

mark e. phillips journal

mark e. phillips journal
	Metadata Events System: Accounting for Time
In the last post, I mentioned that there four primary things that we have needed in order to move a large portion of our student and staff workers to full remote work during this quarantine. In this post, I wanted to jump ahead a bit and talk a bit about how we are accounting for [&#8230;]
	Managing Metadata Editing for Telecommuting.
Many of us in the US, and around the world for that matter, are now sitting at home working remotely trying to maintain some semblance of normalcy during quarantine for COVID-19. I&#8217;m going to write up a few of the things that we have been working on her at the UNT Libraries to try and [&#8230;]
	User Session Analysis: UNT Scholarly Works
This is a continuation of a series of posts that I never got around to writing earlier this semester.  I posted the first and second post in the series in February but never got around to writing the rest of them.  This time I am looking at if users use items from multiple collections in [&#8230;]
	Introducing Sampling and New Algorithms to the Clustering Dashboard
One of the things that we were excited about when we adding the Clustering Dashboard to the UNT Libraries&#8217; Edit system was the ability to experiment with new algorithms for grouping or clustering metadata values.  I gave a rundown of the Cluster Dashboard in a previous blog post  This post is going to walk through [&#8230;]
	User Session Analysis: Investigating Sessions
In the previous post in this series I laid out the work that we were going to do with session data from the UNT Libraries&#8217; Digital Collections.  In order to get the background that this post builds from take a quick look at that post. In this post we are going to look at the [&#8230;]
	User Session Analysis: Connections Between Collections, Type, Institutions
I&#8217;ve been putting off some analysis that a few of us at the UNT Libraries have wanted to do with the log files of the UNT Libraries Digital Collections.  This post (and probably a short series to follow) is an effort to get back on track. There are three systems that we use to provide [&#8230;]
	Metadata Quality Interfaces: Cluster Dashboard (OpenRefine Clustering Baked Right In)
This is the last of the updates from our summer&#8217;s activities in creating new metadata interfaces for the UNT Libraries Digital Collections.  If you are interested in the others in this series you can view the past few posts on this blog where I talk about our facet, count, search, and item interfaces. This time [&#8230;]
	Metadata Interfaces: Search Dashboard
This is the next blog post in a series that discusses some of the metadata interfaces that we have been working on improving over the summer for the UNT Libraries Digital Collections.  You can catch up on those posts about our Item Views, Facet Dashboard, and Element Count Dashboard if you are curious. In this [&#8230;]
	Metadata Quality Interfaces: Element Count Dashboard
Next up in our review of the new metadata quality interfaces we have implemented this summer is our Element Count Dashboard. The basics of this are that whenever we index metadata records in our Solr index we go ahead and count the number of instances of a given element, or a given element with a [&#8230;]
	Metadata Quality Interfaces: Facet Dashboard
This is the second post in a series that discusses the new metadata interfaces we have been developing for the UNT Libraries&#8217; Digital Collections metadata editing environment. The previous post was related to the item views that we have created. This post discusses our facet dashboard in a bit of depth.  Let&#8217;s get started. Facet Dashboard [&#8230;]