The Great ILS-Data Pre-Conference: Quick Lessons With Your Peers

Conferences & Events IUG Conference 2026
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Program Title: The Great ILS-Data Pre-Conference: Quick Lessons With Your Peers

Track: General

Program Description: Ease your way into this year’s conference with our all-star assortment of IUG experts who will present a full afternoon of activities for those looking to expand their library data toolbox. Through a series of mini-talks, some speed geeking and lively conversations, attendees will have opportunities to learn about a wide range of techniques for working with both Sierra and Polaris data.

Individual Sessions

  • DASHboard Confessional: Revealing the secrets of data visualization

    In this quick session we’ll explore how to structure and manage data in order to create a variety of data visualizations and see plenty of examples of data dashboards that have been constructed for the Minuteman Library Network.

  • Vega Kiosks

  • Finding Signal in the Noise with Regex

    A fast, hands-on session on using regular expressions to spot patterns and transform messy text. See how regex skills can work everywhere—from command-line tools and text editors to MarcEdit—to search, clean, and reshape data.

  • From Create Lists to Action: Empowering Staff with API-Driven Micro-Projects

    Create Lists don’t have to stop at reporting. This speed-geeking session explores how curated lists can feed API-based scripts to safely delegate real work, such as patron address cleanup or fine removal for special cases, to staff. A fast, approachable model for extending capacity without building large systems.

  • I :heart: Datasette: A Tool for Exploring and Publishing (Library) Data

    Datasette is a free and open-source software platform designed by Simon Willison to make it easier to share and publish data. At the Cincinnati & Hamilton County Public Library I have been using Datasette in a variety of ways to help explore and share Library data in useful and meaningful ways that I’ll demo here.

  • Out Here in the Fields: Lessons Learned from a Different Database

    You may not believe this, but there is an entire world of library management systems outside professional librarianship, each with their own databases and schemas that bring their own pros and cons. And get this: None of them use MARC. I mean, can you imagine?! Let’s take a quick walk through a project that manages bibliographic data in a completely different way, and what we can take away from that.

  • Data Lakes/warehouses and storing data extracts

    Library data never sits still — and it lives in more places than you think. Records are added, deleted, and weeded every day. Digital resources are circulating outside your ILS, but there’s no easy way to connect physical and digital borrowing activity — making it hard to see your library’s full data landscape. What if you could capture structured snapshots at regular intervals in open formats that you own, not a vendor? This session introduces the data lake concept for libraries: using tools like DuckDB, DuckLake, and Apache Parquet to build an inexpensive, secure, lightweight, and versioned repository of your library data. We’ll look at early experiments at CHPL, including an open-source Sierra MARC harvester and an OverDrive checkout ETL, and discuss why data sovereignty matters for libraries planning ahead.

  • Putting Privacy First: Making Due with Less Data

    The Minuteman Library Network has historically taken a privacy first approach to its policies and data retention practices. We only store a month of circ transaction data in Sierra, take great caution with the data we share with other vendors and refuse to use a number of standard features such as linked patrons. Massachusetts is now on the verge of implementing a new data minimization focused privacy law that has had us looking at reducing data collection even further (do we really need patron addresses? Yes, but we thought about it). Come and hear how we are able to balance these considerations with our vast reporting needs and still manage to operate a successful consortia.

  • AMH Insights: Turning Log Files Into Actionable Data

    Automated Materials Handling (AMH) systems generate valuable operational data, much of which resides in plain-text log files that are rarely analyzed beyond troubleshooting. This ILS-agnostic lightning talk introduces a practical approach for extracting insights directly from AMH logs to better understand item flow, bin utilization, and system behavior.

    Using TechLogic as an example, while keeping the methodology applicable to other AMH vendors, the session outlines how libraries can automate the collection of AMH log files from the system’s main application computer and deliver them to a centralized location for analysis using common automation tools such as PowerShell and WinSCP. By examining this data over time, libraries can identify heavily used bins, uncover patterns in items routed to Exceptions, and use volume-based evidence to inform bin redistribution, mapping adjustments, and operational tuning, independently of the ILS.

  • Python Command Line Processing with argv[] and the argparse Module - Python’s argparse module makes it easy to write user-friendly command-line interfaces. The program defines what arguments it requires, and argparse will figure out how to parse those out of sys.argv. The argparse module automatically generates help and usage messages. The module will also issue errors when users give the program invalid arguments.

    In this session you’ll see an example of this module in action and how it can be utilized in a Python program which places holds on the items/bibs in a review file, a program with numerous required and optional arguments.

  • Thousands of Tables and Four Farthings: Hacking Your Way to a Better Report - In the midst of building a centralized data server, we ran into an issue with a report that the Finance Department had been running for years. Nothing was wrong with the report, the problem came about from the way they were running it. This new data server is going to need that report, but they’re not going to be able to run it the same way. Okay, so we’ll rebuild it. But first things first… where does the data come from, how is it pulled from the database, where is the report file, and how does it work?

    Time for a little old school tracking and hacking.

Speaker/ Information:

The materials, slide decks, and references can be found at the presentation’s Github repo.

1000s_of_Tables_and_4_Farthings.pptx (1.6 MB)
Dashboard_Confessional_with_template.pptx (5.1 MB)
Out_Here_in_the_Fields-Slide_Deck.pptx (7.0 MB)
Pre-conference_Vega_Kiosk-IUG_2026.pptx (816.5 KB)
Putting_Privacy_First_with_template.pptx (3.9 MB)
The_Great_ILS-Data_Pre-Conference.pptx (7.7 MB)