[sections collapse="always"][section title="Description"]

    Seminar: Special Issues in Information Studies: Data, Practices, and Curation + Winter 2014 + INF STD289-3 + BORGMAN
    For course location and time see Registrar Listing: INF STD289-3
    For official course description, final exam code and other course information see: INF STD289-3

    Course description: Seminar, two to four hours. Identification, analysis, and discussion of critical intellectual, social, and technological issues facing the profession. Topics may include (but not limited to) expert systems, literacy, electronic networks, youth at risk, information literacy, historical bibliography, preservation of electronic media, etc. May be repeated with topic change. Letter grading.

    Class description: Data are the new special collections for libraries, the oil of business, and the friction of collaborations. Survey of landscape of data practices, services, and policy, including role of data in sciences, social sciences, and humanities; national and international data policy (e.g., intellectual property, release policies, open access, economics); management of data by research teams, data centers, libraries, and archives; technical standards for data and metadata; and data curation and stewardship. Students read in depth and discuss current tensions in policy and practice. Assignments include analysis of data archives, data management plan for UCLA research project, and project to curate data for a research team. Students work in teams with UCLA researchers and make class presentations. Part one of two-part study.

    [/section][section title="CCLE Info"]
    Instructor Email Office Office hours
    BORGMAN, CHRISTINE borgman@gseis.ucla.edu GSEIS 235 M/W 5-6PM http://doodle.com/73zs95ud6tyyvzhb

     Announcements Forum  Discussion forum
     Relevant Job Openings Wiki
     IS289 Winter 2012 Project Groups File
     Data Jobs Wiki
     Assignment 1 File
     Term Project File

    [/section][/sections]
    [sections collapse="always"]

    [section title="Week 1"]

    Week 1 (January 8): Overview of Data, Data Practices, and Data Curation

    We will devote the first week of class to an overview of the concept of data and its manifestations across scholarly disciplines and in public parlance. We will also begin to form project groups for the term.

    Readings are to be completed in advance of each class session. Please come to class prepared to discuss the material and its relationship to larger issues in the course and the curriculum. Prepare some talking points as part of your reading and studying.

    Required readings

    (Borgman, forthcoming), Chapters 1 and 2, Big and Little Scholarship; Digital Scholarship
    Notes on Borgman Chs 1 & 2

    (Ray, 2014), Introduction, pages 1-21
    Notes on Ray intro

    (Ayres, 2007), Introduction, p 1-18
    Notes on SuperCrunchers

    Video (4:49):

    Bursts, Cascades, and Hot Spots: A Glimpse of Some On-Line Social Phenomena at Global Scales presented by Jon Kleinberg, Cornell University, Institute for Applied Mathematics (IPAM) at UCLA link: http://www.ipam.ucla.edu/programs/sl2014/lecture.aspx
     Ayres, I. (2007). Super Crunchers: Why thinking-by-numbers is the new way to be smart. (Chapter 1)
     Borgman, C.L. (forthcoming). Big Data, Little Data, No Data Scholarship in the Networked World. (Chapter 1 Draft- "Provocations")
     Borgman, C.L. (forthcoming). Big Data, Little Data, No Data Scholarship in the Networked World. (Chapter 2 Draft- "Digital Scholarship")
     Assignment 1: Assess the data archiving needs of a research community

    [/section][section title="Week 2"]

    Week 2 (January 15): What are data?

    “Data” is a far more ambiguous concept than is immediately apparent. Decisions about what data are to be managed, shared, and curated depend heavily on how the concept is defined. We will devote today to exploring some of the many definitions and facets of “data.”

    Assignment: Bring in a sample today of something that you consider to be data. We will discuss them in class.

    Required readings

    (Borgman, forthcoming), Chapter 3, What are data?

    (Edwards et al., 2013); see also Knowledge Infrastructures site: http://knowledgeinfrastructures.org

     Edwards et. al, 2013. Knowledge Infrastructures: Intellectual Frameworks and Research Challenges.
     Borgman, C.L. (forthcoming). Big Data, Little Data, No Data Scholarship in the Networked World. (Chapter 3 Draft: "What Are Data?")
    Notes
    [/section][section title="Week 3"]

    Week 3 (January 22): Public Policies for Research Data

    The ability to deposit, discover, share, retrieve, reuse, and curate data all depend upon public policies about rights and responsibilities. These policies have legal and economic aspects and vary widely around the world, although many international agreements are in place. Term project proposal is due Friday of this week. Please make office hour appointments to discuss your project in the weeks ahead.

    Readings
    (Ray, 2014) part 1: Understanding the policy context (2 chapters)
    (Organization for Economic Cooperation and Development, 2007)

    (Wood et al., 2010)

     Wood, J., Andersson, T., Bachem, A., Best, C., Genova, F., Lopez, D. R., … Hudson, R. L. (2010). Riding the wave: How Europe can gain from the rising tide of scientific data. Final report of the High Level Expert Group on Scientific Data.
     Organization for Economic Cooperation and Development. (2007). OECD Principles and Guidelines for Access to Research Data from Public Funding (pp. 1–24) File

    [/section][section title="Week 4"]

    Week 4 (January 29): Planning for Data Management

    Data management requires considerable planning on the part of the research team and on the part of repositories. We’ll start with some basic principles and components of the planning process. Assignment #4 is due at the start of class today.
    Readings:
    (Ray, 2014), Part 2, Planning for data management, chapters 3-5(Abrams, Cruse, & Kunze, 2009)
     Abrams, S., Cruse, P., & Kunze, J. (2009). Preservation is not a place. International Journal of Digital Curation, 4. File

    [/section][section title="Week 5"] Week 5 (February 5): Public policy for research data
    Notions of data vary greatly by context, discipline, time, and place. We will spend the middle three weeks of the term exploring case studies in multiple fields. Much of research policy is based on scientific data, thus we start with the sciences.

    Speaker (by video): Prof. Borgman, from Melbourne, Australia

    Local host and speaker: Dr. Peter Darch, UCLA Information Studies

    (Borgman, forthcoming), Chapter 5, Science cases

    (National Science Board, 2005)

    (Fortson et al., 2011)
     National Science Board. (2005). Long-Lived Digital Data Collections. File
     Fortson, L., Masters, K., Nichol, R., Borne, K., Edmondson, E., Lintott, C., … Wallin, J. (2011). Galaxy Zoo: Morphological Classification and Citizen Science (arXiv e-print No. 1104.5513). File

    Download (PDF, 343B)

    [/section] [section title="Week 6"] Week 6 (Feb 12): The role of replicating and reproducing research

    The social sciences have a very long history of data management and archiving. UCLA’s own Libbie Stephenson is an international leader in data archives for the social sciences.

    Speaker: Elizabeth Stephenson, Director, Institute for Social Research Data Archive, UCLAReadings(Borgman, forthcoming) Chapter 5: Social sciences cases(Ray, 2014), Chapter 10, Social Science Data(Vardigan & Whiteman, 2007)(Guide to Social Science Data Preparation and Archiving: Introduction, 2012)(King, 2011)
     Vardigan, M., & Whiteman, C. (2007). ICPSR Meets OAIS: Applying the OAIS Reference Model to the Social Science Archive Context.
     Guide to Social Science Data Preparation and Archiving: Introduction (2012).

     King, G. (2011). Ensuring the Data-Rich Future of the Social Sciences. Science, 331, 719–721.
    [/section][section title="Week 7"]

    Week 7 (February 19): Data in the Humanities

    Data is a much different notion in the humanities than in other disciplines. UCLA’s digital humanities program and the IDRE-HASIS have addressed campus data management issues for several years already. Team Project Report outline due today.

    Speaker: Dr. Lisa Snyder, Institute for Digital Research and Education, UCLA (invited) https://idre.ucla.edu/people/profiles/lisa-snyder

    Readings

    (Borgman, forthcoming), Chapter 6, Humanities cases

    (“Archaeology Data Service,” 2013)

    (“AHRC Technical Plan,” 2012)

    (Kouw, Van den Heuvel, & Scharnhorst, 2013)
    [/section][section title="Week 8"] Throughout the stages of a research project, data may be identified, captured, analyzed, modeled, modified, or discarded. Maintaining records of these stages and the relationships between them can be critical for data curation. Research teams handling data may vary in size from a few people to many hundreds. Data are also the “glue” that holds these teams together.

    Crane, G. R. (2006). What do you do with a million books? D-Lib Magazine, 12(3). http://www.dlib.org/dlib/march06/crane/03crane.html

    Goodman, A. & Wong, C. G. (2009). Bringing the night sky closer: Discoveries in the data deluge. In Hey, T., Tansley, S. & Tolle, K. (Eds.). The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond, WA, Microsoft: 39-44. http://research.microsoft.com/en-us/collaboration/fourthparadigm/

    Lagoze, C., & Velden, T. (2009). Communicating chemistry. Nature Chemistry, 1: 673-678. http://www.nature.com/nchem/journal/v1/n9/full/nchem.448.html

    Murray-Rust, P. & Rzepa, H. S. (2004). The next big thing: From hypermedia to datuments. Journal of Digital Information, 5(1): Article No. 248. http://journals.tdl.org/jodi/article/view/130

    Ruecker, S., Radzikowska, M. & Sinclair, S. (2009). Designing Data Mining Droplets: New Interface Objects for the Humanities Scholar. Digital Humanities Quarterly, 3(3). http://digitalhumanities.org/dhq/vol/3/3/000067.html

    Cummings, J., Finholt, T. A., Foster, I., Kesselman, C. & Lawrence, K. A. (2008). Beyond being there: A blueprint for advancing the design,development, and evaluation of virtual organizations. National Science Foundation.http://www.educause.edu/Resources/BeyondBeingThereABlueprintforA/163051

    Wallis, J. C., Borgman, C. L., Mayernik, M. S. & Pepe, A. (2008). Moving archival practices upstream: An exploration of the life cycle of ecological sensing data in collaborative field research. International Journal of Digital Curation, 3(1). Retrieved from http://www.ijdc.net/ijdc/issue/current on 24 November 2008.

    Recommended:
    Zimmerman, A. & Bos, N. (Eds.). Scientific Collaboration on the Internet. Cambridge, MA, MIT Press: 1-12. Retrieved from http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=11603&mode=toc on 29 December 2009.


     Outline and Bibliography Assignment
     Outline and Bibliography Assignment
    [/section][section title="Week 9"]

    Week 9 (March 7): The Role of Libraries & Archives in Data Management

    Only recently have research libraries begun to consider their roles and responsibilities in the curation and management of research data. We will survey current practice, policy, and proposed directions for data services provided by libraries and archives. Peter Young, Chief of the Asian Division of the Library of Congress, is leading LC’s efforts in eScience and data curation, including the Twitter archive. Mr. Young and some of the LC staff will join us by videolink.

    Invited Speaker (by video): Peter Young, Library of Congress

    Readings:

    Corrall, S. (2012). Roles and Responsibilities -- libraries, librarians and data. In G. Pryor (Ed.), Managing Research Data (pp. 105-135). (Attached below)

    Gilliland-Swetland, A. J. (2000). Enduring Paradigm, New Opportunities: The Value of the Archival Perspective in the Digital Environment. Council on Library and Information Resources. Retrieved from http://www.clir.org/pubs/reports/pub89/contents.html on 7 May 2006.

    Hey, T. & Hey, J. (2006). e-Science and its implications for the library community. Library Hi Tech, 24(4): 515 - 528. Retrieved from http://www.emeraldinsight.com/Insight/ViewContentServlet?Filename=Published/EmeraldFullTextArticle/Articles/2380240404.html on 30 December 2009.

    Karasti, H., Baker, K. & Halkola, E. (2006). Enriching the notion of data curation in e-Science: Data managing and information infrastructuring in the Long Term Ecological Research (LTER) Network. Journal of Computer Supported Cooperative
    Work, 15(4): 321-358.
    http://www.springerlink.com/content/f778uh7077914q20/fulltext.pdf

    Pryor, G. & Donnelly, M. (2009). Skilling Up to Do Data: Whose Role, Whose Responsibility, Whose Career? International Journal of Digital Curation, 4(2). Retrieved from http://www.ijdc.net/index.php/ijdc/issue/view/8 on 30 December 2009.

    The Research Library’s Role in Digital Repository Services: Final Report of the ARL Digital Repository Issues Task Force (2009). Association of Research Libraries. Retrieved from http://www.arl.org/bm~doc/repository-services-report.pdf on 10 March 2009. The University's Role in the Dissemination of Research and Scholarship - A Call to Action (2009). Association of Research Libraries. Retrieved from on 10 March 2009.

    Library of Congress slides
    Corrall "Roles and Responsibilities - Libraries, Librarians and Data"
    InterPARES Table
    Repurposing Public Policy Data for Congress
    Corrall "Roles and Responsibilities - Libraries, Librarians and Data"
     InterPARES Table File<
    [/section][section title="Week 10"]

    Week 10 (March 13): No Class
    You will have this week to work on your final project and your presentations for next week.
    Wednesday, March 21:
    Final projects due, 5pm, to instructor’s mailbox and by PDF to CCLE.

     IS289 Winter 2012 Term Project Final Report Submission Assignment
     IS289 Winter 2012 Term Project Final Report Submission Assignment

    ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

    Download (DOCX, 357B)

    Download (DOCX, 357B)

    Download (PDF, 343B)

    GDE Error: Error retrieving file - if necessary turn off error checking (404:Not Found)
    GDE Error: Error retrieving file - if necessary turn off error checking (404:Not Found)

    Download (PDF, 343B)

    GDE Error: Error retrieving file - if necessary turn off error checking (404:Not Found)

    Download (PDF, 343B)

    GDE Error: Error retrieving file - if necessary turn off error checking (404:Not Found)

    Download (PDF, 357B)

    Download (PPTX, 357B)

    [/section][/sections]
    DianaIS289-3 Borgman Data