These "tips" or Pearls were generated from a two-part seminar on project and data management. This seminar focused on the data process, from the acquisition of data and its preparation for analysis. More general issues related to project management and file management were also addressed.

• Examine the scope of a project and adjust accordingly if the size increases or decreases.
• Data management at all levels takes more time than we think. Planning together to outline the project and set deadlines is important.
• Designate a point person to organize, schedule meetings and provide updates on the project’s progress.  
• To Err is Human. Accept the fact, check your work diligently, and be understanding of yourself and others if mistakes occur.
• Ask for help when you need it. This can be a big saver in efficiency.
• Say ‘Thank You’ often.
• Positive feedback makes people feel like they can accomplish more, rather than less.
• Recognize each other’s strengths. Support one another’s growth and learning.
• Go slow to go fast. (The more preparation time allowed the better the end result.)
• It is a problem if you do not have a research question.
• Save yourself some guess work-ask the important questions about the data before you start analyzing it.
• Conduct a lit. review.
• Keep research questions simple.
• Sometimes difficult to generalize.
• The more organizational time, the better the product.
• Ask a lot of questions up front.
• Collaborate with other groups
  

• Label revisions (or versions) as such and remove old/unnecessary versions.
• Keep files where they belong.
• Use shortcuts.
• Save often.
• Back Up.
• When naming folders, make sure there is not already a file in that folder of the same name.
• NO spaces at the end of file names AND when using spaces in file names, make sure there is just one.
• Keep data on the server.
• Be sure that everyone on the team has the same computer software/same versions of the software.
• Include purpose, date, and version in file name
  

• Collect only needed data, but make sure you collect ALL the data you need.
• When you change a question on a form, the data are no longer comparable with previously collected data.
• Ask for data in Access, Excel, CSV, or FLAT file formats.
  

Data coding

• Alpha values are alright.
• Garbage In Garbage Out (GIGO).
• Unique identifiers are very important.
• Use code sheet or data dictionary..
  

• Use the right tool for the right task.
• Use a meaningful naming scheme.
• No hard returns in data.
• Note everything needs a SAS or an Access database and some things can be done easier manually.
• Always use the appropriate software to 'crunch' the data (ie, one that doesn't require a PhD in Quantum Physics)
• Use descriptive field names.
• Use easily understood and consistent field value descriptors.
• Format field for type of data in field
  

• Information kept in only one place only needs to be updated once.
• Keep data current.
• Always over estimate the time that it takes to design a report in Access!