Competency E: Design, query, and evaluate information retrieval systems;
Introduction
Every day, people interact with information retrieval systems, often without realizing it or understanding what they are. Whether searching for a book through a library catalog or entering a question into an online search engine, we rely on these systems to connect us with the knowledge we need. However, finding information is far more complicated than simply entering a few words into a search bar. Behind every search is a system designed to organize, interpret, and retrieve information based on a set of rules and processes designed by information professionals like ourselves. The decisions made in designing these systems can significantly influence how effectively users can find what they need, the type of information they can find, and whether the results are relevant to their search.
Competency E asks us to demonstrate our ability to design, query, and evaluate information retrieval systems. As information professionals, these systems make up the building blocks of our work, allowing us to organize vast amounts of information and make it accessible to our patrons. Understanding how these systems are designed, how to effectively search within them, and how to evaluate their effectiveness is essential to ensuring that users can access the information they need.
Designing Information Retrieval Systems
Information retrieval systems are designed to help users locate relevant information within a larger collection of materials. These systems can take many forms, including library catalogs, academic databases, digital repositories, and search engines. According to Manning et al. (2008), information retrieval involves organizing and indexing information so that relevant materials can be identified and retrieved in response to a user’s search. The design of these systems involves decisions about how information is categorized, described, and presented, all of which can influence a user’s ability to locate the resources they need.
One of the most important aspects of designing an information retrieval system is establishing how resources will be described and organized. Metadata provides descriptive attributes, such as titles, authors, subjects, and publication dates, that allow resources to be identified and retrieved. Riley (2017) emphasizes the importance of metadata in making information discoverable. Controlled vocabularies also support consistency by establishing standardized terms for describing subjects, while disambiguation helps distinguish between terms or names that may have multiple meanings. Another important consideration is the distinction between precoordination and postcoordination. Precoordination involves combining concepts into established subject headings before a search takes place, while postcoordination allows users to combine individual concepts during the search process. These principles influence how information is indexed and how effectively users can retrieve relevant materials.
This demonstrates why designing information retrieval systems requires more than simply organizing materials. Information professionals must also consider how users approach their searches, what terminology they are familiar with, and whether the systems they develop create unnecessary barriers to accessing information.
Querying Information Retrieval Systems
While the design of an information retrieval system determines how information can be found, querying involves developing effective strategies to locate that information. The Association of College and Research Libraries, or ACRL, identifies searching as a process of strategic exploration, emphasizing that research often requires users to reconsider their search terms, explore different resources, and adjust their approaches as they develop a better understanding of their topic (2026).
Effective searching requires an understanding of how different systems interpret queries. Boolean operators such as AND, OR, and NOT allow users to combine, broaden, or exclude search terms, while quotation marks can be used to search for exact phrases in systems that support this function. Truncation and wildcard symbols can help retrieve variations of a word, while field searching allows users to limit their queries to specific attributes, such as titles, authors, or subjects. Searching by controlled subject headings rather than keywords may also produce different results, depending on how a database organizes its information. Another important principle is iterative searching, which involves reviewing initial results, identifying relevant terminology, and adjusting a query to improve its effectiveness. These strategies allow information professionals to develop more precise searches and retrieve information that might otherwise be overlooked.
Evaluating Information Retrieval Systems
Even a well-designed information retrieval system may not always produce useful results. Evaluating these systems is therefore essential to understanding whether they are meeting the needs of their users. Manning et al. (2008) discuss two important measures of retrieval effectiveness: precision and recall. Precision refers to the proportion of retrieved results that are relevant to a search, while recall measures the proportion of all relevant materials in a collection that the system successfully retrieves. For example, a search which returns hundreds of results may appear successful, but if only a small number are relevant, the user may struggle to find useful information. Conversely, a search which returns only a few highly relevant results may still be ineffective if it excludes other important materials. Evaluating retrieval effectiveness therefore involves examining whether a database returns an appropriate balance of relevant results while minimizing unnecessary information and avoiding the exclusion of important resources. By testing searches and comparing the results against known relevant materials, information professionals can identify weaknesses in indexing, search functionality, or retrieval performance.
Technical performance is not the only measure of effectiveness, however. Information professionals must also consider how easily users can navigate a system, whether its search functions are understandable, and whether its design creates unnecessary barriers. A system may retrieve relevant information accurately but still be difficult for someone unfamiliar with its interface to use.
Ultimately, designing, querying, and evaluating information retrieval systems are essential responsibilities within Library and Information Science. As someone who intends to pursue academic librarianship, I recognize the importance of understanding not only how these systems operate, but also how their design influences access to information. By developing effective search strategies and critically evaluating retrieval systems, I hope to help students and researchers navigate increasingly complex information environments.
Evidence
Evidence #1: Search and Reference Activities
- Search Activity 4 — Comparing Database Searches
- Search Activity 9 — Finance, Medical, and Legal Searches
- Search Activity 13 — Current and World Issue Searches
My first piece of evidence consists of three search activities I completed for INFO 210: Reference and Information Services. Throughout these assignments, I explored a variety of information resources and practiced developing search strategies to locate, evaluate, and compare information across different platforms. In the first activity, I researched transformational leadership using reference databases, academic search tools, and Google, comparing the definitions and information available through each source. I also explored biographical databases and psychological assessment resources, examining how their content and organization differed depending on the information being sought. In the second activity, I investigated specialized resources related to business, medicine, and government information. This included comparing financial information available through Google Finance, Mergent Online, and Morningstar, as well as using PubMed to explore different search methods in medical reference, including Boolean operators and advanced filtering options. In the third activity, I evaluated open-access and subscription-based resources, comparing their credibility, accessibility, and usefulness for different research questions. These searches included examining information about artificial intelligence through ProCon.org and Gale’s Opposing Viewpoints, as well as researching Iraq through the CIA World Factbook and Library of Congress Country Studies. Each activity included screenshots documenting my searches and the information I retrieved.
I selected these activities because they demonstrate my ability to accurately query and navigate different information systems and evaluate the effectiveness of various search strategies. Through these assignments, I learned that locating relevant information requires more than entering keywords into a search engine. Different databases offer unique search functions, organizational structures, and levels of detail, making it important to understand which resources are most appropriate for a particular information need. For example, comparing Boolean searching with PubMed’s filtering options helped me recognize how different approaches can affect the accessibility and precision of search results. Similarly, evaluating open-access resources alongside subscription databases reinforced the importance of considering credibility, depth of information, and accessibility when recommending sources to patrons. I also developed a greater appreciation for the role of reference librarians in helping individuals navigate unfamiliar information systems and assess the reliability of what they find. As I pursue a career in academic librarianship, I hope to apply these skills when assisting students and faculty with research, developing effective search strategies, and helping library users become more confident and independent in locating and evaluating information.
Evidence #2: Rule Writing in Sock Cataloging
My second piece of evidence is a rule-writing exercise for INFO 202: Information Retrieval System Design in which I developed search fields and cataloging rules for an information retrieval system designed to organize a collection of socks. For this assignment, I created four descriptive fields: size, material, color, and length. Each field included a designated data type, a list of controlled vocabulary terms, a definition, and a set of rules explaining how information should be recorded. For example, my Size field included instructions for categorizing socks according to different international sizing systems, while my Material field established categories for identifying fabrics and blends. I also developed rules for determining the primary color of a sock and classifying its length according to where it sits on the foot or leg. Throughout the exercise, I considered how to make these instructions clear and consistent, including how to account for socks without packaging or information that could not be determined. By establishing these fields and rules, I created a framework for describing individual items in a way that would support their organization and retrieval.
I selected this artifact because it demonstrates my understanding of how information retrieval systems and controlled vocabularies contribute the accuracy of those systems. Through this assignment, I recognized the importance of establishing consistent descriptive standards when designing an information retrieval system, particularly when multiple individuals may be responsible for entering information into the same system. Without clearly defined rules, similar items could be described differently, making it more difficult for users to locate relevant results. I also learned how decisions about field requirements, terminology, and classification can influence the effectiveness of an information retrieval system. Although this exercise focused on a relatively simple collection of socks, the principles involved are applicable to more complex information environments, including library catalogs and digital collections. As I pursue a career in academic librarianship, I hope to apply this understanding when working with metadata, organizing information resources, and supporting systems that allow students and faculty to locate materials efficiently.
Evidence #3: Group Project – Information Retrieval System Beta Prototype:
Decorative Plants and their Toxicity to Cats and Dogs
My third piece of evidence is an information retrieval system prototype I developed as part of a group project for INFO 202: Information Retrieval System Design. For this assignment, our group designed a database of decorative houseplants intended to help cat and dog owners identify plants suitable for their homes. We began by establishing a statement of purpose and identifying the needs of our intended audience, particularly concerns surrounding pet safety, available space, and plant care requirements. From there, we developed a data structure that organized plants according to characteristics such as category, soil type, lighting requirements, watering frequency, mature height, pot size, and potential toxicity to pets. My primary responsibility was managing the construction of the database within Caspio, where I translated our proposed data structure into a working prototype. This included creating the structure necessary to organize plant records and developing the submission form through which new entries could be added. I also contributed to establishing clear parameters and definitions for our indexing rules, helping ensure that information could be entered consistently by different individuals. Together, these elements provided the foundation for a system that could organize and retrieve plant information according to the needs of its users.
I selected this artifact because it demonstrates my ability to apply information retrieval principles through both collaborative planning and hands-on system development. While my previous rule-writing exercise focused on establishing descriptive standards, this project allowed me to put those concepts into practice by building the structure of an actual database. Working within Caspio helped me better understand how decisions about data types, fields, and submission forms influence the way information is stored and made available for retrieval. My contributions to the indexing rules also reinforced the importance of developing instructions that are understandable to individuals responsible for adding records, particularly when information may be incomplete or difficult to categorize. Additionally, working with my group required us to consider how our design decisions would affect the experience of our intended audience. For example, organizing records around pet safety and environmental requirements allowed users to narrow their searches according to practical concerns rather than simply browsing a general list of plants. This experience strengthened my technical understanding of information retrieval systems while also demonstrating the importance of collaboration in their development. As I pursue a career in academic librarianship, I hope to apply these skills when contributing to the design and maintenance of digital collections, institutional repositories, and other systems that make information more accessible to students and researchers.
Conclusion
Through these assignments, I have developed a more comprehensive understanding of how information retrieval systems function from both the perspective of the user and the information professional responsible for their development. My experiences have strengthened my ability to approach information access critically, recognizing how decisions made during system design can influence the quality and relevance of search results. I have also gained practical experience translating theoretical concepts into functional tools while considering the needs of different audiences. As I move into Academic Librarianship, I intend to build upon these skills by contributing to the improvement of discovery systems, supporting effective research practices, and helping ensure that information remains accessible, accurate, and discoverable to those who need it. I also look forward to helping students find the right databases and search systems they need to complete their own research.
References
| Association of College and Research Libraries. (2026, September 2). Framework for information literacy for higher education. American Library Association. https://www.ala.org/acrl/standards/ilframework Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge University Press. https://doi.org/10.1017/CBO9780511809071 Riley, J. (2017, January 1). Understanding metadata: What is metadata, and what is it for? National Information Standards Organization. https://www.niso.org/publications/understanding-metadata-2017 |