Introduction

Persona creation is a beneficial methodology of user experience (UX) research that is increasingly being used in academic libraries. With a broad range of applications, personas are fictional but realistic profiles that accurately and succinctly represent typical user communities of a specific product or service. Specialized library services, such as those offered by Geographic Information System (GIS) librarians, can effectively use the persona methodology to better inform strategic planning and operations within the library.

In this study, we detail the successful use of personas to direct the development of library programming at New York University Abu Dhabi (NYUAD), a liberal arts and research university connected to a network of global campuses and sites. We describe the persona-creation process from its initial planning phases through data collection to development of the personas themselves and presentation before the entire library team. We provide the user profiles developed from the study as a model for other librarians offering data or specialized research services to use as they plan services for their own communities. We discuss the limitations of this study and the persona methodology, and we give suggestions for further research in the maintenance and refining of personas to accurately represent the information needs of the user community.

Literature Review

The Nielsen Norman Group, a leading UX research and consulting firm in the United States, defines a persona as, “a fictional, yet realistic, description of a typical or target user of the product. A persona is an archetype instead of an actual living human, but personas should be described as if they were real people,” (Harley, 2015).

One of the leading experts on personas as a UX methodology is Lene Nielsen of IT University of Copenhagen. Nielsen completed her doctorate in digital product development at Copenhagen Business School using personas as a case study (Nielsen, 2004). Based on her fifteen years of research into personas, Nielsen developed the ‘10 Steps to Personas’ method with applications to business, communications, information technology, human-computer interaction, and more. The basic idea is to tell the “story” of the user to better understand their needs, perceptions, and how they will use a particular product or service (Nielsen, 2019). The concept of “personas” is similar to that of “profiles,” such as “learner profiles” (Software Carpentry, 2021) and is closely related to the concepts of “user stories” and “use cases” (Ford, 2019).

The library is, in a sense, a product or service that exists to meet the information needs of its users or patrons. While the persona-methodology has been largely applied to business and technology, it has also been used within libraries. Singh argued for the utility of personas in information and library science research, noting its strengths and its weaknesses (2018). Although use of personas in libraries does not appear to be widespread, they have been implemented successfully in relation to web-design (Sundt & Davis, 2017) and marketing (Thompson, 2017). Some librarians found personas to be applicable to a specific population, such as humanities scholars at universities (Al-Shboul & Abrizah, 2016) or ethnic minority users in public libraries (Adkins et al., 2019). Other academic librarians found evidence that personas might describe more or less universal experiences between users (Zaugg & Ziegenfuss, 2018).

In the field of GIS services, usability studies have typically been conducted to improve delivery of services. These types of studies are directly relevant to today’s academic libraries, as institutions have recognized the benefits of integration and collaboration of library and GIS services for some time (Dixon, 2006), particularly regarding graduate education (Oberle et al., 2010). For instance, the Center for Geographic Analysis at Harvard University is a leading model of cooperation between libraries and GIS services in support of various user populations (Guan et al., 2011; Guan et al., 2012); Syracuse University is another such model (Olson, 2004). Bishop et al. (2013) noted in their analysis of the GeoWeb that geospatial technology continues to evolve, and the variety and number of users is increasing. This fact poses a challenge to academic librarians who offer core GIS services to students and faculty, as Kong (2015) highlighted, making usability studies an imperative tool in keeping up with a rapidly changing environment.

The Big Ten Academic Alliance Geospatial Data Project conducted one major usability study in GIS; although it did not use personas, the researchers did categorize users into experienced and inexperienced users and into undergraduate students and advanced researchers (Blake et al., 2017), which is analogous to the division of users in persona creation. The Norman B. Leventhal Map Center, a non-profit organization that provides stewardship of the Boston Public Library’s cartographic collections, used the methodology of personas to inform both the design of public GIS products and programs as well as to conduct usability tests in the post-launch phase (Thornberry, 2017).

Our study aims to contribute to the literature by detailing the successful implementation of personas to enhance GIS services at New York University Abu Dhabi.

Research Objectives

Depending on research domain or experience, people who approach a librarian who offers geospatial services have different ideas about what geospatial research is and the tools used. Some people come to the library with extensive knowledge, some come to the library with expectations based on what was available at their previous institutions, and some have never used geospatial data or tools but want to engage them. This study provides an approach that considers faculty and doctorate-holding researchers’ geospatial needs using narrow-scope personas (Salazar, 2020) to better understand the typical reference interaction and queries from faculty and researchers who often steer the long-term research agenda of the institution. Our objective was to assist in the planning of long-term and scalable programming related to geospatial data services, rather than continuing an unscalable premium service mentality.

The data collected through interviews for this project were originally part of an internal assessment of geospatial research needs of faculty, postdocs, and doctorate-holding research associates and instructors at New York University Abu Dhabi. These groups lead the research mission of the university, in which the library provides essential support, so it was critical to ensure the library’s GIS program matched the actual needs of researchers based on evidence, rather than assuming the needs or perceptions of users. After we completed interviews and identified the general needs, there was an interest in using the data further to create personas, which led to the conclusions of this study.

Methods

Project Phases and Planning

This research consisted of seven phases: data collection planning, first-round data collection, second-round data collection, data synthesis, personas development, reflection, and presentation and integration. Here is a brief description of each phase.

    Phase 1: Data collection planning
  • Decide on primary method of data collection as a semi-structured interview.

  • Curate a list of users to request for interviews.

  • Contact users identified to interview in March and April 2019.

  • Draft guiding interview questions.

    Phase 2: First-round data collection
  • April 2019: Conduct nine semi-structured interviews that yield usable data (primary data).

    Phase 3: Second-round data collection
  • Identify geospatial reference interactions with faculty between January 2018 and May 2019.

  • Use the information from the reference data to supplement interview data (secondary data).

    Phase 4: Data synthesis
  • Transcribe interview notes and structure them into a spreadsheet.

  • Identify themes and concepts within the primary and secondary data using online tools for text and content analysis.

    Phase 5: Personas development
  • Design personas round 1: Draft and storyboard text-based personas.

  • Design personas round 2: Design visual personas.

    Phase 6: Reflection
  • Compare personas with data.

  • Refine personas as needed to better reflect typical user-interactions based on the data.

    Phase 7: Presentation and integration
  • Create an internal report to present to the library team and administration.

  • Integrate improvements identified from personas into annual planning, service improvements, programming, and budget justifications.

Data Collection

We collected the primary data used in the development of the personas through semi-structured interviews and supplemented with secondary data from recorded geospatial reference consultations with the target group from the previous year and a half. We used this time range for the secondary data because no other experiential data was available; the geospatial data services librarian entered the role in January 2018 and no well-documented or recorded reference information related to geospatial consultations was available prior to that.

The semi-structured interviews were with doctorate-holding faculty, researchers, postdocs, and instructors at the university. We chose this method because library colleagues had shared that they had seen low response rates and minimal success with more impersonal surveys and had better success with in-person contact. Additionally, interviews allowed the people to share more personal and in-depth details about how they integrated geospatial data and tools into their research, which produced a significant set of qualitative data we could use to enhance the program’s services.

We contacted the users for interviews based on previous geospatial reference data and recommendations from colleagues with departmental liaison roles. The initial outreach requests for interviews targeted roughly representative responses from each academic division, which included arts and humanities, social sciences, science, and engineering. A limitation of our study is that the interview request response rate and interest across academic divisions varied, which is an expected challenge when collecting data from people whose busy schedules may not be able to accommodate time for interviews.

We developed interview questions to guide the conversation, but due to the semi-structured nature of the interviews, not all interviewees answered every question. The prepared interview questions were:

  • Would you consider yourself a current user of GIS or geospatial data?

  • If yes, how do you use it?

  • What have your prior institutions had that we do not?

  • What would you like to see?

  • Are there any geospatial needs you have that are currently not being met that you think the university or library could be meeting?

  • Do you think GIS/geospatial data are important to your colleagues, deans, administrators, students?

We used supplemental reference data to fill in the gaps in the needs of specific academic divisions. The supplemental data included four recorded reference interactions with arts and humanities, three with social sciences, one with science, and one with engineering. Those reference interactions ranged from asking about access to GIS on campus to more complex assistance with data creation and project management needs. This data provided us with hands-on, real-world queries from the targeted user populations to complement what we extracted from the semi-structured interviews.

Results

In total, we conducted eight in-person interviews during spring 2019, and one additional user responded by email. Six of the interviewees were faculty members at various levels, two were research scientists, and one was a postdoctoral associate. We included the interviews of three non-faculty members since the aim of the study was to improve the library’s programming comprehensively to meet research needs for the entire campus. This is a breakdown by academic division of the affiliations of the interviewees:

    Arts and Humanities
  • 1 assistant professor

  • 1 associate professor

    Engineering
  • No interviews conducted

    Science
  • 1 assistant professor

  • 1 associate professor

  • 1 full professor

  • 1 postdoctoral associate (non-faculty)

  • 2 research scientists (doctorate-holders, non-faculty)

    Social Sciences
  • 1 assistant professor

The interview data contained more representation from the science division than others. While science is one of the largest academic departments at the university, social sciences is larger, and we interviewed only one faculty member from that division. We had contacted an even split of people across the divisions for in-person interviews, but users from science were more responsive at the time of this study.

We used the supplemental data from reference interactions to compensate for the limited number of respondents across departments. However, there were still inequities in how many doctorate-holding researchers and faculty on campus had recorded outreach to the librarian. The supplemental reference data are outlined in appendix A.

Personas Development

GIS programming and technology can be more costly and difficult to justify compared to the needs of other library services. Since a goal of personas is to educate and influence stakeholders (Salazar, 2020), we chose to use them because they are a useful tool in garnering support for the development and design of new and potentially expensive programming. The ability of personas to influence is one of its essential strengths as a methodology, because the storytelling component makes the argument seem more realistic and allows stakeholders to envision the user base of a new service or technology. When asking for funds, it is important for librarians to clarify for administration who the new services will impact and the long-term benefits of building these programs that may sustain partnerships across the university.

One of our other goals of generating personas was to identify user patterns of behavior to develop streamlined, satisfactory, and scalable GIS data services—ensuring time and money were well spent. The objective of this project was not to create universal personas that other institutions can use to represent their typical users, but to document a workflow for local persona creation in libraries and attest to their usefulness in developing GIS data services.

Developing personas is not an exact science that has strict requirements or uses precise measures. A persona often relies on imprecise generalizations from data to tell a realistic story that is not tied to a singular, known person. It is a fictionalized yet genuine profile representing a typical user and behavior derived from the connections found across multiple data points. In this study, we used the primary and secondary data to develop three personas representing typical GIS researchers at the university.

Exploratory Data Visualization

We used the online environment Voyant Tools (https://voyant-tools.org) to generate exploratory data visualizations from both the text of interviews and supplemental data. This led us to better understand the data and derive general categories and themes to use across all the personas. Voyant Tools is an easy-to-use application that provides content and text analysis to generate word counts and pairings, as well as useful visualizations, that demonstrate common themes and connections between words. Major themes from the interviews included various ways users could receive geospatial data and research support, student training, funding, and labs.

For example, Figure 1 is an image generated from the Collocates Graph tool in Voyant Tools. It shows the selected keywords GIS, data, and research in blue and words that are often collocated with, or nearby them, in orange. This visualization helped generate themes and categories for realistic researcher profiles, goals, and frustrations for the personas.

Figure 1
Figure 1

Theme visualization.

One way to interpret the link based on the keyword “GIS” is that some interviewees who were using GIS were focused on publishing papers and disseminating results. From the “research” keyword, we could interpret that some people needed continued research support not only for themselves but also for capstone projects, which all seniors are required to complete. The social link could reflect a theme many interviewees touched upon: the desire for a community of practice at the university surrounding geospatial research. Lastly, the keyword “data” and its links might best reflect themes from both primary and supplemental data where people needed assistance with data collection, turning data into maps, or learning more data skills to complete geospatial research projects. When interpreting this visualization, our understanding of both the context of the interviews and supplemental data is essential to make sense of the resulting image.

Determining How Many Personas to Create

There is not a specific desirable number of personas to create. In this study, we identified three groupings of characteristics in the primary and secondary data. Broadly, the people interviewed or interacted with in the supplemental data could be described as people who did not see themselves as GIS users but wanted to use it more, those who did not see themselves as GIS users but generated significant amounts of geospatial data in their research, and those that were frequent users of geographic information and GIS and would identify themselves as such. These groupings led to the creation of three distinct, realistic, and well-rounded personas that capture a wide cross-section of users as represented by the data available. Certainly, there could be more groupings, but from the data available there was too little data to create more than three holistic personas. Additionally, three were also enough to provide a consistent and actionable story without overwhelming stakeholders when we reported the study.

Persona creation is basically storytelling, so while it might be necessary to fill in gaps when creating personas, it defeats the purpose to concoct a story that is no longer rooted in the data just to create more but less accurate or false personas. For instance, due to the minimal representation from the engineering division in the data, you will see in the following sections that there is no persona with a role in engineering despite the existence of this user population; no persona is better than an inaccurate persona.

Persona Design Round 1: Storyboarding the Personas

After reviewing the data, we storyboarded the personas using six elements for each. We chose these elements based on features typically used in personas (Harley, 2015). Some basic building blocks of personas are name and tagline, a short biography, experience with the service or tool, goals and motivations, frustrations, and areas of intervention or service improvement. In this case, we centered the elements around GIS usage and in a way that other library stakeholders, who may not be knowledgeable of GIS, would be able to understand.

The elements of these personas are:

  1. Name and tagline.

  2. GIS research profile: a biography to describe their role at the institution and research background.

  3. GIS technical ability.

  4. Motivations and goals for using GIS data.

  5. Frustrations or challenges to using GIS data and tools.

  6. Helpful library interventions.

To create realistic profiles, we gave all personas a name, a faculty role within an academic division, and a background of previous knowledge or experience with GIS data and tools. While not all interviewees were faculty, all personas had at least a pseudo-faculty role, such as lecturer, for a clearer presentation because the research of faculty and non-faculty members often overlaps. In the future, one could add a postdoc or research associate persona to this series. We also used the personas to note the ways the library was already positioned to support high-level and long-term research as well as areas of potential growth and improvement.

We did not use visuals for the first round of persona design; we thought of them as text-based outlines to eventually aid in the visual design process. The initial personas are represented in Appendix B.

The three personas are Rachel the Novice, A.J. the Professor, and Jean-Paul the Big-Thinker. We chose the names and characteristics based on demographics and traits of the interviewees, what was represented in the supplemental data, and our university’s academic population. An actual user of geospatial services at the university might not fall into every category of a single persona, and there is no reason for users to directly mimic a persona. For example, a full professor asking for first-time assistance with geospatial data likely has more shared characteristics with Rachel the Novice than Jean-Paul the Big-Thinker, even though Jean-Paul is a full professor as well. Put differently, one should not assume all full professors have the same geospatial research needs as The Big-Thinker even though they share an equivalent academic rank.

Persona Design Round 2: Visual Design of the Personas

The purpose of the visual output of the personas was to convey user-information in an easily understandable format to non-GIS services providers and stakeholders in the library. The information needed to be persuasive and believable to library administrators. Most importantly, it needed to be a reference that we could return to when thinking about how to design programming and support research. An additional objective of creating personas was to provide any future librarian within the GIS program with a reliable foundation to serve the university’s diverse community of users.

We used a free, personal Canva (https://www.canva.com) account to design the personas visually. Canva is a freemium, web-based tool for design. We formatted each of the six elements within a resume template and touched them up with features such as free head-shot style photographs.

We chose the photographs to provide a sense of realism to the personas. With a free Canva account, limited head-shot style photographs were available. Nevertheless, it was important to select images that reflected the diversity of our user population. We did not settle for images of only one demographic, as it would not be reflective of all or most faculty and researchers at the university. We tried to be as inclusive as possible with the limited means available, and with each image, we chose one to reflect personality traits one might discern from looking at the image. While some researchers choose not to include images in their personas (Miklaszewicz, 2019), we chose to include them because it would be important for making the personas memorable to stakeholders.

Rachel the Novice

Rachel the Novice is represented as a younger woman. In the photo, Rachel appears smiling and happy. We chose this image for The Novice profile because the smiling face represents a sense of possibility and eagerness to learn and grow.

A.J. the Professor

A.J. the Professor is represented as a man facing the camera head-on with a knowing, confident smile. We chose this image to reflect confidence as The Professor persona is comfortable with their technical abilities and skills.

Jean-Paul the Big-Thinker

Jean-Paul the Big-Thinker is represented as an older man in a relaxed pose. The person in the image has a far-off, visionary look in the eyes to convey the long-shot ideas and big dreams heard from some of the interviewees.

Beyond the visual design, there is another difference between the first and second rounds of the personas. In round one, the geospatial technical abilities were more nuanced for each persona, but we condensed these in the final visual report. For example, in the second round, we list GIS technical skills but show a scale of ability with ArcGIS. While ArcGIS may not be the primary GIS tool for everyone, we chose it due to its brand-name familiarity among the library stakeholders. The second round, essentially, summarized the nuanced text of the first round into actionable information for colleagues and administrators to easily digest. Figures 24 show the final products.

Figure 2
Figure 2

Rachel the Novice

Figure 3
Figure 3

A.J. the Professor

Figure 4
Figure 4

Jean-Paul the Big Thinker

Presenting Personas and Integrating into Work

It’s important that persona information be disseminated to colleagues, supported by administration, and implemented in programming. To this end, we wrote an internal report that outlined the project timeline, methods, discussion of themes from the interviews, and further work to integrate the findings. At a regular meeting of librarians and department heads, the GIS librarian presented the findings to colleagues. The GIS librarian was both creator and consumer of the personas, and the feedback and ideas in the personas were integrated into annual planning. For example, we set goals of creating a new faculty geospatial data consulting program and starting a geospatial community of practice.

Discussion

Operational and UX-Related Aspects of Specialized GIS Services

Personas must serve a purpose that can answer a question: what interventions can the library offer to assist users in meeting their information needs? This study makes the case that narrow-scope personas are an effective way to visualize typical users for specialized research services, such as GIS data services. These personas conceptualize some typical interactions between a faculty member or researcher and the GIS librarian. If we can relate a faculty or doctorate-holding user to one of three personas, it is easier for us to anticipate an appropriate level of service. For instance, Jean-Paul the Big-Thinker does not need the librarian to show them basic datasets or resources because they have likely created their own datasets. On the other hand, the librarian does need to show Rachel the Novice where to find basic datasets, while A.J. the Professor might already have the dataset in mind but may need advice on adopting the best coordinate reference system for their next analysis.

The “helpful library interventions” section of the personas provided a framework for designing new services and programmatic goals. To make these interventions actionable, the GIS librarian worked with an administrative supervisor to incorporate some of them as annual goals in the library’s strategic planning. At the time of this writing, a more structured faculty consulting service is in development. Moreover, the need for more staff or student workers to assist with GIS research is now on the record in the internal report; the personas and the data we used to create them can serve as justification for additional hiring requests.

In addition to looking forward, one can use personas to validate existing successful services. One such example is the continuation of introductory GIS-skills workshops, which are tailored to meet the needs of The Novice persona. We had considered ending these workshops to support more advanced needs, but it is clearer now that they are still needed but may benefit from better marketing toward those who encompass aspects of Rachel the Novice.

Limitations and Further Research

The aim of this study was to create narrow-scope personas based on the ongoing and high-level research needs of a small research-oriented liberal arts university. While the number of interviews was adequate and in line with UX methods, a significant limitation of this study is the lack of representation from the engineering department. This might simply indicate that engineering users are not as in need of the library’s GIS services. That assumption could be problematic without data, and in the future there may be efforts to reach out again to users in the engineering division. We can update internal documentation if new data are acquired later, or we can create an additional persona specific to engineering.

Another limitation is that we studied only a subset, albeit an active and significant one, of the entire GIS research community on campus. It was logical to begin this study with users who set the GIS research agenda and plan courses, i.e., the faculty. Subsequent research could document the GIS data needs of other categories of users, such as undergraduate and graduate students, external communities, administrative users, and many more narrow user populations that the library may seek to serve.

A final limitation to acknowledge is the question of whether personas are a useful methodology at all. Without careful implementation of the methodology, it is possible for poorly developed personas to throw one off track. In this regard, Adkins et al. (2019) conducted a focus group near the final phase of their research. This is common practice to make sure personas are grounded in the reality of data collected rather than assumptions (Pruitt and Grudin, 2003). We cross-referenced the final personas with the primary interview and secondary reference data to ensure authenticity, but there could be a fully iterative approach that included additional formal focus groups, interviews, or decisive testing to reverify or modify the existing personas.

We believe the personas developed in this study currently reflect the typical faculty or high-level researchers at the university who are utilizing geospatial tools and methods. However, persona creation is an ongoing, iterative process of reevaluation to improve or extend specialized library services. In the future, we could collect more data and revisit the personas to ensure accurate representation of the user community.

References

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Appendix A Supplemental Reference Data

Engineering department:

  • Has a GIS project idea for a student and wants to talk about resources for project

  • Trouble viewing Esri basemaps in laptop, wanting to do a timelapse video of data exported from a 3d plotting software

Humanities department:

  • Plotting points in Carto. Interested in doing some analysis and preliminary mapping for a publication.

  • Talking about potential tools and approaches for using GIS in his upcoming research about historical migration in the Mediterranean

  • Working on site collection data for course. Wants to use a survey tool. Any advice for one to use that can collect audio, video, text, image, and location data. I also want to use this same collection form for a wider Heritage Map that anyone can contribute

  • question about QGIS, using it in archaeology research as opposed to ArcMap

Science department:

  • Teaches class on global climate change and requests GIS instruction/introduction for class

Social science department:

  • A while back, you showed me a google resource where I could pull up satellite data and apply supervised learning methods to that data. Can you send me a link to that? I can’t recall where to find it!

  • I am looking for data on the territory size of provinces / states (admin1) in Afghanistan, Iraq and Somalia. Do you know if there is a global database that would contain this information for these countries? I see some of this information on wikipedia but the source is unclear.

  • Datasets available on China to perform economic analysis. Seems to specifically be seeking 2010 China Data Center County-level files.

Appendix B Initial Personas

The Novice

Geospatial Research Profile: Rachel has been at NYUAD for two years and is a Faculty Fellow in the arts and humanities division. She has used geospatial tools and data in a limited way to make simple maps and even incorporated some basic concepts into a class, but she does not consider herself a daily user of GIS or geospatial data because it is not part of her daily work or title. She did take a class on it in graduate school. Rachel wants to learn more but feels overwhelmed by the task, uncertain of which tutorials to take, tools to invest in, or what may be worthwhile. She has been impressed by how her colleagues have used geospatial tools and analyses in their research and understands it is an important skill and would be beneficial to her research, especially when it comes to building a unique CV that would make her a strong candidate for future opportunities.

  • Geospatial Technical Ability

    • ◦ Web GIS

    • ◦ Basic desktop (can load a dataset and complete other functions with documentation, completed a GIS course in grad school)

    • ◦ Experience with other data analysis tools and programming languages

    • ◦ Strong research and project management skills in field of study

  • Motivations/Goals

    • ◦ Opportunities for expanding current research areas

    • ◦ Obtaining a tenure track position, promotion, extension of contract

    • ◦ Continuing to establish self in field

  • Frustrations/Challenges

    • ◦ Unsure of how to structure geospatial data and manage geospatial projects

    • ◦ Unsure of which tools to use or choose

    • ◦ Barriers to entrance on learning: many tutorials out there, but many also assume some prior knowledge. Gatekeeping.

  • Helpful library interventions

    • ◦ Continue to host introductory workshops for GIS and geospatial research

    • ◦ Offer syllabus development as a service for faculty who want to integrate data skills and/or GIS into courses

The Professor

Geospatial Research Profile: A.J. has been at NYUAD for five years and is an assistant professor on the tenure track in the social sciences department. His major research themes ask geospatial questions, and he is a nearly daily user of geospatial tools such as ArcGIS. Many of his course assignments require his students to learn and use GIS. He has a solid understanding of GIS, its importance in his field and research, and is always looking for new ways to expand his geospatial toolbox. He does not need basic assistance for getting started with GIS or seeking out data. Primarily, he needs assistance with finding obscure data and map projections and developing training and workflows for his student assistants.

  • Geospatial Technical Ability

    • ◦ Intermediate usage of ArcGIS, can perform complex analysis by following documentation

    • ◦ Data collection (such as finding sources, merging data, own field collection, and cleaning and merging messy data sometimes from varied sources)

    • ◦ Experience with R and/or Python as well as other data analysis tools used in field

  • Motivations/Goals

    • ◦ Publications

    • ◦ Become/Maintain position as leading researcher in field on these topics and applications

    • ◦ Tenure

    • ◦ Grant approval, funding

  • Frustrations/Challenges

    • ◦ Seeking out and purchasing data for research, courses

    • ◦ Identifying and working with more obscure map projections and data types

    • ◦ Developing training and workflows for research assistants

  • Helpful library and/or university interventions

    • ◦ Start a community of practice so researchers from different domains can meet

    • ◦ Offer a more structured faculty consulting service to work on agreed upon tasks and develop training materials for research assistants

The Big-Thinker

Geospatial Research Profile: Jean-Paul is a full professor in the sciences division and has been at the university for more than a decade. Many of the research scientists and assistants in his lab use geospatial tools and data, and these are fully integrated into much of the field research done by his lab. Even though his research deals in space, i.e., species in a particular area or a particular biome, he does not consider himself to be a user of GIS because his field isn’t geoscience, his work doesn’t produce many maps, and much of the nitty-gritty work is being done by his lab workers. Jean-Paul has big ideas about sharing his and his global collaborators’ research data in an open-online platform but is unclear about the software, development, and sharing environments that would encompass the online sharing, analyzing, interacting, and downloading of large datasets.

Geospatial Technical Ability

  • ◦ Experienced with programming languages and analysis and visualization tools used in field, not necessarily geospatial if at all

  • ◦ Experienced with collection data in the field and those tools needed (not necessarily geospatial or up on latest methods for collaborative geospatial data field collection, e.g., Survey123)

  • Motivations/Goals

    • ◦ Grants

    • ◦ Publications

    • ◦ Continued funding of lab or research center

    • ◦ Global recognition and collaboration

    • ◦ Create new tools, software and web applications

  • Frustrations/Challenges

    • ◦ Understanding of full-stack web and software development, particularly for GIS (e.g., databases and servers for geospatial—PostGIS, OpenGeoServer)

    • ◦ Geospatial data management systems

    • ◦ Appropriate systems and platforms for sharing geospatial data with colleagues and public

  • Helpful library and/or university interventions

    • ◦ Continue offering library partnership opportunities to share data management and archiving expertise

    • ◦ Hire student workers or staff to consult on and develop web applications and software