Indexing is categorizing and organizing data according to a specific framework or rules. Data will then be more organized and easier to be accessed and read. This data has been indexed for comparison using a similar point of reference. For one or a company to choose what to index in an information system, there are factors to be considered for them to choose wisely. They have to know, for example, how indexing this data help them achieve their goals, the risk constraints and its relevance for the organization.
One of the factors to be considered includes importance and relevance of the information. The relevance of information determines the indexing priority. High-value or essential information should be indexed with higher priority making them to be accessed and retrieved easily. This ensures that the most crucial information is made available to the users. Information relevance also affects the indexing depth. Indexing may involve a more thorough analysis to ensure quick and accurate search results for the most important and relevant information. (Li, Lei, & Mao, 2022). Another factor is the available resources. This directly impacts the indexing process in an information system. The availability of resources such as computing power, storage capacity, network bandwidth, and even humans. To avail all these, budget constraints are automatically considered.
Additionally, volume of data is another essential factor to be considered. Large volumes of data may require careful consideration as they may be difficult to handle, unlike small volumes of data. Also, indexing large volumes of data may have performance implications. The time needed to search and retrieve information increases as the volume of data increases. Depending on the type of indexing algorithm, performance may degrade if high-quality and complex ones are not used when handling large volumes of data. Furthermore, the time taken to generate an index for a large volume of data is more compared to less data. (Kar, & Dwivedi, 2020).
User feedback and usage patterns also influence the decision on what to index in an information system. Analysis of questions users ask or search for, together with search logs, will help and provide insights on areas that require improvements and the most popular type of information users need. Knowing all these will then improve information accessibility and accuracy in a search system. Privacy and legal constraints are also considered when deciding what to index. Some specific types of data, such as personal and private data, may require some additional safeguard controls to restrict accessibility or are sometimes excluded from indexing to ensure compliance with the existing rules and regulations (Viljoen, 2021).
Scope. Scope refers to the boundaries or depth of the content included in an information system’s indexing. This greatly varies depending on a particular information system’s needs, goals and objectives. The scope will therefore determine the content to be included in the index, that is, a subset of the information in a system or the whole of it. The scope also affects the system’s performance, especially when dealing with large volumes of data. A narrower scope can then be implemented to improve the system’s performance altogether. (Shim, & Jo, 2020). The presence of structured metadata for particular information in a system also affects the decision on what to index. Since metadata is “data about data,” it provides additional contextual information about data that increases its search capabilities. Such data should be indexed.
References
Li, L., Lei, B., & Mao, C. (2022). Digital twin in smart manufacturing. Journal of Industrial Information Integration, 26, 100289.
Kar, A. K., & Dwivedi, Y. K. (2020). Theory building with big data-driven research–Moving away from the “What” towards the “Why”. International Journal of Information Management, 54, 102205.
Viljoen, S. (2021). A relational theory of data governance. Yale LJ, 131, 573..
Shim, M., & Jo, H. S. (2020). What quality factors matter in enhancing the perceived benefits of online health informa
Data Organization
tion sites? Application of the updated DeLone and McLean Information Systems Success Model. International Journal of Medical Informatics, 137, 104093.
write