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The purpose of this paper is to review literature on librarian professional identity to develop a more integrated understanding of this topic.

Literature was retrieved and analysed with no date or geographic limit from nine databases on the subject of librarian professional identity. A combination of keywords and database specific controlled language was utilized to increase retrieval, as well as inspection of reference lists. Exclusion criteria were applied.

The review found 14 characteristics or themes relevant to librarian professional identity formation and development, understood as process over time. This process is in part defined by benchmark events, such as critical incidents, as well as highly personal aspects, such as perception of these incidents. This review also introduces an original conceptual model of librarian professional identity formation and development.

A limitation of this review was that only English-language literature was considered. A further limitation is the omission of works that have not been formally published. Additionally, the model introduced is untested.

By reviewing librarian professional identity literature, this paper offers an integrated understanding of this topic and introduces a new, original model to understand the process of librarian professional identity and development. It further offers an examination based on a sociological lens to examine this identity.

This study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.

In this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.

This paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.

Early career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.

This study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

Jennifer Campbell-Meier is an instructor at the School of Library and Information Science at the University of Alabama. Formerly, she was the coordinator of Library Instruction & Distance Education at North Georgia College & State University. She earned an MLS (1995) from Indiana University and a PhD (2008) in Communication and Information Sciences at the University of Hawaii at Manoa.

This study investigated the development of institutional repositories (IRs) at doctoral institutions, identifying factors that influence development and best practices using a comparative case study analysis approach to gather and analyze data. The development of a repository is one of the more complex projects that librarians may undertake. While many librarians have managed large information system projects, IR projects involve a larger stakeholder group and require support from technical services, public services, and administration to succeed. A significant increase in the development of repositories is expected with technology and process improvements for digital collection development so further study is warranted. Both institutional and subject repositories were examined for the case studies. Best practices and recommendations for future developers, such as early involvement of stakeholder groups and the need to educate both librarians and teaching faculty about open access collections, are also discussed. This study contributes to a more informed understanding of the development of IRs and identifies a model framework for future IR developers. The best practices framework incorporates the processes from the case study sites and includes additional factors identified from the case study interviews. Key to the framework is the inclusion of stakeholder groups on campus and assessment measures. While the case studies focused on doctoral institutions, the framework can be adapted to any size institution.

This paper aims to explore the extent of open data actualization for start-up entrepreneurs based on affordance theory. The principal interest of the study revolves around the possible actions or actualization of open data for innovation and entrepreneurial benefits.

The author used a qualitative case study as the research design. The author consulted the central public agency that manages open data implementations in Malaysia regarding the research topic. By doing so, the author recognized and interviewed start-up entrepreneurs who actualize open data in businesses. From that exercise, the author conducted a snowball sampling technique to recruit more informants for the research. Start-up entrepreneurs selected for the study must be active in an entrepreneurial project and have at least one year of experience using open data for innovation and entrepreneurship. The author conducted 30 online semistructured interviews with start-up entrepreneurs, representatives from open data providers and a start-up association for triangulation purposes. The author adopted affordance theory as a lens of understanding. Qualitative analysis software was used to generate research findings.

In this study, start-up entrepreneurs actualize open data in three principal areas: product building with open data, value creation with existing products and open data for business research and strategies. The study came across distinct narratives of local start-ups that build open data products named “a property start-up,” “mechanics on the go” and “peer-to-peer digital charity movement.” Also, the study discovered three unanticipated findings about the research topic. First, the study uncovered two start-ups that used open data to enhance algorithm designs. Second, the study revealed a unique narrative of a start-up that pivoted business ideas based on open data during the Covid-19 pandemic. Third, the study learned about a start-up that initiated strategic partnerships with an agricultural association and smallholder farmers inspired by open data. These findings extend the literature on how start-up entrepreneurs actualize open data for entrepreneurial gains in a developing economy. What is also unique about this study is that there might be an open data misconception among start-up entrepreneurs. The findings advocate that some start-up entrepreneurs believed all data should be shared or opened upon request based on the generic understanding of open data. Clearly, this is a fallacy, and better awareness is required among start-up entrepreneurs regarding open data principles and implementations.

Data providers need to build a credible image of open data as a foundation to drive actualization. This can be achieved through capacity building, awareness campaigns and strategic engagements with start-up entrepreneurs. Open data institutions need to initiate flagship projects with start-up associations in highly valuable sectors to demonstrate commercial applications of open data in certain fields.

Previous research provides limited empirical studies on the commercial application of open data for start-up entrepreneurs. Hence, the novelty of this study lies in understanding how start-up entrepreneurs actualize open data to create value in their respective fields.