Cabada, E., Kurt, E., & Ward, D. (2021). Constructing a campus-wide infrastructure for virtual reality. College & Undergraduate Libraries, 0(0), 1–24. https://doi.org/10.1080/10691316.2021.1881680
As an interdisciplinary hub, academic libraries are uniquely positioned to serve the full lifecycle of immersive environment needs, from development through archiving of successful projects. As and informal learning environment that or discipline neutral and high traffic, the academic library can serve as a clearinghouse for experimentation and transmission of best practices across colleges.
these foundational questions:
1. What VR infrastructure needs do faculty and researchers have?
2. Where is campus support lagging?
3. What current partnerships exist?
4. What and where is the campus level of interest in VR?
As marketing for workshops and programs can be challenging, particularly for large institutions, data was collected on where workshop participants learned about Step Into VR. The responses show that users learned of the workshops from a variety of ways with email ( 41 % ) as the most cited method (Figure 4). These marketing emails were sent through distributed listservs that reached nearly the entire campus population. Facebook was called out specifically and represented the second largest marketing method at 29% with the library website, friends, instructors, and digital signage representing the remaining marketing channels.
While new needs continue to emerge, the typical categories of consultation support observed include:
• Recommendations on hardware selection, such as choosing the best VR headset for viewing class content
• Guidance on developing VR applications that incorporate domain-specific curricular content
• Support for curricular integration of VR
• Recommendations on 360 capture media and equipment for documenting environments or experiences, such as the GoPro Fusion and Insta360 One X
• Advice on editing workflows, including software for processing and rendering of 360 content
Alex Fogarty
p. 9
While many library patrons understand the basic concepts of recording video on a camera, 360 cameras present a large divergence from this process in several primary ways. The first is a 360 camera captures every direction at once, so there is no inherent “focus,” and no side of a scene that is not recorded. This significantly changes how someone might compose a video recording, and also adds complexity to post-production, including how to orient viewers within a scene. The second area of divergence is that many of these devices, especially the high-end versions, are recording each lens to a separate data file or memory card and these ftles need to be combined, or “stitched,” at a later time using software specific to the camera. A final concern is that data ftles for high-resolution 3 D capture can be huge, requiring both large amounts of disk space and high-end processors and graphic cards for detailed editing to occur. For example, the Insta360 Pro 2 has 6 sensors all capable of data recording at 120 Mbps for a grand total of 720 Mbps. This translates into 43.2 gigabytes of data for every minute o
In 2013, the librarians at a small academic health sciences library reevaluated their mission, vision, and strategic plan to expand their roles. The school was transitioning to a new pedagogical culture and a new building designed to emphasize interprofessional education and active learning methodologies. Subsequent efforts to implement the new strategic plan resulted in the librarians joining curriculum committees and other institutional initiatives, such as an Active Learning Task Force, and participating in faculty development workshops. This participation has increased visibility and led to new roles and opportunities for librarians.
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Reflections on an Embedded Librarianship Approach: The Challenge of Developing Disciplinary Expertise in a New Subject Area
Embedded librarianship has emerged as a user-centred approach to academic library services, requiring an in-depth understanding of the education and research priorities of students and staff. User-centred approaches require the development of disciplinary expertise and engagement with the research culture of a particular subject area. This paper details the author’s experiences in situating his practice within the discipline of pharmacy and discusses some of the challenges around the scale and sustainability of such specialised support. Regardless of the extent to which a librarian is ‘embedded’, they must see themselves as learners, too, as they develop their understanding of the disciplines they support through an ongoing process of experiencing, reflecting, conceptualising and testing in their practice.
definition: Embedded librarianship differs from traditional librarian roles in its focus on working in partnership with clients, rather than simply providing a support service (Carlson & Kneale, 2011). In this sense, embedded librarianship is user-centred rather than library-centred and requires the librarian to develop a holistic understanding of the environment in which their client groups operate.
most training materials followed a one-size-fits-all approach, where students would be taken from locating background information and textbook chapters all the way to searching for primary evidence in a bibliographic database within the same hour. Most sessions ran over time and were overloaded with content. In some instances, students complained that they had already covered this content in their previous year.
While information literacy as a construct is valued by librarians, the term’s use remains
largely restricted to the library and information science (LIS) field and might even be labelled
undiscovered country for academics (McGuinness, 2006, p. 580). Academics often consider
IL instruction as a service provided by the library and do not see librarians as partners, nor
do they see the value in integrating course-specific IL training (Derakhshan & Singh, 2010).
a spectrum of embeddedness with 5 levels (2008, p. 442), from ‘entry level’, where the librarian might collaborate on assignment development and deliver a standalone IL session, to ‘co-teaching’, where the librarian co-teaches and develops discipline-specific course materials, lectures, assessment designs and grading in collaboration with academic staff. Their findings suggest that student performance is positively related to the level of librarian involvement
phenomenographic interview methodology, where the librarian is positioned as a ‘curricular
consultant’
My note (sarcastic): whoa, what a novelty; it is repeated for two decades at SCSU, but “hot water still not invented” and the ATT still does not have neither a faculty, nor ID, but the only Ph.D. in ID just got laid off.
Hallam, Thomas and Beach illustrate that the library is not singularly responsible for developing information and digital literacies, and therefore, a collaborative approach involving a range of stakeholders including academic staff, learning designers, educational technologists and others is required
Librarianship and libraries, through the eyes of the public, have consistently been viewed as a house of books and documents where librarians help their patrons with readers’ advisory and directions. Though these elements of being a librarian exist, the stereotype of this is far from accurate. Today in 2020, Librarians perform a myriad of tasks in order to provide fluid functionality to academic, public and special collections libraries. These tasks create a multifaceted librarian where multi-departmental duties fall squarely on the shoulders of one librarian. This year’s LACUNY Institute will illustrate this multifaceted librarian to gain understanding and perspective of the reality of librarianship as we enter a new era of technology and digital scholarship.
The underlying question LACUNY Institute 2020 aims to address is what role do 21st-century librarians and library support staff play in our society? Although perceptions about librarians have changed over time, librarian stereotypes still persist. This is the case even in popular culture. For instance, Barbara Gordon, Batgirl’s alter-ego, is a librarian with a doctoral degree, yet it is often speculated that the character’s role as an information professional is part of the character’s effort to conceal her identity by working in a safe, slow-paced environment.
Librarianship is a multifaceted and creative profession. This year’s conference will highlight the different roles that librarians play in our society as librarians wear different hats. We are mentors, supervisors, activists, instructors, unofficial guidance counselors, gamers, artists, and so forth. In some instances, we may even be the “cool” professor on campus.
Paper and Panel Proposals
We are collecting individual papers and panel topic proposals pertinent to the personal and professional experience of information professionals and staff that address but are not limited to the following areas:
Activism within and outside the library
The roles of non-librarians or non-information professionals within the profession
Partnerships between libraries and communities
(In)Visibility of non-librarian and part-time workers
How our unique experiences and/or biases influence cataloging, collection development, the hiring process, etc.
How information professionals bring creativity into the profession including classrooms, reference consultations, etc.
Multiple identities within the workplace
The changing role of the library and what library workers are doing to adapt
survey of 116 directors, deans and other high level officials of academic libraries about how they feel about their library’s info technology lending programs.
data on the level of satisfaction with such programs, plans for library budget support
for these programs, and plans for new acquisitions of tablets, virtual reality
technology, laptops, digital cameras and other types of information
technology. In addition to looking at plans for the future, the report gives
detailed data on the level and nature of budgetary support for technology
lending programs over the past few years. Survey participants also comment on
which library constituencies use the programs the most.
Administrators over age 65 were much more likely than others to want to contract the program while those under age 50 were much less likely.
In general, the more sophisticated the degree offered by the college, the greater the likelihood that it had increased spending on its technology lending program over the past three years.
Art and architecture students were frequently cited as prime users of academic library technology lending programs.
Many librarians have shied away from ICT literacy, concerned that they may be asked how to format a digital document or show students how to create a formula in a spreadsheet. These technical skills focus more on a specific tool than on the underlying nature of information.
librarians have begun to use an embedded model as a way to deepen their connection with instructors and offer more systematic collection development and instruction. That is, librarians focus more on their partnerships with course instructors than on a separate library entity.
If TPACK is applied to instruction within a course, theoretically several people could be contributing this knowledge to the course. A good exercise is for librarians to map their knowledge onto TPACK.
ICT reflects the learner side of a course. However, ICT literacy can be difficult to integrate because it does not constitute a core element of any academic domain. Whereas many academic disciplines deal with key resources in their field, such as vocabulary, critical thinking, and research methodologies, they tend not to address issues of information seeking or collaboration strategies, let alone technological tools for organizing and managing information.
Instructional design for online education provides an optimal opportunity for librarians to fully collaborate with instructors.
The outcomes can include identifying the level of ICT literacy needed to achieve those learning outcomes, a task that typically requires collaboration between the librarian and the program’s faculty member. Librarians can also help faculty identify appropriate resources that students need to build their knowledge and skills. As education administrators encourage faculty to use open educational resources (OERs) to save students money, librarians can facilitate locating and evaluating relevant resources. These OERs not only include digital textbooks but also learning objects such as simulations, case studies, tutorials, and videos.
Reading online text differs from reading print both physically and cognitively. For example, students scroll down rather than turn online pages. And online text often includes hyperlinks, which can lead to deeper coverage—as well as distraction or loss of continuity of thought. Also, most online text does not allow for marginalia that can help students reflect on the content. Teachers and students often do not realize that these differences can impact learning and retention. To address this issue, librarians can suggest resources to include in the course that provide guidance on reading online.
My note – why specialist like Tom Hergert and the entire IMS is crucial for the SCSU library and librarians and how neglecting the IMS role hurts the SCSU library –
Similarly, other types of media need to be evaluated, comprehended, and interpreted in light of their critical features or “grammar.” For example, camera angles can suggest a person’s status (as in looking up to someone), music can set the metaphorical tone of a movie, and color choices can be associated with specific genres (e.g., pastels for romances or children’s literature, dark hues for thrillers). Librarians can explain these media literacy concepts to students (and even faculty) or at least suggest including resources that describe these features
My note – on years-long repetition of the disconnect between SCSU ATT, SCSU library and IMS –
instructors need to make sure that students have the technical skills to produce these products. Although librarians might understand how media impacts the representation of knowledge, they aren’t necessarily technology specialists. However, instructors and librarians can collaborate with technology specialists to provide that expertise. While librarians can locate online resources—general ones such as Lynda.com or tool-specific guidance—technology specialists can quickly identify digital resources that teach technical skills (my note: in this case IMS). My note: we do not have IDs, another years-long reminder to middle and upper management. Many instructors and librarians have not had formal courses on instructional design, so collaborations can provide an authentic means to gain competency in this process.
My note: Tom and I for years have tried to make aware SCSU about this combo –
Instructors likely have high content knowledge (CK) and satisfactory technological content knowledge (TCK) and technological knowledge (TK) for personal use. But even though newer instructors acquire pedagogical knowledge (PK), pedagogical content knowledge (PCK), and technological pedagogical knowledge (TPK) early in their careers, veteran instructors may not have received this training. The same limitations can apply to librarians, but technology has become more central in their professional lives. Librarians usually have strong one-to-one instruction skills (an aspect of PK), but until recently they were less likely to have instructional design knowledge. ICT literacy constitutes part of their CK, at least for newly minted professionals. Instructional designers are strong in TK, PK, and TPK, and the level of their CK (and TCK and TPK) will depend on their academic background. And technology specialists have the corner on TK and TCK (and hopefully TPK if they are working in educational settings), but they may not have deep knowledge about ICT literacy.
Therefore, an ideal team for ICT literacy integration consists of the instructor, the librarian, the instructional designer, and the technology specialist. Each member can contribute expertise and cross-train the teammates. Eventually, the instructor can carry the load of ICT literacy, with the benefit of specific just-in-time support from the librarian and instructional designer.
My note: I have been working for more then six years as embedded librarian in the doctoral cohort and had made aware the current library administrator (without any response) about my work, as well as providing lengthy bibliography (e.g.https://blog.stcloudstate.edu/ims/2017/08/24/embedded-librarian-qualifications/ and have had meeting with the current SOE administrator and the library administrator (without any response).
I also have delivered discussions to other institutions (https://blog.stcloudstate.edu/ims/2018/04/12/embedded-librarian-and-gamification-in-libraries/) Librarians should seriously consider TPACK as a way to embed themselves into the classroom to incorporate information and ICT literacy.
United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.
National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself, while still trying to grow economies in the wake of the 2008 financial crisis and subsequent financial pressures
African digital literacy is more business-oriented.
Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming material from abroad, which may elicit criticism of neocolonialism or religious challenges.
p. 14 Digital literacy for Humanities: What does it mean to be digitally literate in history, literature, or philosophy? Creativity in these disciplines often involves textuality, given the large role writing plays in them, as, for example, in the Folger Shakespeare Library’s instructor’s guide. In the digital realm, this can include web-based writing through social media, along with the creation of multimedia projects through posters, presentations, and video. Information literacy remains a key part of digital literacy in the humanities. The digital humanities movement has not seen much connection with digital literacy, unfortunately, but their alignment seems likely, given the turn toward using digital technologies to explore humanities questions. That development could then foster a spread of other technologies and approaches to the rest of the humanities, including mapping, data visualization, text mining, web-based digital archives, and “distant reading” (working with very large bodies of texts). The digital humanities’ emphasis on making projects may also increase
Digital Literacy for Business: Digital literacy in this world is focused on manipulation of data, from spreadsheets to more advanced modeling software, leading up to degrees in management information systems. Management classes unsurprisingly focus on how to organize people working on and with digital tools.
Digital Literacy for Computer Science: Naturally, coding appears as a central competency within this discipline. Other aspects of the digital world feature prominently, including hardware and network architecture. Some courses housed within the computer science discipline offer a deeper examination of the impact of computing on society and politics, along with how to use digital tools. Media production plays a minor role here, beyond publications (posters, videos), as many institutions assign multimedia to other departments. Looking forward to a future when automation has become both more widespread and powerful, developing artificial intelligence projects will potentially play a role in computer science literacy.
In traditional instruction, students’ first contact with new ideas happens in class, usually through direct instruction from the professor; after exposure to the basics, students are turned out of the classroom to tackle the most difficult tasks in learning — those that involve application, analysis, synthesis, and creativity — in their individual spaces. Flipped learning reverses this, by moving first contact with new concepts to the individual space and using the newly-expanded time in class for students to pursue difficult, higher-level tasks together, with the instructor as a guide.
Let’s take a look at some of the myths about flipped learning and try to find the facts.
Myth: Flipped learning is predicated on recording videos for students to watch before class.
Fact: Flipped learning does not require video. Although many real-life implementations of flipped learning use video, there’s nothing that says video must be used. In fact, one of the earliest instances of flipped learning — Eric Mazur’s peer instruction concept, used in Harvard physics classes — uses no video but rather an online text outfitted with social annotation software. And one of the most successful public instances of flipped learning, an edX course on numerical methods designed by Lorena Barba of George Washington University, uses precisely one video. Video is simply not necessary for flipped learning, and many alternatives to video can lead to effective flipped learning environments [http://rtalbert.org/flipped-learning-without-video/].
Fact: Flipped learning optimizes face-to-face teaching. Flipped learning may (but does not always) replace lectures in class, but this is not to say that it replaces teaching. Teaching and “telling” are not the same thing.
Myth: Flipped learning has no evidence to back up its effectiveness.
Fact: Flipped learning research is growing at an exponential pace and has been since at least 2014. That research — 131 peer-reviewed articles in the first half of 2017 alone — includes results from primary, secondary, and postsecondary education in nearly every discipline, most showing significant improvements in student learning, motivation, and critical thinking skills.
Myth: Flipped learning is a fad.
Fact: Flipped learning has been with us in the form defined here for nearly 20 years.
Myth: People have been doing flipped learning for centuries.
Fact: Flipped learning is not just a rebranding of old techniques. The basic concept of students doing individually active work to encounter new ideas that are then built upon in class is almost as old as the university itself. So flipped learning is, in a real sense, a modern means of returning higher education to its roots. Even so, flipped learning is different from these time-honored techniques.
Myth: Students and professors prefer lecture over flipped learning.
Fact: Students and professors embrace flipped learning once they understand the benefits. It’s true that professors often enjoy their lectures, and students often enjoy being lectured to. But the question is not who “enjoys” what, but rather what helps students learn the best.They know what the research says about the effectiveness of active learning
Assertion: Flipped learning provides a platform for implementing active learning in a way that works powerfully for students.
The Exposure Approach: we don’t provide a way for participants to determine if they learned anything new or now have the confidence or competence to apply what they learned.
The Exemplar Approach: from ‘show and tell’ for adults to show, tell, do and learn.
The Tutorial Approach: Getting a group that can meet at the same time and place can be challenging. That is why many faculty report a preference for self-paced professional development.build in simple self-assessment checks. We can add prompts that invite people to engage in some sort of follow up activity with a colleague. We can also add an elective option for faculty in a tutorial to actually create or do something with what they learned and then submit it for direct or narrative feedback.
The Course Approach: a non-credit format, these have the benefits of a more structured and lengthy learning experience, even if they are just three to five-week short courses that meet online or in-person once every week or two.involve badges, portfolios, peer assessment, self-assessment, or one-on-one feedback from a facilitator
The Academy Approach: like the course approach, is one that tends to be a deeper and more extended experience. People might gather in a cohort over a year or longer.Assessment through coaching and mentoring, the use of portfolios, peer feedback and much more can be easily incorporated to add a rich assessment element to such longer-term professional development programs.
The Mentoring Approach: The mentors often don’t set specific learning goals with the mentee. Instead, it is often a set of structured meetings, but also someone to whom mentees can turn with questions and tips along the way.
The Coaching Approach: A mentor tends to be a broader type of relationship with a person.A coaching relationship tends to be more focused upon specific goals, tasks or outcomes.
The Peer Approach:This can be done on a 1:1 basis or in small groups, where those who are teaching the same courses are able to compare notes on curricula and teaching models. They might give each other feedback on how to teach certain concepts, how to write syllabi, how to handle certain teaching and learning challenges, and much more. Faculty might sit in on each other’s courses, observe, and give feedback afterward.
The Self-Directed Approach:a self-assessment strategy such as setting goals and creating simple checklists and rubrics to monitor our progress. Or, we invite feedback from colleagues, often in a narrative and/or informal format. We might also create a portfolio of our work, or engage in some sort of learning journal that documents our thoughts, experiments, experiences, and learning along the way.
In 2014, administrators at Central Piedmont Community College (CPCC) in Charlotte, North Carolina, began talks with members of the North Carolina State Board of Community Colleges and North Carolina Community College System (NCCCS) leadership about starting a CBE program.
Building on an existing project at CPCC for identifying the elements of a digital learning environment (DLE), which was itself influenced by the EDUCAUSE publication The Next Generation Digital Learning Environment: A Report on Research,1 the committee reached consensus on a DLE concept and a shared lexicon: the “Digital Learning Environment Operational Definitions,
2018 Special Focus: Education in a Time of Austerity and Social Turbulence 21–23 June 2018 University of Athens, Athens, Greece http://thelearner.com/2018-conference
Theme 8: Technologies in Learning
Technology and human values: learning through and about technology
Crossing the digital divide: access to learning in, and about, the digital world
New tools for learning: online digitally mediated learning
Virtual worlds, virtual classrooms: interactive, self-paced and autonomous learning
Ubiquitous learning: using the affordances of the new mediaDistance learning: reducing the distance
Theme 9: Literacies Learning
Defining new literacies
Languages of power: literacy’s role in social access
Instructional responses to individual differences in literacy learning
The visual and the verbal: Multiliteracies and multimodal communications
Literacy in learning: language in learning across the subject areas
The changing role of libraries in literacies learning
Languages education and second language learning
Multilingual learning for a multicultural world
The arts and design in multimodal learning
The computer, internet, and digital media: educational challenges and responses
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PROPOSAL: Paper presentation in a Themed Session
Title
Virtual Reality and Gamification in the Educational Process: The Experience from an Academic Library
short description
VR, AR and Mixed Reality, as well as gaming and gamification are proposed as sandbox opportunity to transition from a lecture-type instruction to constructivist-based methods.
long description
The NMC New Horizon Report 2017 predicts a rapid application of Video360 in K12. Millennials are leaving college, Gen Z students are our next patrons. Higher Education needs to meet its new students on “their playground.” A collaboration by a librarian and VR specialist is testing the opportunities to apply 360 degree movies and VR in academic library orientation. The team seeks to bank on the inheriting interest of young patrons toward these technologies and their inextricable part of a rapidly becoming traditional gaming environment. A “low-end,” inexpensive and more mobile Google Cardboard solution was preferred to HTC Vive, Microsoft HoloLens or comparable hi-end VR, AR and mixed reality products.
The team relies on the constructivist theory of assisting students in building their knowledge in their own pace and on their own terms, rather than being lectured and/or being guided by a librarian during a traditional library orientation tour. Using inexpensive Google Cardboard goggles, students can explore a realistic set up of the actual library and familiarize themselves with its services. Students were polled on the effectiveness of such approach as well as on their inclination to entertain more comprehensive version of library orientation. Based on the lessons from this experiment, the team intends to pursue also a standardized approach to introducing VR to other campus services, thus bringing down further the cost of VR projects on campus. The project is considered a sandbox for academic instruction across campus. The same concept can be applied for [e.g., Chemistry, Physics, Biology) lab tours; for classes, which anticipate preliminary orientation process.
Following the VR orientation, the traditional students’ library instruction, usually conducted in a room, is replaced by a dynamic gamified library instruction. Students are split in groups of three and conduct a “scavenger hunt”; students use a jQuery-generated Web site on their mobile devices to advance through “hoops” of standard information literacy test. E.g., they need to walk to the Reference Desk, collect specific information and log their findings in the Web site. The idea follows the strong interest in the educational world toward gaming and gamification of the educational process. This library orientation approach applies the three principles for gamification: empowers learners; teaches problem solving and increases understanding.
Similarly to the experience with VR for library orientation, this library instruction process is used as a sandbox and has been successfully replicated by other instructors in their classes.
Applications for the 2018 Institute will be accepted between December 1, 2017 and January 27, 2018. Scholars accepted to the program will be notified in early March 2018.
Title:
Learning to Harness Big Data in an Academic Library
Abstract (200)
Research on Big Data per se, as well as on the importance and organization of the process of Big Data collection and analysis, is well underway. The complexity of the process comprising “Big Data,” however, deprives organizations of ubiquitous “blue print.” The planning, structuring, administration and execution of the process of adopting Big Data in an organization, being that a corporate one or an educational one, remains an elusive one. No less elusive is the adoption of the Big Data practices among libraries themselves. Seeking the commonalities and differences in the adoption of Big Data practices among libraries may be a suitable start to help libraries transition to the adoption of Big Data and restructuring organizational and daily activities based on Big Data decisions. Introduction to the problem. Limitations
The redefinition of humanities scholarship has received major attention in higher education. The advent of digital humanities challenges aspects of academic librarianship. Data literacy is a critical need for digital humanities in academia. The March 2016 Library Juice Academy Webinar led by John Russel exemplifies the efforts to help librarians become versed in obtaining programming skills, and respectively, handling data. Those are first steps on a rather long path of building a robust infrastructure to collect, analyze, and interpret data intelligently, so it can be utilized to restructure daily and strategic activities. Since the phenomenon of Big Data is young, there is a lack of blueprints on the organization of such infrastructure. A collection and sharing of best practices is an efficient approach to establishing a feasible plan for setting a library infrastructure for collection, analysis, and implementation of Big Data.
Limitations. This research can only organize the results from the responses of librarians and research into how libraries present themselves to the world in this arena. It may be able to make some rudimentary recommendations. However, based on each library’s specific goals and tasks, further research and work will be needed.
Big Data is becoming an omnipresent term. It is widespread among different disciplines in academia (De Mauro, Greco, & Grimaldi, 2016). This leads to “inconsistency in meanings and necessity for formal definitions” (De Mauro et al, 2016, p. 122). Similarly, to De Mauro et al (2016), Hashem, Yaqoob, Anuar, Mokhtar, Gani and Ullah Khan (2015) seek standardization of definitions. The main connected “themes” of this phenomenon must be identified and the connections to Library Science must be sought. A prerequisite for a comprehensive definition is the identification of Big Data methods. Bughin, Chui, Manyika (2011), Chen et al. (2012) and De Mauro et al (2015) single out the methods to complete the process of building a comprehensive definition.
In conjunction with identifying the methods, volume, velocity, and variety, as defined by Laney (2001), are the three properties of Big Data accepted across the literature. Daniel (2015) defines three stages in big data: collection, analysis, and visualization. According to Daniel, (2015), Big Data in higher education “connotes the interpretation of a wide range of administrative and operational data” (p. 910) and according to Hilbert (2013), as cited in Daniel (2015), Big Data “delivers a cost-effective prospect to improve decision making” (p. 911).
The importance of understanding the process of Big Data analytics is well understood in academic libraries. An example of such “administrative and operational” use for cost-effective improvement of decision making are the Finch & Flenner (2016) and Eaton (2017) case studies of the use of data visualization to assess an academic library collection and restructure the acquisition process. Sugimoto, Ding & Thelwall (2012) call for the discussion of Big Data for libraries. According to the 2017 NMC Horizon Report “Big Data has become a major focus of academic and research libraries due to the rapid evolution of data mining technologies and the proliferation of data sources like mobile devices and social media” (Adams, Becker, et al., 2017, p. 38).
Power (2014) elaborates on the complexity of Big Data in regard to decision-making and offers ideas for organizations on building a system to deal with Big Data. As explained by Boyd and Crawford (2012) and cited in De Mauro et al (2016), there is a danger of a new digital divide among organizations with different access and ability to process data. Moreover, Big Data impacts current organizational entities in their ability to reconsider their structure and organization. The complexity of institutions’ performance under the impact of Big Data is further complicated by the change of human behavior, because, arguably, Big Data affects human behavior itself (Schroeder, 2014).
De Mauro et al (2015) touch on the impact of Dig Data on libraries. The reorganization of academic libraries considering Big Data and the handling of Big Data by libraries is in a close conjunction with the reorganization of the entire campus and the handling of Big Data by the educational institution. In additional to the disruption posed by the Big Data phenomenon, higher education is facing global changes of economic, technological, social, and educational character. Daniel (2015) uses a chart to illustrate the complexity of these global trends. Parallel to the Big Data developments in America and Asia, the European Union is offering access to an EU open data portal (https://data.europa.eu/euodp/home ). Moreover, the Association of European Research Libraries expects under the H2020 program to increase “the digitization of cultural heritage, digital preservation, research data sharing, open access policies and the interoperability of research infrastructures” (Reilly, 2013).
The challenges posed by Big Data to human and social behavior (Schroeder, 2014) are no less significant to the impact of Big Data on learning. Cohen, Dolan, Dunlap, Hellerstein, & Welton (2009) propose a road map for “more conservative organizations” (p. 1492) to overcome their reservations and/or inability to handle Big Data and adopt a practical approach to the complexity of Big Data. Two Chinese researchers assert deep learning as the “set of machine learning techniques that learn multiple levels of representation in deep architectures (Chen & Lin, 2014, p. 515). Deep learning requires “new ways of thinking and transformative solutions (Chen & Lin, 2014, p. 523). Another pair of researchers from China present a broad overview of the various societal, business and administrative applications of Big Data, including a detailed account and definitions of the processes and tools accompanying Big Data analytics. The American counterparts of these Chinese researchers are of the same opinion when it comes to “think about the core principles and concepts that underline the techniques, and also the systematic thinking” (Provost and Fawcett, 2013, p. 58). De Mauro, Greco, and Grimaldi (2016), similarly to Provost and Fawcett (2013) draw attention to the urgent necessity to train new types of specialists to work with such data. As early as 2012, Davenport and Patil (2012), as cited in Mauro et al (2016), envisioned hybrid specialists able to manage both technological knowledge and academic research. Similarly, Provost and Fawcett (2013) mention the efforts of “academic institutions scrambling to put together programs to train data scientists” (p. 51). Further, Asomoah, Sharda, Zadeh & Kalgotra (2017) share a specific plan on the design and delivery of a big data analytics course. At the same time, librarians working with data acknowledge the shortcomings in the profession, since librarians “are practitioners first and generally do not view usability as a primary job responsibility, usually lack the depth of research skills needed to carry out a fully valid” data-based research (Emanuel, 2013, p. 207).
Borgman (2015) devotes an entire book to data and scholarly research and goes beyond the already well-established facts regarding the importance of Big Data, the implications of Big Data and the technical, societal, and educational impact and complications posed by Big Data. Borgman elucidates the importance of knowledge infrastructure and the necessity to understand the importance and complexity of building such infrastructure, in order to be able to take advantage of Big Data. In a similar fashion, a team of Chinese scholars draws attention to the complexity of data mining and Big Data and the necessity to approach the issue in an organized fashion (Wu, Xhu, Wu, Ding, 2014).
Bruns (2013) shifts the conversation from the “macro” architecture of Big Data, as focused by Borgman (2015) and Wu et al (2014) and ponders over the influx and unprecedented opportunities for humanities in academia with the advent of Big Data. Does the seemingly ubiquitous omnipresence of Big Data mean for humanities a “railroading” into “scientificity”? How will research and publishing change with the advent of Big Data across academic disciplines?
Reyes (2015) shares her “skinny” approach to Big Data in education. She presents a comprehensive structure for educational institutions to shift “traditional” analytics to “learner-centered” analytics (p. 75) and identifies the participants in the Big Data process in the organization. The model is applicable for library use.
Being a new and unchartered territory, Big Data and Big Data analytics can pose ethical issues. Willis (2013) focusses on Big Data application in education, namely the ethical questions for higher education administrators and the expectations of Big Data analytics to predict students’ success. Daries, Reich, Waldo, Young, and Whittinghill (2014) discuss rather similar issues regarding the balance between data and student privacy regulations. The privacy issues accompanying data are also discussed by Tene and Polonetsky, (2013).
Privacy issues are habitually connected to security and surveillance issues. Andrejevic and Gates (2014) point out in a decision making “generated by data mining, the focus is not on particular individuals but on aggregate outcomes” (p. 195). Van Dijck (2014) goes into further details regarding the perils posed by metadata and data to the society, in particular to the privacy of citizens. Bail (2014) addresses the same issue regarding the impact of Big Data on societal issues, but underlines the leading roles of cultural sociologists and their theories for the correct application of Big Data.
Library organizations have been traditional proponents of core democratic values such as protection of privacy and elucidation of related ethical questions (Miltenoff & Hauptman, 2005). In recent books about Big Data and libraries, ethical issues are important part of the discussion (Weiss, 2018). Library blogs also discuss these issues (Harper & Oltmann, 2017). An academic library’s role is to educate its patrons about those values. Sugimoto et al (2012) reflect on the need for discussion about Big Data in Library and Information Science. They clearly draw attention to the library “tradition of organizing, managing, retrieving, collecting, describing, and preserving information” (p.1) as well as library and information science being “a historically interdisciplinary and collaborative field, absorbing the knowledge of multiple domains and bringing the tools, techniques, and theories” (p. 1). Sugimoto et al (2012) sought a wide discussion among the library profession regarding the implications of Big Data on the profession, no differently from the activities in other fields (e.g., Wixom, Ariyachandra, Douglas, Goul, Gupta, Iyer, Kulkami, Mooney, Phillips-Wren, Turetken, 2014). A current Andrew Mellon Foundation grant for Visualizing Digital Scholarship in Libraries seeks an opportunity to view “both macro and micro perspectives, multi-user collaboration and real-time data interaction, and a limitless number of visualization possibilities – critical capabilities for rapidly understanding today’s large data sets (Hwangbo, 2014).
The importance of the library with its traditional roles, as described by Sugimoto et al (2012) may continue, considering the Big Data platform proposed by Wu, Wu, Khabsa, Williams, Chen, Huang, Tuarob, Choudhury, Ororbia, Mitra, & Giles (2014). Such platforms will continue to emerge and be improved, with librarians as the ultimate drivers of such platforms and as the mediators between the patrons and the data generated by such platforms.
Every library needs to find its place in the large organization and in society in regard to this very new and very powerful phenomenon called Big Data. Libraries might not have the trained staff to become a leader in the process of organizing and building the complex mechanism of this new knowledge architecture, but librarians must educate and train themselves to be worthy participants in this new establishment.
Method
The study will be cleared by the SCSU IRB.
The survey will collect responses from library population and it readiness to use and use of Big Data. Send survey URL to (academic?) libraries around the world.
Data will be processed through SPSS. Open ended results will be processed manually. The preliminary research design presupposes a mixed method approach.
The study will include the use of closed-ended survey response questions and open-ended questions. The first part of the study (close ended, quantitative questions) will be completed online through online survey. Participants will be asked to complete the survey using a link they receive through e-mail.
Mixed methods research was defined by Johnson and Onwuegbuzie (2004) as “the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts, or language into a single study” (Johnson & Onwuegbuzie, 2004 , p. 17). Quantitative and qualitative methods can be combined, if used to complement each other because the methods can measure different aspects of the research questions (Sale, Lohfeld, & Brazil, 2002).
Sampling design
Online survey of 10-15 question, with 3-5 demographic and the rest regarding the use of tools.
1-2 open-ended questions at the end of the survey to probe for follow-up mixed method approach (an opportunity for qualitative study)
data analysis techniques: survey results will be exported to SPSS and analyzed accordingly. The final survey design will determine the appropriate statistical approach.
Project Schedule
Complete literature review and identify areas of interest – two months
Prepare and test instrument (survey) – month
IRB and other details – month
Generate a list of potential libraries to distribute survey – month
Contact libraries. Follow up and contact again, if necessary (low turnaround) – month
Collect, analyze data – two months
Write out data findings – month
Complete manuscript – month
Proofreading and other details – month
Significance of the work
While it has been widely acknowledged that Big Data (and its handling) is changing higher education (https://blog.stcloudstate.edu/ims?s=big+data) as well as academic libraries (https://blog.stcloudstate.edu/ims/2016/03/29/analytics-in-education/), it remains nebulous how Big Data is handled in the academic library and, respectively, how it is related to the handling of Big Data on campus. Moreover, the visualization of Big Data between units on campus remains in progress, along with any policymaking based on the analysis of such data (hence the need for comprehensive visualization).
This research will aim to gain an understanding on: a. how librarians are handling Big Data; b. how are they relating their Big Data output to the campus output of Big Data and c. how librarians in particular and campus administration in general are tuning their practices based on the analysis.
Based on the survey returns (if there is a statistically significant return), this research might consider juxtaposing the practices from academic libraries, to practices from special libraries (especially corporate libraries), public and school libraries.
References:
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Vicky Steeves (@VickySteeves) is the first Research Data Management and Reproducibility Librarian
Reproducibility is made so much more challenging because of computers, and the dominance of closed-source operating systems and analysis software researchers use. Ben Marwick wrote a great piece called ‘How computers broke science – and what we can do to fix it’ which details a bit of the problem. Basically, computational environments affect the outcome of analyses (Gronenschild et. al (2012) showed the same data and analyses gave different results between two versions of macOS), and are exceptionally hard to reproduce, especially when the license terms don’t allow it. Additionally, programs encode data incorrectly and studies make erroneous conclusions, e.g. Microsoft Excel encodes genes as dates, which affects 1/5 of published data in leading genome journals.
technology to capture computational environments, workflow, provenance, data, and code are hugely impactful for reproducibility. It’s been the focus of my work, in supporting an open source tool called ReproZip, which packages all computational dependencies, data, and applications in a single distributable package that other can reproduce across different systems. There are other tools that fix parts of this problem: Kepler and VisTrails for workflow/provenance, Packrat for saving specific R packages at the time a script is run so updates to dependencies won’t break, Pex for generating executable Python environments, and o2r for executable papers (including data, text, and code in one).
a plugin for Jupyter notebooks), and added a user interface to make it friendlier to folks not comfortable on the command line.
