Information Retrieval Systems
Statement of Competency:
Design, query, and evaluate information retrieval systems.
Introduction
Information retrieval systems are central to how individuals locate, access, and evaluate information in both physical and digital environments. Competency E focuses on the ability to design, query, and evaluate these systems, requiring an understanding of both the technical structures that support retrieval and the human behaviors that shape how users search for information. Throughout my MLIS coursework, I have developed an understanding that effective information retrieval is not simply about locating data, but about designing systems that connect users to relevant information in meaningful and efficient ways.
At its core, information retrieval involves the organization and representation of information so that it can be discovered and used. Bates (1999) describes information science as a field concerned with the representation and organization of information rather than the information itself, emphasizing that retrieval systems depend on how information is structured and described. This includes the use of metadata, controlled vocabularies, and classification systems, all of which influence how information is indexed and retrieved. Without thoughtful design at this level, even well-developed systems can fail to meet user needs.
Equally important is the role of user behavior in shaping retrieval systems. Information-seeking is not a linear process, and users often engage in iterative searching, browsing, and refining of queries. Bates (2007) explains that browsing involves a series of actions—glimpsing, selecting, examining, and either acquiring or discarding information—highlighting the dynamic nature of information retrieval. This behavior must be considered when designing systems, as rigid or overly structured systems may not align with how users naturally search for information.
The effectiveness of an information retrieval system is also influenced by how well it supports relevance and usability. Relevance is not a fixed concept, but one that varies depending on context, user needs, and situational factors (De Sabbata et al., 2015). Modern retrieval systems must account for these variables while also providing intuitive interfaces that support efficient navigation. However, as Tucker and Edwards (2021) note, many contemporary search systems have prioritized speed and simplicity over depth, often limiting users’ ability to perform complex searches or fully understand the scope of available information. This shift underscores the importance of designing systems that balance accessibility with functionality.
In addition to system design and user behavior, evaluation plays a critical role in ensuring that retrieval systems are effective. Information professionals must assess whether systems meet user needs, identify areas for improvement, and refine structures accordingly. This includes evaluating database fields, search functionalities, and overall usability. As Hirsh (2022) emphasizes, information professionals are responsible for selecting, organizing, and providing access to information in ways that support diverse user communities, making evaluation an ongoing and essential process.
Through my coursework, I have engaged with information retrieval systems from multiple perspectives, including designing databases, developing controlled vocabularies, evaluating system effectiveness, and working with real-world datasets. These experiences have allowed me to understand how retrieval systems function both structurally and from a user-centered perspective. This competency reflects my ability to design, query, and evaluate information retrieval systems in ways that support effective access to information across a variety of contexts.
Evidence
My understanding of information retrieval systems has developed through coursework that required me to design, evaluate, and apply retrieval systems across different contexts. Through assignments in INFO 202, INFO 248, INFO 220, and INFO 287, I engaged with both the structural and user-centered aspects of retrieval systems. These experiences allowed me to move from designing controlled systems to evaluating their effectiveness and ultimately applying retrieval principles to real-world data and user-facing environments.
Artifact #1
Beta Prototype Design: LEGO Botanical Collection Database (INFO 202: Information Retrieval System Design)
Justification
This artifact demonstrates my ability to design an information retrieval system by creating a structured database tailored to a specific user group. In this project, my team and I developed a database for the LEGO Botanical Collection, focusing on how users would search for and retrieve information based on their needs.
The design process required identifying key fields such as set name, price range, number of pieces, and botanical type, and structuring them in a way that supported both broad and specific queries. Each field was intentionally designed with defined rules and controlled values to ensure consistency and accuracy during indexing. For example, dropdown fields and standardized input formats were used to minimize ambiguity and improve retrieval effectiveness. In addition to structuring the database, I applied user-centered design principles through card sorting exercises. These exercises revealed that users often categorize information based on both subject and context, rather than strictly defined system categories.
This insight influenced how the system was organized, reinforcing the importance of aligning system design with user expectations.
This artifact supports Competency E by demonstrating my ability to design an information retrieval system that integrates structured data, controlled vocabularies, and user-centered organization to support effective querying and access.
Artifact #2
Project Reflection: Database Design and Evaluation (INFO 202: Information Retrieval System Design)
Justification
This artifact demonstrates my ability to evaluate and refine an information retrieval system based on its effectiveness. In this reflection, I analyzed the strengths and limitations of the database design, particularly in relation to how information was structured and retrieved.
One key insight from this reflection was the importance of clearly defining fields and their relationships. For example, I identified confusion between the “brand” and “set name” fields, which impacted how users would search and retrieve information. This highlighted how even small inconsistencies in system design can affect retrieval accuracy and user experience.
I also reflected on the role of indexing and searching within the system, recognizing that retrieval systems must function effectively for both indexers and end users. This dual perspective allowed me to better understand how systems must balance structure with usability.
This artifact supports Competency E by demonstrating my ability to critically evaluate a retrieval system and identify areas for improvement, reinforcing the importance of iterative design and continuous refinement.
Artifact #3
Beta Prototype Evaluation Report (INFO 202: Information Retrieval System Design)
Justification
This artifact demonstrates my ability to evaluate an information retrieval system developed by others. In this assignment, I analyzed another group’s database design, focusing on how well it met user needs and supported effective retrieval.
Through this evaluation, I examined key components such as field structure, rule clarity, and search functionality. I identified strengths in the system’s organization, as well as areas for improvement, including inconsistencies in rules and limitations in field values that restricted search flexibility.
This process reinforced the importance of clear and consistent rules in supporting accurate indexing and retrieval. It also highlighted how system usability directly impacts a user’s ability to retrieve relevant information. By evaluating both successful and problematic elements, I gained a deeper understanding of how retrieval systems must be designed and tested to ensure effectiveness.
This artifact supports Competency E by demonstrating my ability to evaluate retrieval systems critically and apply principles of usability, structure, and functionality to assess system performance.
Artifact #4
Data Retrieval and Visualization Projects (INFO 220: Data Services in Libraries & INFO 287: Library Services in the Digital Age)
Justification
This artifact demonstrates my ability to apply information retrieval principles to real-world data systems and user-facing environments. These projects represent my progression from working with structured datasets to presenting retrieved information in meaningful ways.
In my INFO 220 project, I worked with a dataset on suicide rates in California, which required retrieving, cleaning, and transforming data using tools such as Excel, OpenRefine, and Tableau. This process involved organizing data fields, ensuring consistency, and preparing the dataset for analysis. The retrieval process was not limited to accessing data, but included refining and validating it to ensure accuracy and usability.
In my INFO 287 project, I extended these skills by creating a data visualization that communicated complex information to users. The homicide rate visualization demonstrated how retrieval systems must not only provide access to data, but also support interpretation. For example, I noted that missing data in visualizations does not necessarily indicate low values, but may reflect gaps in reporting or data availability. Highlighting the importance of evaluating how information is presented and understood by users.
https://public.flourish.studio/story/3587634/
This highlights the importance of evaluating how information is presented and understood by users.
Together, these projects demonstrate my ability to work across the full lifecycle of information retrieval systems, from data acquisition and processing to user-facing interpretation. This artifact supports Competency E by showing my ability to retrieve, evaluate, and present information in ways that support both analysis and user understanding.
Conclusion
Through these artifacts, I have developed a comprehensive understanding of how information retrieval systems are designed, implemented, and evaluated. By working with database design, system evaluation, and real-world data projects, I have gained insight into how information is structured and how users interact with retrieval systems. These experiences demonstrated that effective retrieval is not simply about locating information, but about ensuring that systems are organized in ways that support accurate, efficient, and meaningful access.
This competency has reinforced that the success of an information retrieval system depends on the relationship between structure and user behavior. A well-designed system must balance controlled organization with flexibility, allowing users to search, browse, and refine queries in ways that align with their information needs. Additionally, evaluating systems is essential to identifying limitations and improving usability, ensuring that retrieval systems continue to evolve alongside user expectations and technological advancements.
As I move forward in my career, I will apply these principles by designing and evaluating systems that prioritize both functionality and user experience. I will continue to refine my ability to structure information effectively, assess system performance, and adapt retrieval tools to meet diverse user needs. To remain current, I will engage with professional literature and ongoing developments in information retrieval, metadata standards, and user-centered design. By doing so, I will be better prepared to contribute to information systems that provide reliable, accessible, and meaningful access to information.
References
Bates, M. J. (1999). The invisible substrate of information science. Journal of the American Society for Information Science, 50(12), 1043–1050.
Bates, M. J. (2007). What is browsing—really? A model drawing from behavioural science research. Information Research, 12(4).
De Sabbata, S., Mizzaro, S., & Reichenbacher, T. (2015). Geographic dimension of relevance. Journal of Documentation, 71(4), 650–666.
Fisher, K. E., & Fulton, C. (2022). Information communities. In S. Hirsh (Ed.), Information services today: An introduction (3rd ed.). Rowman & Littlefield.
Hirsh, S. (2022). Information services today: An introduction (3rd ed.). Rowman & Littlefield.
Tucker, V. M., & Edwards, S. L. (2021). Search evolution for ease and speed: A call to action for what’s been lost. Journal of Librarianship and Information Science, 53(4), 668–685.