Minor formatting in docs

docs/input-types.md

@@ -1,4 +1,4 @@
-# Input type: file, url, or database?
+# Input type: File, URL, or Database?
 
 lbsntransform can read data from different common types of data sources:
 

docs/output-mappings.md

@@ -100,11 +100,12 @@ For example:
 lbsntransform --include_lbsn_bases hashtag,place,date,community
 ```
 
-would fill/update entries of the hlldb structures:  
-- topical.hashtag
-- spatial.place
-- temporal.date
-- social.community
+..would fill/update entries of the hlldb structures:  
+
+- topical.hashtag  
+- spatial.place  
+- temporal.date  
+- social.community  
 
 This name refers to `schema.table`.
 

docs/use-cases.md

@@ -2,21 +2,20 @@ If you're using the command line interface, a common usage of lbsntransform is t
 import/convert arbitrary social media data, e.g. from Flickr or Twitter, to a Postgres Database
 with the [common lbsn structure](https://lbsn.vgiscience.org/)
 
-The following use cases exist:
-
-1. importing lbsntransform as a package
+The following two primary use cases exist:
 
+1. **Importing lbsntransform as a package**
    Use this approach to convert data, such as individual posts 
    retrieved from an API, on-the-fly (in-memory), in your own
    python package.
 
-2. using the command line interface (cli) to perform batch conversions
-
+2. **Using the command line interface (cli) to perform batch conversions**
    Use this approach if you want to convert batches of data stored as
    arbitrary json/csv files, or if you want to convert from a database 
    with the raw lbsn structure to a database with the privacy-aware hll 
    format.
 
 For any conversion,  
-- the input type must be provided, see [input-types](input-types)
-- a mapping must exist, see [input-mappings](input-mappings)
+
+- the input type must be provided, see [input-types](/input-types)  
+- a mapping must exist, see [input-mappings](/input-mappings)