•    Did your graduate program include training in curating or managing data? Wondering what it means? Researchers need better online collaboration tools that provide more sophisticated access controls and can support the volume of data generated. To see to big data acceptance even more, the implementation and use of the new big data solution need to be monitored and controlled. As a result, popular fields may be overstudied while other lines of inquiry may be neglected entirely. •    Difficulty maintaining organizational structure of files, insufficient time for organizational tasks, •    Images: TIFF, raw, JPEG, KML (for display of geographic data) Lawson adds, “As it turns out, data governance doesn’t have to be this all-encompassing, massive project. We would like to thank the Alfred P. Sloan Foundation for its generous funding, which enabled us to carry out this study. If not, does another staff member fulfill this role? The digital curator said that while the data have been prepared thus far principally for other researchers and therefore require an understanding of geological fieldwork to be meaningful, he envisions an “interactive geologic map” that would be useful to a wide audience. •    Data curation systems should be integrated with the active research phase (i.e., as a backup and collaboration solution). Data integrity can be ensured when sufficient measures are in place. •    How are the data named/numbered, etc.? A “think globally, act locally” approach is what organizations need to follow. •    Archeology in the Gordian region, Turkey (and collaboration with civil rights nongovernmental organization), Collaboration •    Cognitive development in children, using eye tracking equipment Universities should consider amending these policies to reflect the reality of multi-institutional research teams. 2010. a.    There is unlikely to be a single out-of-the-box solution that can be applied to the problem of data preservation. Not allowing business needs to drive data and cloud strategy. Fox, Peter, and James Hendler. Among the participants in this study, the scale of research data ranged from under 1 GB to multiple terabytes. Pixilation on lower resolution images renders them unusable, making very large files (up to 60–65 GB per section) necessary. Aiming to resolve all your data problems in the initial phase of data management invites trouble. 3. •    Does your university or library offer any services to help you with curating your data? What problems do you see when using big data analytics/technologies? If so, when do you expect it to be completed? •    What kind of data sources did you use in this project? Personal Practices and Training: The thin sections also posed difficulties, because the images needed enough resolution to allow researchers to measure 200–500 grains of the mineral. Without sufficient attention to the context of data aggregated from an array of fields, we run the risk of promoting facile interpretations of the relationship between human biology and behavior, and of human nature itself. •    STATA Data preservation strategies not only must take into account these varied, proprietary, and non-standard data formats, but also must provide a real-time benefit for the scholar in meeting research goals. As Mathews and colleagues note, “Simple notions of access are substantially complicated by shifting boundaries between what is considered information versus material, person versus artifact, and private property versus the public domain” (2011, 725). (2010). It has been seen that organizations have recognized the importance of big data and are treating data as an asset (probably one of the most valuable of all due to its ability to decide growth trajectory and ability to offer a competitive advantage over competitors), but have failed to draw any fruitful insights from it. There is a clear need for libraries to move beyond passively providing technology to embrace the changes in scholarly production that emerging technologies have brought. •    How did the training influence the way you conducted your research? Although some researchers acknowledge that their data could be useful to other researchers, there is little incentive to invest time in archiving or repackaging data sets. With big data… •    Indian legal history and the British Empire The interviews focused on how the researchers collect and analyze data; how they manage, preserve, and archive these data; and what training they have had in data curation practices (Appendix B). The goals of the study were to identify barriers to data curation, to recognize unmet researcher needs within the university environment, and to gain a holistic understanding of the workflows involved in the creation, management, and preservation of research data. However, metadata are not always held at every level of the file structure, and the members of the research team must consult the tracking spreadsheet, which sometimes creates confusion. So managing this kind of restricted access is difficult, especially for social scientists when they don’t have multimillion dollar grants. Metadata and documentation are of interest only if they help a researcher complete his or her work. Altman, Micah, and Gary King. •    Inadequate online collaboration space Our findings and recommendations are as follows: 1.    An approach that emphasizes early engagement with researchers and dialog around finding/building the appropriate tools to manage data for a particular project/researcher is likely to be the most productive. In-depth data profiling right at the start of the project ensures that less time is spent to make updates to the data cleaning portion of the ETL in the future. Participant #2-12-111011 is an assistant professor of environmental science who studies environmental politics and protests in Kyrgyzstan. 2011. In other cases, the dispersal of data reflects idiosyncratic work habits with insufficient time for organizational tasks. •    How did you become involved in this project? •    What software (if any) did you use? The protective attitude toward research data might also lead (or even require) researchers to neglect metadata and secondary materials (e.g., codebooks, explanatory materials, finding aids, ontologies) that are necessary to ensure the long-term usefulness of primary data. •    Educational or other training programs should focus on early intervention in the researcher career path for the greatest long-term benefit. 2006; Smail 2008). •    Systems and infrastructure overwhelmed by scale of data Science 332(6025): 60-65. Transcription files have been managed by means of flash drives and Google Docs. The program approach is the best fit for data governance in which one would be allowed to define a series of project streams that focus on one key area. It may not be until the active research phase that data collection is systematic, although changes in protocol may occur even during this phase. Here are four of the top pain points that businesses are experiencing with data management—and how to overcome them: 1. 10/22/1999, 10/28/1999, 4/9/2000 1.3 Specific Objectives of Data Management The specific objectives of data management are: 1.3.1 Acquire data and prepare them for analysis The data management system includes the overview of the flow of data from research subjects to data … •    Inter-university Consortium for Political and Social Research (ICPSR) archive (Participant #5-11-103111) Citation and Peer Review of Data: Moving Towards Formal Data Publication. After another good introduction to Mobile Computing it •    What kinds of primary sources did you use? Pool, Ithiel de Sola. •    Little or no training, learning as needed throughout research Efficient entry of analog data does not require any specialized skills beyond keyboarding accuracy, while effective digital data management requires both expertise and labor continuity that is not readily found in a pool of transient research assistants. The American Psychologist 63(7): 602-614. For this reason, file formats, as well as the software and hardware platforms used to manage and manipulate data, tend to proliferate. Evans and Foster (2011) argue that a meta-analysis of research findings (i.e., publications) could identify overstudied fields where continued research has diminishing returns, thus helping individuals make better decisions about research investment. Additionally, university policies that appropriately address the ethical considerations relating to data sharing and preservation would benefit researchers, administrators, and technologists alike. Data Governance is a growing challenge as more data moves from on-premise to cloud locations and governmental and industry regulations, particularly regarding the use of personal data. CC BY-SA 4.0 License, National Digital Stewardship Residency (NDSR) Assessment, Mellon Fellowships for Dissertation Research in Original Sources, Chief Information Officers in Liberal Arts Colleges, Digitizing Hidden Special Collections and Archives, Mellon Fellowships for Dissertation Research, http://classifications.carnegiefoundation.org/, Biological Anthropology, Archaeology, Sociology Education, Slavic Languages, Psychology, Education, Political Science, Architectural History, Political Science, Sociology, Environmental Science, International Relations, Anthropology, Sociology and Public Policy, Applied Mathematics, Geology (data scientist), Sociology, Anthropology. Science 331(6018): 714–717. The goal of this project was to preserve and present as much of the material online as possible, and several types of materials presented particular difficulties. For example, synthesizing social science, ecological, and hydrological data could help society cope with climate change (Overpeck et al. It would be particularly problematical if each collaborator is working under a sponsored project in which their institutions are responsible for data management. In the field of neuroscience, for example, Akil and colleagues (2011) suggest that integrating neural connectivity data with behavioral phenotype data (e.g., IQ scores) will provide new insight into the spatial organization and function of the human brain. Tracking the Flow of Information. Characteristics of research sites included in this study. •    Learning among children within an online environment •    Have you had training in data curation? Importantly, because the researchers themselves could not always predict which data would be useful in the future (either for themselves or for other researchers), they were unsure which data should be preserved and what contextual information should be included with the data. 2011), design better cities (Gur et al. •    Did the timing seem appropriate for your work? In particular, she observed that she has a weak and nonsystematic backup plan for her data, relying principally on multiple personal computers and external hard drives. The numerical data are analyzed in SPSS and Excel. The need to share files among researchers at multiple universities has also created problems. If data are not to be disseminated, these aids are often unnecessary to individuals or small groups of researchers. The researchers are not naïve; they understand that poor data management can be costly to their research and that access to greater technical expertise, through either a consultant or additional training, would be useful for their work. None of the scholars interviewed during this study expressed satisfaction with their level of expertise in data management, and few had access to individuals who could provide knowledgeable guidance. Platforms that could provide both a workspace and a preservation space would add significant value for scholars. •    Audio: wav, mp3, analog tape Carnegie Foundation for the Advancement of Teaching. •    What were the goals of this project? Researchers need no longer stretch a limited supplies budget to cover the high cost of film and, without this restriction, may be less judicious with their documentation. Quantitative results are stored in Excel and SPSS files, while the audio recordings are in the process of being transcribed. Thing 2: Issues in research data management Research data is for everyone. •    Excel Science 331(6018): 705–708. Finally, it is likely that a data specialist will need to function as an advocate for researchers within the local systems. Challenges and Opportunities for Genomic Developmental Neuropsychology: Examples from the Penn-Drexel Collaborative Battery. Not only are necessary metadata and other materials much more easily captured while research is in progress, but also there is a real opportunity to streamline research workflows and to provide much needed support. * Information from Carnegie Foundation for the Advancement of Teaching (2010). c.    Small- to medium-sized research teams and single researchers are likely to have the greatest unmet need, because they typically lack the resources of major research initiatives to hire data professionals. Taking a reactive approach to data management. Mathews, Debra J. H., Gregory D. Graff, Krishanu Saha, and David E. Winickoff. Data Management managers manage these changes, b… •    The demands of publication output overwhelm long-term considerations of data curation. Because she works in three languages (Kyrgyz, Russian, and English), the researcher has had difficulties hiring and training transcriptionists, and the transcription of her interviews has taken several years to complete. We conducted ethnographic interviews with faculty, postdoctoral fellows, graduate students, and other researchers in a variety of social sciences disciplines. Framing data ingestion with the research questions would facilitate linking the research findings to the analysis and observations. Data management is the upkeep of records, information, and data. Thoughtfully integrated pools of data could also promote transparency in research (Gur et al. Science 331(6018): 708–712. •    Some data considered proprietary by collection holders (museum collections) One of the main challenges is to have all the business information available. Arguments aimed at convincing researchers to think about long-term data preservation for its own sake are not likely to be effective. However, it was only after 2000 that digital storage formats became a significant portion of total storage media, and by 2007, 94 percent of technological memory was in digital format (Hilbert and López 2011). Although this project has both an NSF data management plan and a physical anthropology data-sharing plan (a standard in physical anthropology for a number of years), several factors limit the effective reuse of the project’s research data. As data is unpredictable and can change anytime, flexibility in the dataset is essential. 2007. For non-American studies the rate was even higher, 80 percent (Arnett 2008, 604). On the contrary, most participants reported feeling adrift when establishing protocols for managing their data and added that they lacked the resources to determine best practices, let alone to implement them. For example, when the project needed chimpanzee bones to use for comparison with human bones, the researchers could not obtain samples locally. •    What are the products/outcomes of your work? In what format? For example, Participant #2-12-111011, Assistant Professor, Environmental Studies collected data on graffiti during fieldwork and then donated the data to another researcher (see Appendix C, case study #3). The transition to digital data collection has altered scholarly workflows. Background: Data sharing Recently Forbes said that organizations are keen to spend on big data app development to manage the huge volume of information created where 40% of these apps are customer-facing. •    During what phase of your research development did you receive this training? None of the researchers interviewed for this study had received formal training in data management practices. Proceedings of the National Academy of Sciences of the United States of America 103(13): 4940–4945. When embarking on data management, the key to success lies in the belief that it is an ongoing process and hence start small. •    Uneven access to university infrastructure (e.g., Participant #4-25-120511 reported that undergraduates and graduate students on a project do not have the same privileges as senior project members for network storage). This doubt contributes to scholars’ reluctance to allocate time to data preservation and annotation. As big data applications are expanding at a much faster pace, more and more businesses are choosing the path of digital transformation to maintain relevancy and stay abreast with the current trends. c.    Researchers are unlikely to engage with those they do not view as peers. A Proposed Standard for the Scholarly Citation of Quantitative Data. hybrid cloud, or hybrid Data Management systems must be able to communicate with each other about where data … The best-case scenario encountered during this study was a project at Penn State University that emphasizes ontology development at the beginning of the research process. Rzhetsky, Andrey, Ivan Iossifov, Ji Meng Loh, and Kevin P. White. This situation can be avoided when you ensure that the applications are maintained and updated on time without fail. Carnegie Classification of Institutions of Higher Education. You will be able to bag maximum benefit out of it when you choose to invest in it. Given the nature of the academic system, which offers little or no career reward for preserving one’s data, this is not surprising. Science 331(6018): 725–727. Another situation might arise if the principal investigator simply does not dedicate the appropriate time and effort to fulfill responsibilities related to proper data management. The organization of digital files is also very difficult for this researcher, and she finds the file management tools that are part of a computer’s operating system insufficient for her needs. Data silos. Thus, systems that restrict access to institutional affiliates would preclude multi-institutional collaboration among scholars in data sharing and preservation. Notably, the researcher also holds an electronic collection of Kyrgyz newspapers that no longer exist and no longer have web archives. This is likely to be a slow process initially. Data quality management is a setup process, which is aimed at achieving and maintaining high data quality. Ask the participant to narrate the process of completing the work from beginning to end. •    Inadequate time and skill to maintain data in legacy file formats (e.g., MS Word) He is presently an assistant professor (doctorate completed in 2001) and had no digital curation or data management training as part of his graduate training. •    Database programs: Bento by Filemaker Pro, MS Access, Filemaker •    Where are they located? Data not maintained at the institution. •    How do you work with/analyze/manipulate/transform the data? This participant went on to describe tools that could remediate some of these difficulties, suggesting networked databases that include tools for ingesting data according to schema designed for the project’s research questions. Evans, James A., and Jacob G. Foster. •    Reanalysis of archeological excavation site data •    Are the data backed up? This example shows that not taking your future datasets into account means it only supports your present dataset. •    In the area of privacy and data access control, additional tools should be developed to manage confidential data and provide the necessary security. Scholars need help with the technical aspects of managing and preserving data, as well as with basic curation issues (e.g., what to keep and what to delete), and the ethical implications of sharing their data (e.g., what is an appropriate latency period for the data and how does one balance the need to provide meaningful access with the risk of inadvertently exposing confidential participant information). However, top management should not overdo with control because it may have an adverse effect. •    If someone wanted to replicate/reconstruct your analysis, what information would be needed? 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