Data Management

Data management includes the procurement, preservation, manipulation and documentation of data used in research. The support goals in this area include:

• Assistance with Data Acquistion - this includes ICPSR data orders and other acquistions that can be undertaken through the Social Science Data Center or Perkins Library.
   
• Archival Support - assisting with data perservation or in making data publicly available.
   
• Instruction - identifying experts in the use of particular data management tools or techniques and facilitating opportunities for them to teach short courses or workshops.
   
• Tutorials - on data management technique, locally prepared or derived from pointers to other sites. Data management technique is conditioned by the choice of tool (statistical package or programming language). But within each programming environment, there are general sets of issues that come up:
   
• Input of raw data
• Rectangular files
• Hierarchical files
• Numeric versus character data input
• Input formats - free field, fixed field, specialized informat
• Record formats - fixed, variable
• Derivation of new measures (variables)
• Assigning new variables
• Numeric data manipulations
• Character data manipulations
• Date and time manipulations
• Conditional variable assignments
• Handling missing data
• Data set transformations
• Subsetting
• Sorting and BY group processing
• Concatenating
• Merging
• Aggregating
• Transposing
• Sampling