Step 1:
	Every time when a new database is pushed online, 
	
	For SQL users:
		a. Go to the folder '1_SQL_Data_Prep'. 
		b. Throughout the script, replace 'patent_20180528' with the most recent raw database and 'PatentsView_20180528' with the latest reporting database EXCEPT 
		   for the 'temp_inventor_gender' table, which will not be present in new databases as the gender code is not yet implemented. 
		c. Then run through all of the SQL scripts (in numerical order) to generate tables that will be used to generate these visualizations. 
		   ** Note: Notice that some of the queries arequite slow due to table size.

	For R users:
		a. To gather data, you will be able to download the most updated data from http://www.patentsview.org/download/ and save it to folder 'data_to_read'. 
		   These data include:
			1. uspatentcitation
			2. patent
			3. patent_govintorg
			4. patent_inventor
			5. patent_assignee
			6. nber
			7. wipo
			8. wipo_field
			9. temp_5yr_citations
			10. government_organization
			11. assignee
			12. government_interest
			13. rawassignee
			14. temp_gi_assignee_type
			15. temp_inventor_gender
			16. temp_gi_has_female_inv
			17. temp_gi_inventor_gender

		b. Go to the folder '1_R_Data_Prep'. 
		c. Make sure you change the path which you store your data you downloaded in step (a). Then run through all of the R scripts in numerical order to generate tables 
		d. Save all the tables generated in this step in folder 'data_to_read', these include
			1. temp_patent_level_gi.csv
			2. temp_gi_level_gi.csv
			3. temp_patent_level_all
			4. all_assignees
			5. temp_5yr_citations_by_cite_yr1
			6. temp_5yr_citations_by_cite_yr2
			7. temp_5yr_citations_by_cite_yr3
			8. temp_5yr_citations_by_cite_yr4
			9. temp_5yr_citations_by_cite_yr5
			10. assignee_type
Step 2:
	Put the lookup files that are provided in folder 'data_to_read'. These files include:
		a. assignees_lookedup_types.csv [from python script]
		b. government_interest_patents_1980-2018_returned.csv [from USPTO]
		c. Agencies.csv [from Archive]

Step 3:
	** NOTE: In this step, if you generated tables useing R in Step 1, then make sure you change the way you read in table from local file in the following three R scripts.

	Go to folder '3_Data_Viz_Generate' to generate data viz
	
	Run through 1.govIntBrief_v3.R to generate data visualizations and tables for analysis. This script will generate two folders:
		(1) Folder 'data_viz': a folder to store all of the viz that will be generated from R script
		(2) Folder 'out': a folder to store all of the tables that will be generated from R script
	
	Then, run 2.govIntBrief_v3_assignee and 3.govIntBrief_v3_gender