreal
• Informal

We like https://code4lib.org/about

• Action Clara will customize the Code4Lib statement, ensuring it reflects a Montreal & bilingual context

Presentations

Sarah Severson: sick, will present conference report from DLF next time

Chris Trudeau: citations to reserves

Idea: instead of faculty emailing the library with their individual requests for items that need to be placed on reserve, why not extract the citations from the course outline / syllabus (in PDF or Word format) and automatically generate reserve requests?

Feedback

• McGill used to have faculty upload syllabi, but eventually stopped because of resistance ("private information")
• McGill accepts reserve requests in any format: email, in person, paper
• Tomasz built something like this for Concordia in 2009 and is willing to share it; but faculty wanted the ability to submit the entire syllabus; or paste in a full citation; or fill out the parts field-by-field

Tim Walsh, Bulk Reviewer

Identifies, reviews, and removes sensitive files in disk images and directories, regardless of file format Sensitive info - SSN, credit card numbers, phone numbers, email addresses, internet history, EXIF metadata, GPS data, custom search terms, Windows registry (program install history) Built using Django, Vue.js, bulk_extractor, DFXML, and Docker bulk_extractor generates text files or a SQLite database that normally gets processed into a histogram; this processes the data to instead support a Web browser front end and identify the individual files that may be problematic Problems: Many false positives (e.g. all 9 digit numbers are identified as SSNs); Tim isn't sure any of these tools have a high level of confidence Tooling is all American-based, so adding something like a SIN requires C++ (Tomasz is willing to help!)

Next meeting

• November - Sarah and John to present
• Mid-December - social