Graphic elicitation techniques, which ask research participants to provide visual data representing personal understandings of concepts, experiences, beliefs, or behaviors, can be especially useful in helping participants to express complex or abstract ideas or opinions. The benefits and drawbacks of using graphic elicitation techniques for data collection, data analysis, and data display in qualitative research studies are analyzed using examples from a research study that employed data matrices and relational maps in conjunction with semi-structured interviews. Results from this analysis demonstrate that the use of these combined techniques for data collection facilitates triangulation and helps to establish internal consistency of data, thereby increasing the trustworthiness of the interpretation of that data and lending support to validity and reliability claims. Findings support the notion that graphic elicitation techniques can be highly useful in qualitative research studies at the data collection, the data analysis, and the data reporting stages. For example, this study found that graphic elicitation techniques are especially useful for eliciting data related to emotions and emotional experiences.

Data have significant potential to address current societal problems not only at the federal and state levels, but also in smaller communities, in neighborhoods, and in the lives of individuals. While the proposition for this potential is that data are and will be shared with and reused by and for communities at different levels, not all data are systematically or routinely shared for reuse with communities due to social, structural and technical infrastructure barriers. Data intermediary organizations can play a significant role in removing existing barriers while unlocking the potential of data for all, particularly for communities with limited human or financial resources, limited access to existing data infrastructures, and underserved populations. Considering the significance of the data intermediary organizations on local communities, this study aims to explore the role of intermediaries that usually facilitate community members/organizations' data utilization. The findings of this study reveal that data intermediary organizations play four major roles that are crucial in communities' data utilization: (1) democratizing data, (2) adding value to existing data, (3) enhancing communities' data literacy, and (4) building communities' data capacity. This study has several important implications to offer as a solution to overcome the challenges of data reuse at the local level.

This research investigated preservation practices of personal digital information by public library users. This qualitative study used semistructured interviews and two visual representation techniques, information source horizons and matrices, for data collection. The constant comparison method and descriptive statistics were used to analyze the data. A model emerged which describes the effects of social, cognitive, and affective influences on personal preservation decisions as well as the effects of fading cognitive associations and technological advances, combined with information escalation over time. Because the preservation of personal digital information involves personal, social, and technological interactions, the integration of these factors is necessary for a viable solution to the digital preservation problem.

As a cultural institution, the public library is charged with providing resources and services that fit the needs of a particular community and, if space and budgets allow, of serving as a resource and repository of the community's past. To fulfill its mission to the public, the library must attract that public by offering materials and providing opportunities for them to pursue their unique and varied interests and discover new things. By engaging individuals in the identification and preservation of their own personal, digital objects, it may be possible to increase awareness in, and commitment to, community repositories that reflect a community's diversity and that will serve all. A user education program that focuses on the importance of identifying and preserving the information and artifacts that are important, that addresses the technical aspects of preservation, and that creates awareness of the benefits and challenges associated with sharing personal information can result in a community repository that ultimately has more value for both the individual and the community.

The benefits of open data for helping to address societal problems and strengthen communities are well recognized, and unfortunately previous studies found that smaller communities are often excluded from the current data ecosystem because of existing technological, technical, cognitive, and practical barriers. This study aims to investigate the process of communitiesʼ data use for community development and decision‐making—focusing on the opportunities and challenges of data for communities. From the interviews with 25 staff from community‐based organizations (CBOs) in nine small, medium, and large cities in the United States, the findings of this study describe dataʼs role in supporting communitiesʼ development while reporting several major challenges that hinder CBOs data use: difficulty accessing data, limitations of open data (un‐local nature, excluding essential data from being open), limited data capacity (especially in data literacy skills), and difficulties using and accessing existing data infrastructures. Our findings suggest opportunities for addressing these challenges, particularly by creating educational programming, building partnerships within data ecosystems, and bringing community voices forward in current data ecosystems, which are critical to realizing dataʼs potential for all citizens.