Qualitative Data Topic 2 DQ 1
There are several strategies that can be put in place by researchers to manage the overwhelming and voluminous nature of qualitative data. The first strategy is the use of current technologies for the storage of data, which will make access to the information easy. For instance, feeding information to search engines that are full text like Lucene that makes it possible for data to be retrieved easily (Büttcher et al., 2016). The engines for data searching can be configured to perform searches that are faceted, making it possible for metadata facets to get attached like the type of media, the author, and the date of creation. This strategy allows ease of access to qualitative data for the purpose of supporting quantitative analysis.
Another strategy is the management of data through the central repository, which is the location where all the original raw files of data that gets submitted by the ethnographic get stored on a network in the hard drive. In this strategy, every member of staff has their own location for the storage of data that is unique. These data are inclusive of digital voice files, notes made in the field during research and transcripts. The management of all these files then gets placed under one staff member from the administration of the organization. Every digital voice file and field note that gets uploaded by the staff from the field gets placed in a spreadsheet for the [purpose of tracking the progress of the work, and if it gets discovered the something is missing, then the data gets uploaded again.
Another strategy for management and organization of qualitative data is through semi-quantitative coding, which entails the storage of questions and answers to interview in a database (Haenssgen, 2019). The respondents then get coded in accordance with their education level and their gender by the analyst to be able to define categories for themes that are different and assign numeric values to each of the categories. This classification makes it easy for researchers to access specific information regarding particular information in the process of data analysis.
References
Haenssgen, M. J. (2019). Data Analysis Methods. In Interdisciplinary Qualitative Research in Global Development: A Concise Guide. Emerald Publishing Limited. Retrieved from https://www.emerald.com/insight/content/doi/10.1108/978-1-83909-229-920191006/full/html
Han, W., & Jochum, M. (2018, July). Assessing a central satellite data repository and its usage statistics. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 6528-6531). IEEE. Retrieved from https://ieeexplore.ieee.org/abstract/document/8519346/
Büttcher, S., Clarke, C. L., & Cormack, G. V. (2016). Information retrieval: Implementing and evaluating search engines. Mit Press. Retrieved from https://books.google.com/books?hl=en&lr=&id=2c3RCwAAQBAJ&oi=fnd&pg=PR7&dq=+search+engines+that+are+full+text+like+Lucene+that+make+it+possible+for+data+to+be+retrieved+easily&ots=7rH0npI-iB&sig=E3wR8hE83N0XhInGULBj6lRChQ0