Welcome to the Data @ FSU LibGuide! 

This LibGuide covers definitions of data, the data lifecycle, research data management, reusing data, and data ownership and ethics. 

There are many definitions of research data, but one common one comes from the OMB Circular A-110:

"The recorded factual material commonly accepted in the scientific community as necessary to validate research findings." 

Research data can be divided into four broad types (from the University of Edinburg): 

• Observational -- Data captured in real time. typically not replicable. 
• Experimental -- Data captured from lab equipment. can be replicable, but may be expensive. 
• Simulation -- Data generated from test models where the models and metadata are more important than the output data
• Derived or compiled -- Data captured from data mining, complied databases or similar tasks. Can be replicated, but may be expensive. 

Source: University of Edinburgh via the NECDMC Module 1

Data can cover a broad range of information, depending on research project and discipline: 

• Documents, spreadsheets
• Laboratory notebooks, field notebooks, diaries 
• Questionnaires, transcripts, codebooks 
• Survey responses 
• Health indicators 
• Audio and video recordings 
• Images, films
• Protein or genetic sequences 
• Spectra 
• Test responses 
• Slides, artifacts, specimens, samples 
• Database contents (video, audio, text, images)
• Models, algorithms, scripts 
• Software code, software for simulation 
• Methodologies and workflows 
• Standard operating procedures and protocols 

Source University of Oregon via NECDMC Module 1