DCXL Lightning Talk: Archiving Small Datasets

DCXL Lightning Talk: Archiving Small Datasets

• 1.
  Archiving  Small   Science  Data  Sets     Carly  Strasser  |  carly.strasser@ucop.edu  |  www.carlystrasser.net   John  Kunze   Patricia  Cruse   Personal  Digital  Archiving    |    February  2012  
• 2.
  UGLY TRUTH Many   Earth  |  Environmental  |  Ecological   scientists…       5shortessays.blogspot.com     are  not  taught  data  management   don’t  know  what  metadata  are   can’t  name  data  centers  or  repositories   don’t  share  data  publicly  or  store  it  in  an  archive   aren’t  convinced  they  should  share  data    
• 3.
  Where  do  data  end  up?   From  Flickr  by  diylibrarian   www blog.order2disorder.com   From  Flickr  by  csessums   Data   Metadata   From  Flickr  by  csessums   Recreated  from  Klump  et  al.  2006  
• 4.
  Where  do  data  end  up?   From  Flickr  by  diylibrarian   www Data   www Metadata   From  Flickr  by  torkildr   Recreated  from  Klump  et  al.  2006  
• 6.
  Facilitate   Archiving   Data   Data  Reuse   management   Sharing   &  organization   Reproducibility   Publishing  
• 7.
  Why  are  you   promoting   Excel?   Develop  an  open  source  &  free     Excel  add-­‐in     Add-­‐in:    Little  pieces  of  software          Download  to  extend  the  capabilities  of  Excel        Appear  as  “ribbon”   www.ablebits.com  
• 8.
  Why  are  you   promoting   Excel?   Everyone  uses  it   Stopgap  measure      
• 9.
  DCXL  Project  Goals   Audience:  Earth,  atmospheric,   environmental,  ecological  scientists       Contributors:  UC  community,  DataONE,   broader  community  via  conferences       Method:  Collect  requirements  via  surveys,   interviews,  polls      
• 10.
  ~ 150  scientists   •  No  data  preservation   –  Unaware  of  archives   –  Resistant  to  sharing   •  Poor  data  documentation   •  90%  use  other  programs  along  with  Excel  
• 11.
  Requirements   1.  Must  work  for  Excel  users  without  the  add-­‐in   2.  No  additional  software  (other  than  add-­‐in  and  Excel)  necessary   3.  Can  be  used  offline  
• 12.
  Requirements   1.  Must  work  for  Excel  users  without  the  add-­‐in   2.  No  additional  software  (other  than  add-­‐in  and  Excel)  necessary   3.  Can  be  used  offline   4.  Perform  CSV  compatibility  checks,  reporting,  and  automated  fixes  
• 13.
  Requirements   1.  Must  work  for  Excel  users  without  the  add-­‐in   2.  No  additional  software  (other  than  add-­‐in  and  Excel)  necessary   3.  Can  be  used  offline   4.  Perform  CSV  compatibility  checks,  reporting,  and  automated  fixes   5.  Add  Metadata  to  data  file   a.  Can  use  existing  metadata  as  a  template   b.  Add-­‐in  can  automatically  generate  some  of  the  metadata   where  the  info  is  available  from  the  file   6.  Generate  a  citation  for  the  data  file  
• 14.
  Requirements   1.  Must  work  for  Excel  users  without  the  add-­‐in   2.  No  additional  software  (other  than  add-­‐in  and  Excel)  necessary   3.  Can  be  used  offline   4.  Perform  CSV  compatibility  checks,  reporting,  and  automated  fixes   5.  Add  Metadata  to  data  file   a.  Can  use  existing  metadata  as  a  template   b.  Add-­‐in  can  automatically  generate  some  of  the  metadata   where  the  info  is  available  from  the  file   6.  Generate  a  citation  for  the  data  file   7.  Deposit  data  and  metadata  in  a  repository  
• 15.
  dcxl.cdlib.org   DCXLatCDL   @dcxlCDL  
• 16.
  dcxl.cdlib.org   @dcxlCDL   www.facebook.com/DCXLatCDL   www.carlystrasser.net   carlystrasser@gmail.com   @carlystrasser