Metadata Crosswalking/ Transforming and Federated Searching in Ex Libris Products

Anthony DellureficioLibrary Systems ManagerThe New School Universitydellurea@newschool.edu

Goals of this Presentation Define the role of crosswalks in

federated searching Identify the problems created by

crosswalks Explore possible solutions to these

problems Draw conclusions about how to

structure metadata and improve federated searches

What is a “Crosswalk”?

Federated searches can incorporate many different types of metadata

Crosswalks map descriptive metadata into a uniform schema

The Issue with Federated Searching

Increased recall by adding collections Decreased precision due mismatching

data fields

Crosswalks offer a good solution but they are not ideal and they need tweaking

Related Products

ExLibris products which gather data from multiple sources (Primo, Digitool, SFX, Metalib, URM)

Products which supply data (Aleph) Integrated products which gather

ExLibris data (Xerxes, Umlaut) Any other products that contribute or

gather data

What metadata is crosswalked?

Descriptive metadata

Schemata: MARC, DC, EAD, etc. Sources: vendor data, locally created

descriptive data, harvested data (OAI), public databases

Crosswalks in Ex Libris

Table which defines all fields Table of indexed fields Table of search fields Table of display fields Map between field codes and

standard fields

Why are crosswalks inadequate?

Not all metadata has an equivalent in another schema

Differing levels of specificity Lumping metadata Many standards

Options

Alter different aspects of the structure:

Data structure Search structure Metadata structure Interpretation of data

Data Structure

Ex. Original cataloging

Pros: total institutional control of data

Cons: conform to standards?, time consuming

Search Structure

Ex. Adding database discovery pages

Pros: options for more sophisticated researchers, able to search more specific data

Cons: messy website, confusing to have multiple search pages

Metadata Structure

Ex. Parse and lump crosswalk fields

Pros: adds more access points, customized to specific collection

Cons: conforms to standards?, hierarchy problems, slow searches

Interpretation of Data

Better search paradigm Pros: more human, addresses actual

problem of data interpretation, not a “work-around”

Cons: requires programming and special knowledge

Remaining Problems

Metadata MUST be good! Access to table files (may need dev

box) Staff and time to alter metadata May be constrained by old

system/structure/data

Conclusions

Part of an overall metadata strategy No single solution Each institution must know its patrons

and how they search Increased transforming results in

increased data loss