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Notes on the UMLS Semantic Network

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UMLS Semantic Network

This was a really interesting reading. Not interesting like a novel or movie, of course, but interesting because I keep hearing about semantic webs without seeing any worthwhile examples.

One thing I was a little surprised to see was the ASCII codes for creating a flat-file database. I would have through they would have either specified it in XML or something a little more modern. And I kind of cringe whenever I hear anyone call an ASCII file a database. Even though it’s technically true, to me ‘database’ means database management system (DBMS), with some mechanisms put into place to allow multiple users, referential integrity, etc. If everything is stored in ASCII files, than any idiot can ruin the whole system and it’s really, really easy to let data get corrupted. You have to do all sorts of extra work to make sure updates to one field cascade through the rest of the file.

Even through this was designed specifically for the medical field, it’s surprising how much their relationships and semantic types could be useful for almost any semantic web. I could only think of a few relationships that were missing, the chief one being requires. This is a relationship that’s very common in computer science, but I think it might apply fairly often in other fields as well. When and entity requires another it cannot exist without it. It’s kind of a mix between part_of and precedes.

Notes on “Vocabulary as a central concept in Information Science” and additional readings

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Vocabulary as a Central Concept in Information Science, Michael Buckland (1999)

The role of classification in knowledge representation and discovery, BH Kwasnik – Library Trends, 1999

 

One good point in the Buckland article was that vocabulary can differ between those who are doing the cataloging, the authors and the searcher, even if everyone is within the same field. I’ve read some about these differences before, but they almost always seem to take the form of novice searcher vocabulary vs. expert author vocabulary or natural searcher vocabulary vs. structured system vocab. Those are probably the most clear ways to look at these distinctions—to tell you the truth looking at subtle differences between five different vocabularies does not seem like that much fun to me.

This article gets back to some of the same points we’ve already discussed in class when talking about synonym rings and taxnomies. Even through the author comes at it from a vocabulary point of view, he’s saying the same things everyone else is. If your users want to search for “Vietnam War” but your system uses “Vietnam Conflict,” without pointing the user in the right direction, no purpose has been served. You can be as correct and specific in your phrasing as you want but that’s no guarantee you’ll have a usable system.

The Kwasinik reading was really good at pointing out the strengths and weaknesses of hierarchies, trees and other organization schemes. In doing the AG assignment I ran into the “Lack of complete and comprehensive knowledge” barrier quite often. That’s one of the biggest problems with not just hierarchies, but any project like this where we have some knowledge of the domain—everyone has seen greeting cards—but not of the entire body of AG’s product line or even a representative subset. I wouldn’t want to construct a taxonomy of content object before people started entering data—I would have it be built as the database grew, with specific people in charge of keeping it consistent.

Knowledge Organization System for a Greeting Card Company’s Design Studio Archives

Academic Papers, Projects, , , , , ,

Note: this was a project for a graduate course in Knowledge Organization Systems

Introduction

The goal of this project is to create a Knowledge Organization System (KOS) for a Greeting Card Company Studio archive so that designers are able to find source artwork and previous designs. This is no small task–Greeting Card Company has been in operation for nearly 100 years and has at least partial archives from the entire period, and today the company employs hundreds of designers and produces thousands of products. There is no question that without an inclusive, accurate, and easy-to-use archive, designers are unable to build on each others ideas and a great deal of work is being duplicated. Also, intellectual property needs to be properly managed and licensed artwork needs to be tracked and protected from accidental misuse.

Currently, all archives are stored in protective containers in the Studio, shelved by year. In addition a vast number of digital files have been compiled on the Studio’s serves and CD and tape backups. This project does not address the physical process of collection and digitization, but instead offers a road map to how items will be classified as they are entered into the system. This KOS also provides a framework for the database and the ultimate user interface.

Below is an analysis of the users and groups, followed by a description of the overall structure of the KOS. After that is a description of each facet, followed by pick lists, synonym rings, and taxonomies for each where applicable.

 

Users

In this analysis three distinct user groups were identified: Archivists, Designers, and Management/Administration. Archivists include the companies current information professionals as well as the interns and temp workers who will be doing the digitization and data entry under their supervision. The KOS has been set up under the assumption that most data entry personnel will be able to properly classify perhaps 80 to 90 percent of all items within each facet, forwarding the rest to more skilled information professionals. The professionals include skilled librarians, art historians, and other researchers who should be adequately prepared to train data entry personnel and classify more difficult items.

The designer group includes artists and graphic designers of varying skill and experience. Nearly all, however, have completed at least a two-year program and the majority have completed a four-year college degree. Taxonomies were developed with this level of expertise in mind. Designers were surveyed and a wide range of thinking about art objects and designs were found. The facets below were designed to cover virtually every way in which a designer might want to look for a piece.

Management and administration also have specific needs. It is for them primarily that the Designer entity described below as well as most facets dealing with licensing and sales have been created.

 

Organization

The archive needs to be broken down into four different logical entities: Art Elements (such as clip art, photographs, sculptures, etc.), Products (such as individual greeting cards, e-cards, etc.), Digital Files, and Designers. Each entity will have a number of associated facets which roughly correspond to the fields in the database and will allow multiple methods of search and organization.

The entity relationships will be defined in the database so that searches will cascade upward. For example, some searching for art elements will be able to find those done by a specific AG department, because Art Elements are related to products which are related to Designers, who have the Department/Team facet. All of this is relatively simple to do with SQL and can be hidden in the interface to make searching easier.

Each facet has an associated type, whether that be a simple constraint on an open text field, a pick list, or a taxonomy. Where lists and taxonomies have been developed the list’s page number is noted as well.

View the KOS, including the entities and their facets, pick lists, and taxonomies [pdf]