This practical session covers how Clemson University Libraries’ metadata team describes their largest digital collection of historical images. It focuses on what the team has learned from this project thus far. This includes developing workflows and strategies for describing images, creating and using a controlled vocabulary of local headings, and leveraging expertise across the libraries to streamline metadata creation. The team walks through the metadata management tool CollectiveAccess, shares image examples from the collection, and discusses the benefits of metadata documentation. The team concludes with challenges they still face, such as selecting appropriate subject headings, managing entities, and describing images with little to no...
Libraries, archives and museums (LAMs) have been creating metadata of various types (catalog records...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
Are you flooded with files? Drowning in data? Swimming in spreadsheets? Just add metadata! Doing res...
This practical session covers how Clemson University Libraries’ metadata team describes their larges...
This practical session covers how Clemson University Libraries’ metadata team describes their larges...
Libraries are at the forefront of creating rich quality metadata to ensure a future where communitie...
Libraries are at the forefront of creating rich quality metadata to ensure communities can access, l...
This chapter describes the issues confronted along the “road taken” by a technical services team as ...
Slides from a presentation on metadata basics for library projects. Delivered October 6, 2011 at the...
The COVID-19 pandemic and the resulting shift to working from home (WFH) and online education proved...
Acquisition of unique digital material is an ongoing challenge for Special Collections units—often u...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This presentation was developed to help train student employees on metadata protocols implemented at...
Libraries, archives and museums (LAMs) have been creating metadata of various types (catalog records...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
Are you flooded with files? Drowning in data? Swimming in spreadsheets? Just add metadata! Doing res...
This practical session covers how Clemson University Libraries’ metadata team describes their larges...
This practical session covers how Clemson University Libraries’ metadata team describes their larges...
Libraries are at the forefront of creating rich quality metadata to ensure a future where communitie...
Libraries are at the forefront of creating rich quality metadata to ensure communities can access, l...
This chapter describes the issues confronted along the “road taken” by a technical services team as ...
Slides from a presentation on metadata basics for library projects. Delivered October 6, 2011 at the...
The COVID-19 pandemic and the resulting shift to working from home (WFH) and online education proved...
Acquisition of unique digital material is an ongoing challenge for Special Collections units—often u...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
This presentation was developed to help train student employees on metadata protocols implemented at...
Libraries, archives and museums (LAMs) have been creating metadata of various types (catalog records...
This paper describes the process developed by Binghamton University Libraries to extract embedded me...
Are you flooded with files? Drowning in data? Swimming in spreadsheets? Just add metadata! Doing res...