Method should describe how you gather and process your data.
Method should be a description of what you are doing to get the data, your step-by-step procedure of collecting the information and how you process it.
This should be clearly explained so that your peers can understand how you arrived at amassing the data. Peers may wish to replicate your study and validate or refute the results and significance with their own data. This is important as replication studies can reinforce the validity or lack thereof in research designs and outcomes.
Methods should practicably include everything you used (equipment/facilities), where you did it (location/time) and how (process/procedure).
For example, you might list the software, facilities, computers and equipment used to gather and process your data, describing in detail your work-flow while listing the times and locations you used certain facilities and with whom.
Carefully log everything you do towards your research. Keep a record of every search term and keyword, when and where you go (online and offline) and with whom, from your research routine.
The gold standard is that if you or someone else had to redo your research using your exact methods, they’d get the same or significantly similar types of data.
Methodology should describe why you choose to gather and process the data the way you do.
Method-ology translated directly means the study (scientific field/school of thought) of the logic (reasoning) behind your chosen methods.
Your methodology description might be supported by concepts (ideas) and theories (beliefs) of other researchers who’ve developed or popularized a unique research method approach and perspective.
It might also include your own prevailing world view and epistemology (knowledge theory) as a part rationalizing your choice of data gathering and justifying your belief that your choice of data processing is suitable to your study.
Methodologies are numerously abundant and new methodologies and their variations are being invented all the time.