When going through data management steps in Stata, there are several
documentation features available that allow you to attach information to the
dataset.  This approach to documenting allows you to always have access to
your notes when looking at the data.  Then, when working with the dataset, using some search commands can be an efficient way to find the desired variables for analysis and
avoid confusion. 

First, we demonstrate how to add variable label, value labels, dataset notes,
and variable notes to data. 

Adding a variable label and/or value label

A variable label allows you to describe the information contained in a
variable (thus allowing you to keep variable names more concise!).  To add
a label to a variable, use the label variable command, then provide the
variable you wish to label and the label to apply. Below, we will create a
categorical variable called honsci based on the science variable. 
Those with science scores of 60 or over are eligible for entry to a science honors
society.  We will indicate this with a variable label.

use https://stats.idre.ucla.edu/stat/stata/notes/hsb2, clear
gen honsci = (science >= 60)
label variable honsci `"honors eligibility"'

For purposes of data analysis in Stata, you will often need to code
categorical variables as numeric.  However, you can still have a string
describing each numeric value in such a variable.  Since the variable honsci
contains 0 and 1, we will add value labels describing what each value
represents. To do this, we will first define a label with the value descriptions
using label define.  Then we will apply the label to the values in
honsci using label values.

label define elig 1 "eligible" 0 "not eligible"
label values honsci elig
table honsci

-------------------------
honors       |
eligibility  |      Freq.
-------------+-----------
not eligible |        153
    eligible |         47
-------------------------

Adding variable or dataset notes

Notes in Stata are an excellent way to annotate your data.  Notes can be
attached either to the dataset as a whole or to specific variables.  Below,
we write a note to the dataset and a note to the ses variable.

note: Perhaps recenter score variables for analysis
note ses: This variable must be dummy coded for analysis

The command notes lists all of the notes in a dataset:

notes

_dta:
  1.  Perhaps recenter score variables for analysis

ses:
  1.  This variable must be dummy coded for analysis

All of these are included when a Stata dataset is loaded and all are searchable.
In Stata 11 and later, you can use the Variables Manager to see variable labels,
formats, and whether or not a variable has a value label or notes attached to
it.

Adding data-validation checks

There is a package of Stata commands you can download, ckvar, that
allows you to create “self-validating” datasets.  For a full presentation
of the package by its author, see Bill Rising’s WCSUG07 slides.
We will briefly demonstrate how to add a rule to a variable and
then check that the dataset does not have any observations that violate the
accepted range.  After downloading ckvar, you can use the
ckvaredit to open a dialog window that allows you to enter validation rules
for your variables.

ckvaredit

Our variable female should only take on values 0 and 1. We can select
female from the “Variable to Check” list and then provide a rule for the
acceptable range of values. We do this by entering in {0,1} in the
“Current Rule(s)” box.  When we click “Done”, we see the equivalent code
appear:

ckvareditSave female, stub(valid) req(0) rulechgflag(1) rule("in {0,1}")

We can check to see if there are any violations of rules by entering ckvar.

ckvar
Checking hsb2.dta on 28 Jan 2010 at 15:55:26:

There were no errors or missing required values!

If we wish to see what an error would trigger, we can change a value in our data and then rerun this check.

preserve
replace female = 3 if id == 1
ckvar

Checking hsb2.dta on 28 Jan 2010 at 15:58:36:

 Variable name | Errors | Missing | Error-marker name
---------------+--------+---------+------------------
            id |    N/A |     N/A |              none
        female |      1 |     N/A |      error_female
           ses |    N/A |     N/A |              none
        schtyp |    N/A |     N/A |              none
          prog |    N/A |     N/A |              none
          read |    N/A |     N/A |              none
         write |    N/A |     N/A |              none
          math |    N/A |     N/A |              none
       science |    N/A |     N/A |              none
         socst |    N/A |     N/A |              none
        honors |    N/A |     N/A |              none
        awards |    N/A |     N/A |              none
           cid |    N/A |     N/A |              none
           
restore

For more details on the types of rules that can be implemented, the linked presentation is the best source.

Searching in variable names and variable labels

If you are presented with a dataset and wish to find which variables have a
name or label containing a given string, you can use the lookfor command.
We will demonstrate this and similar commands using the small sample dataset,
hsb2, but it is likely more useful when you are looking at a dataset with
many variables or variables that are ambiguously named, but well labeled. First, we can
look for the string “male” among our variable names and labels.

lookfor male

              storage  display     value
variable name   type   format      label      variable label
---------------------------------------------------------------------------------------------------------------------
female          float  %9.0g       fl

Stata returns a list of the variables that match our search–the variable
name “female” contains “male”. Next, we can search for the string “score”.

lookfor score

              storage  display     value
variable name   type   format      label      variable label
---------------------------------------------------------------------------------------------------------------------
read            float  %9.0g                  reading score
write           float  %9.0g                  writing score
math            float  %9.0g                  math score
science         float  %9.0g                  science score
socst           float  %9.0g                  social studies score

We see all of the variables with the word “score” in their label.

Searching in notes

You can search through these notes with the notes search command.  We
can search for the string “analysis”.

notes search analysis

_dta:
  1.  Perhaps recenter score variables for analysis

ses:
  1.  This variable must be dummy coded for analysis

Stata returns the notes containing the string and indicates if they are dataset notes or variable-specific.

Searching a directory (several datasets)

Often in an analysis, multiple datasets are analyzed. The lookfor_all command
allows searches through all Stata files in the current directory.  This is
a user-written command and can be easily downloaded (see Stata FAQ: How
do I use the search command to search for programs and additional help?).

Use the
pwd command to learn Stata’s current directory.  You can change the
working directory using cd or by choosing “Change Working Directory” from
the “File” menu. The code below searches for the string “school” in
the variable names and labels of the .dta files in the working directory.

pwd

D:Data

lookfor_all school

use "D:/Data/hsb2.dta" 
variables: schtyp
use "D:/Data/hsbmis.dta" 
variables: schtyp

Total 5 out of 5 files checked in  "D:/Data/"

Stata returns the commands needed to load the datasets containing the
variable(s) of interest and indicates the names of the variables in each dataset
containing the string in its name or label.

Searching in value labels

To see all of the value labels present in a dataset and the list of variables
to which they have been applied, you can use the labelbook
command. Below, we demonstrate this (but show only one of the output labels to
save space).

labelbook
---------------------------------------------------------------------------------------------------------------------
value label elig 
---------------------------------------------------------------------------------------------------------------------

      values                                    labels
       range:  [0,1]                     string length:  [8,12]
           N:  2                 unique at full length:  yes
        gaps:  no                  unique at length 12:  yes
  missing .*:  0                           null string:  no
                               leading/trailing blanks:  no
                                    numeric -> numeric:  no
  definition
           0   not eligible
           1   eligible

   variables:  honsci

Variables in Stata can also contain value labels that we may wish to search. 
We can do this using the vlabs option in the lookfor_all command. The code below searches for the string “low” in the variable names, variable
labels, and value labels of all the .dta files in the working directory.

lookfor_all low, vlabs

 use "D:/Data/hsb2.dta" 
then:
 label list sl 


 use "D:/Data/hsbmis.dta" 
then:
 label list sl 

 use "D:/Data/mypars.dta" 
 variables: min95

 Total 5 out of 5 files checked in  "D:/Data/"

From this output, we can see that there are two datasets, hsb2 and hsbmis, that contain
a value label with the string “low”.  There’s also a dataset mypars
with a variable min95 that must have “low” in its variable label.