Competency G

Demonstrate understanding of basic principles and standards involved in organizing information such as classification and controlled vocabulary systems, cataloging systems, metadata schemas or other systems for making information accessible to a particular clientele.

Section 1: Introduction

Organizing information is governed by several different types of metadata standards working together, each solving a distinct problem. The National Information Standards Organization (NISO) (2007) offers a useful typology, distinguishing data structure standards, the “categories” or “containers” that make up a record, from data value standards, the actual controlled terms and names used to populate those containers, from data content standards, the rules governing how those values should be formatted, and from data format or technical interchange standards, the machine-readable encoding that makes a given structure usable by computer systems. MARC and Dublin Core are examples of the first category; the Library of Congress Subject Headings (LCSH) is an example of the second; RDA is an example of the third; and MODS and METS are examples of the fourth. A well-organized information system is the product of several different kinds of standards, working at different levels, that function correctly together.

Data value standards, the standards that define controlled vocabularies, deserve particular attention, since they determine whether two different catalogers, or two different institutions, describe the same concept in the same way. Miller (2021) distinguishes between several types of controlled vocabularies, including authority files, which establish one preferred form for a name or concept, and thesauri, which map broader, narrower, and related relationships between terms, each suited to different organizational needs. Properly applying an established vocabulary like LCSH requires selecting a shared, previously established form so that a search for one heading reliably allows related materials to be returned.

Even given shared vocabularies, though, institutions rarely all use the same data structure standard, which raises a separate problem: interoperability. Zeng and Qin (2016) define interoperability as the capacity for different systems to exchange data with minimal loss of content and meaning, and they distinguish between syntactic interoperability, whether data formats and encodings are even compatible, and the harder problem of semantic interoperability, whether the actual meaning of the data survives the exchange. Converting a record from one schema to another through crosswalks, like from MARC to MODS, isn’t just a technical exercise in relabeling fields; it requires understanding what aspect of a described material each field in the original standard is actually trying to capture, so that the corresponding field in the new standard retains as close to the same meaning as possible. Apart from crosswalks, another tool for increasing interoperability is the creation and publication of metadata application profiles, sets of rules customized for a particular institution and its users, that can be adapted for use by similar institutions. Metadata application profiles specify which fields are mandatory and which are optional, enforce particular controlled vocabularies or value standards for particular fields, and enable automated validation by digital tools, reducing human error.

The judgment calls involved in assigning metadata and applying standards are what I enjoy most about this work. Organizing information is rarely just mechanically applying a rule; it is a kind of detective work in reverse. A detective pieces together clues to understand what happened, while an archivist must examine incomplete or ambiguous evidence and then arrange and describe it so that a future researcher can piece together what they need to know. In my current internship at the Santa Monica College Archives, I sort photographs into a preexisting schema, which constantly raises questions: a photo of students walking past a brightly colored building could reasonably go under Facilities, if the subject is really the building, or under Student Affairs, if the subject is actually the students and the building is just the setting for their activity. Should a photo of an identified professor teaching several students outdoors go into the professor’s file, or into the file for the academic department where he taught? If I find several photographs in an unlabeled envelope but they depict different subjects, do I divide them up, or keep them together to adhere to original order? With few detailed guidelines or policies for this budding archive, there is rarely one obviously correct answer. In order to make these types of calls, I must imagine how future researchers might search for these items or their digital surrogates, without knowing their needs in advance. Making these decisions requires working with several aspects of metadata at once: understanding which data standard governs which part of an organizational system, applying established data values correctly, and translating metadata between different data structures while maintaining findability and meaning. The evidence that follows reflects these principles applied to both physical and digital materials.

References

Section 2: Evidence

My understanding of organizing information comes from two dedicated courses, Beginning Cataloging and Classification (INFO 248), and Metadata (INFO 281), spanning original record creation, standards translation, and systematic evaluation of an existing digital library’s metadata implementation.

My first piece of evidence is a set of fifteen original MARC records I created for INFO 248, using books from my personal collection. I created and recorded fields for main entry, statement of responsibility, publication and physical description, applied RDA content, media, and carrier typing, and assigned Library of Congress Subject Headings, verified against their official authority record numbers. Cataloging these records required interpretive judgment: for one item, a translated illustrated religious text with no clearly identifiable author, I decided to use a title main entry rather than a personal name main entry. Neither RDA nor the record’s own title page gave any basis for treating an individual as primarily responsible for the work. This artifact demonstrates my ability to apply an official cataloging standard correctly to textual materials, including recognizing which of that standard’s rules apply to a given item.

My second piece of evidence is a Dublin Core metadata record I created for INFO 281, describing a 1942 Civilian Exclusion Order connected to the forced removal and internment of Japanese Americans, held in a university special collections archive. I used the Advanced Dublin Core Generator, a tool that provides a structured input form and converts selected values into properly formatted XML output, but the tool only handles formatting: I was responsible for researching the item and making substantive decisions about its description, including searching and selecting the correct Library of Congress Subject Headings, formatting the creation date to W3CDTF standards, and choosing isFormatOf and isPartOf relationship elements to correctly distinguish the digital surrogate from both its physical original and its place within a larger finding aid and collection.

I also completed a related exercise using this same skill in the opposite direction: using a worksheet that paired an Oregon Digital repository record’s own local field labels with their Dublin Core equivalents, I mapped ten local fields to the correct DC element and recorded each value, including recognizing correspondences that weren’t obvious from the labels alone. For example, I realized that the repository’s “Media” field corresponded to Dublin Core’s “Format” element, which I recorded as the MIME type “application/pdf,” and its “Submission Date” and “Date” fields corresponded respectively to DC’s “Date” and “Coverage” (temporal) elements, which distinguish between when an item was digitized and when the original historical object was actually created. This confirmed that I could recognize Dublin Core being applied within another institution’s locally customized system, untangling which of its labels mapped directly onto DC elements and which reflected separate, institution-specific description needs.

My third piece of evidence is a MARC-to-MODS crosswalk I completed for INFO 281, hand-encoding a MODS 3.6 record in XML based on an existing MARC record for a digital object, by referencing Library of Congress documentation, rather than an automated conversion tool. This required understanding what information each MARC field is intended to capture, so that the corresponding MODS element preserved the same meaning: for instance, I mapped MARC’s 506 restrictions-on-access note into a MODS accessCondition element, and used MODS’s relatedItem structure to represent the item’s relationship to both its archival finding aid and its physical box-and-folder location, two distinct relationships MARC would typically include in separate fields instead of a single element. This artifact demonstrates the kind of interoperability work Zeng and Qin (2016) describe, requiring semantic understanding of two different data structure standards well enough to move information between them while minimizing loss of meaning.

My fourth piece of evidence is a metadata evaluation exercise from INFO 281, in which I systematically assessed an existing digital library’s implementation of descriptive, administrative, technical/preservation, rights, use, and structural metadata for a digitized manuscript collection. Applying this framework revealed genuine gaps alongside notable strengths: the collection provided rich descriptive and structural metadata, including page-turning navigation through an International Image Interoperability Framework (IIIF) manifest (a widely adopted de facto standard for interoperable image delivery and presentation) and direct links to download records in MARC and Dublin Core formats. However, technical and preservation metadata was only partially present, with no documentation of scanning resolution or description of the digitization process itself. This exercise shows how I evaluated an existing metadata implementation critically, using a systematic framework.

Section 3: Conclusion

These four pieces reflect how organizing information is a multidimensional skill: I am able to create original records according to an established standard, translate a record between two different standards without losing its meaning, and evaluate an existing implementation critically enough to identify information that could be represented more fully. Across these examples, I apply standards not only to create technically correct metadata, but to make information more accessible to users: consistent names and subjects improve discovery, structured relationships help users understand context, interoperable schemas allow information to move between systems, and evaluation identifies metadata gaps that could prevent users from finding or using materials. In my future career, I intend to continue to approach cataloging and metadata work as the kind of detective work in reverse I described earlier, always asking not just what rule technically applies, but what a future researcher would actually need in order to find and understand a given item. To stay current in this area, I plan to follow the Library of Congress’s ongoing revisions to standards like BIBFRAME, MARC, and MODS and to consult the Digital Library Federation’s metadata assessment working group and related resources, keeping up with how standards and professional practices continue to evolve in institutional settings.