2. We often forget about legacy data or de-prioritize the impact of changes in data management practices. RDA brought about many data changes. While most of those are not significant as they do not deal with formatting of data, some do change the expectation for data.
https://twitter.com/georgiawebgurl/status/1592215750000918528
3. Any variation in expected data (e.g., 260 vs. 264) can cause issues. An 007/008 expectation for media or 336-338 fields which may not appear in older records. You can't build facets and search parameters on what doesn't exist.
4. Other changes in practice impact #ILS migration, too, such as the preference of a single record for all formats. That really was a workaround for ILS who couldn't aggregate or FRBRize data displays for formats. #migration #systems #data #metadata #cataloging #ILS
5. ILS specific functionalities (or lack of) that required changes to MARC standards or do not matching the new system. If your ILS didn't support holding records, then what happens when you migrate to a system that does? (They are often erroneously created on the fly). #ils
6. Poor data management practices, especially in regards to data maintenance & cleanup. Data is often provided, ingested in bulk, or outsourced for cleanup without any oversight. Even something simple like deduping records can get missed. #lls #migration #systems #data
7. Data is not static. Instead, much like the larger web, our data is dynamic. Our systems change. Our practices change. Our controlled vocabularies change. Yet, some libraries do ALMOST no data management which then leads to huge data issues uncovered at system migration. #ils
8. All of these factors collide at system migration. Data management practices, for better or worse, are exposed. Data is exposed. Quality control (or the lack of QC) is exposed. Changes in practice are exposed. Staff training needs are often exposed (patterns of errors).
9. An often unspoken part of system migration is the impact of the data reveal - this it is a great time to review workflows; make better and more informed decisions about good data management practices going forward. #ils #cataloging #metadata #listwitter #data #cataloging
10. Use what you find in #ILS or #repository #archives #system #migrations to make a case for better resources including staffing & training. Identify training needs uncovered in the migration. Write a data management plan for your library.
11. The data that #catalogers & #metadata folks create is the language in which we speak to patrons. We may or may not work directly with patrons, but OUR data is what makes search work. If our data is garbage (for whatever reason), that makes findabililty more challenging.
12. AI can help us. Linked data can help us. However, we have to be able to work with our systems. We need to advocate for good #data management practices and quality control of #metadata. Because when we don't, it rarely happens and that impacts our end users. #ils #migration
13. I used to blog topics like this in a galaxy far, far away (academia), so if you found this interesting, please let me know. Also, don't forget you can connect with me on linkedin. Be safe. Be well. Never stress over an ILS migration! linkedin.com/in/robinfay/
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