The Williams College Museum of Art Collection has many different labelling systems that are inconsistent with each other, therefore the tool OpenRefine is incredibly useful. OpenRefine’s data filtering capacity is intuitive using such parts as faceting by date, or by number.
Using a facet that filters out blank entries, we can distinguish what artwork have images attached. Using the facet for Words, we can filter by department to filter out items that do not have a clear label regarding their designation and usability in an image analysis. I have been unable to clearly map entries based on accession date, due to the abnormal methods of numbering. It would be fascinating to compare creation dates to aquisition dates. Using Starring, it is possible to filter the dataset multiple times which I have found incredibly useful, however I have found it difficult to apply more than about three filters based on this method.