Poster RDAP13: Data information literacy multiple paths to a single goal
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share

Poster RDAP13: Data information literacy multiple paths to a single goal

  • 851 views
Uploaded on

Jake Carlson, Jon Jeffryes, Brian Westra and Sarah Wright ...

Jake Carlson, Jon Jeffryes, Brian Westra and Sarah Wright

Data Information Literacy: Multiple Paths to a Single Goal

Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
851
On Slideshare
851
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
4
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Purdue UniversityPurdue e-PubsLibraries Faculty and Staff Presentations Purdue Libraries1-1-2013Data Information Literacy: Multiple Paths to aSingle GoalJake CarlsonPurdue University, jakecarlson@purdue.eduSarah WrightCornell University, sjw256@cornell.eduBrian WestraUniversity of Oregon, bwestra@uoregon.eduJon JeffryesUniversity of Minnesota - Twin Cities, jeffryes@umn.eduFollow this and additional works at: http://docs.lib.purdue.edu/lib_fspresPart of the Library and Information Science CommonsThis document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact epubs@purdue.edu foradditional information.Recommended CitationCarlson, Jake; Wright, Sarah; Westra, Brian; and Jeffryes, Jon, "Data Information Literacy: Multiple Paths to a Single Goal" (2013).Libraries Faculty and Staff Presentations. Paper 12.http://docs.lib.purdue.edu/lib_fspres/12
  • 2. Mini-­‐Course  Readings  &  Seminar  Objec&ve  What  skills  will  graduate  students  need  to  be  successful  in  managing,  working  with  and  cura=ng  their  research  data?    This  poster  reports  on  ini=al  results  from  a  two-­‐year  project  funded  by  the  Ins=tute  of  Museum  and  Library  Services  (IMLS)  that  is  centered  on  exploring  this  ques=on.  Methods  The  project  is  comprised  of  five  teams  (each  made  up  of  a  data  services  librarian,  a  subject  or  informa=on  literacy  specialist  and  a  faculty  researcher)  from  four  ins=tu=ons.    Each  team  conducted  environment  scans  of  the  discipline  and  conducted  interviews  of  their  faculty  partner  and  his  graduate  students.    Using  this  knowledge  each  team  developed  an  educa=onal  program    tailored  to  their  specific  discipline  and  local  prac=ces.          Findings      Data  Informa&on  Literacy:  Mul&ple  Paths  to  a  Single  Goal  Jake  Carlson,  Purdue  University;  Jon  Jeffryes,  University  of  Minnesota;    Brian  Westra,  University  of  Oregon;  Sarah  Wright,  Cornell  University  Discipline      Natural  Resources   Civil  Engineering    Ecology  Electrical  &  Computer  Engineering    Ag  &  Bio  Engineering  Iden=fied        Needs  Data  Sharing    Databases    Metadata  Data  Ownership    Long-­‐term    Access    Cultures  of  Prac=ce    Metadata    Closing  Out  a  Grant    Document-­‐  a=on  &  Organiza=on    Transfer  of  Responsibilty    Data  Sharing  Protocols      Metadata  Response  Outcomes  Faculty  Engagement      Applica=on  of  Best  Prac=ces  Completed  DMP  Improved  Data  Prac=ces  Awareness  of  Tools,  Resources,  and  Best  Prac=ces  Raised  Awareness  Resources  for  Evalua=ng    Student  Work  Refine  Exis=ng  SOPs  on  Data  Checklist  for  Enforcing  SOPs  Cornell  University  University  of  Minnesota  University  of  Oregon  Purdue  University  #1  Purdue  University  #2  Online  Course  Embedded  Librarianship  Workshops  •  All  12  competencies  were  seen  as  important  by  faculty  and  graduate  students.    •  Lack  of  formal  training  in  data  management  •  Lack  of  formal  policies  in  the  research  team  •  Self-­‐directed  learning  through  trial  and  error  •  Focus  on  data  mechanics  and  local,  immediate  needs  over  deeper  concepts  or  applica=on  outside  of  the  lab.    Note:  Due  to  the  small  size  and  use  of  convenience  sampling  these  findings  cannot  be  generalized  beyond  this  project.  Project  Personnel:    Jake  Carlson  (PI),  Camille  Andrews,    Marianne  Stowell  Bracke,  Michael  Fosmire,  Jon  Jeffryes,  Lisa  Johnston,  Megan  Sapp  Nelson,  Dean  Walton,  Brian  Westra,  Sarah  Wright.        Data  Informa=on  Literacy  Model  Image  Credits:  Photos:  “School  of  Fish”  by  Tom  Weilenmann:  h_p://www.flickr.com/photos/tom_weilenmann/51673288/;  “Roosevelt  Dam  Bridge”  by  Al_HikesAZ:  h_p://www.flickr.com/photos/alanenglish/466658759/;  “Sunshine  Sparkling  on  the  Prairie  Grass”  by  Carol  VanHook:  /librariesrock/3613075606/;  “Code  Obfusca=on  -­‐  Part  2:  Obfusca=ng  Data  Structures”  by  Sonia  Gupta:  h_p://palizine.plynt.com/issues/2005Sep/code-­‐obfusca=on-­‐con=nued/;  “SEPACisco”  from  the  Water  Quality  Field  Sta=on:  h_p://www.agry.purdue.edu/water/fieldstn/photogallery/SEPACisco.jpg.    Graphics:  “User  Experience”  stencils  by  Todd  Zazelenchuk  &  Elizabeth  Boling:  h_p://www.userfocus.co.uk/resources/omnigraffle.html            hKp://datainfolit.org