Raw Data (Nvivo)

This dataset contains the raw qualitative data and coding outputs used in the research on digital communication and public service engagement in library institutions. The data were processed and analyzed using NVivo software to identify key themes, patterns, and relationships within interview transcripts and supporting documents. The dataset includes several types of files that support qualitative analysis and ensure research transparency and reproducibility. The materials consist of coded interview transcripts, thematic coding structures, coding frequency comparisons, and word frequency analysis generated during the NVivo data processing stage. The interview data were collected from multiple informants, including librarians, information technology personnel, literacy community representatives, and library users. These participants provided insights into the implementation of digital communication platforms and digital service engagement strategies in public library services. The NVivo coding process involved categorizing responses into thematic nodes related to digital platforms, communication strategies, service effectiveness, technological constraints, and user engagement. The coding structure was then analyzed to examine patterns of digital communication practices, platform utilization, and the challenges faced in implementing digital public services. The dataset contains the following components: Interview transcripts used as primary qualitative data sources. Coding framework (codes) representing thematic categories developed during NVivo analysis. Coding comparison results showing the distribution and number of coding references across themes. Word frequency query results generated to identify dominant keywords and recurring concepts in the data. Supporting documents related to digital public communication practices and implementation constraints. These data provide transparency for the qualitative analytical process and allow other researchers to understand how themes and interpretations were generated from the raw interview materials. For ethical considerations, the dataset does not include sensitive personal identifiers of the participants. Informants are anonymized using coded identifiers to protect their privacy. The dataset can be used by researchers interested in qualitative research methodology, digital public communication, digital engagement strategies, and the role of digital platforms in public service institutions.