Minor updates

docs/administration.md

@@ -64,7 +64,7 @@ pilosa import -i project -f stargazer --field star_count project-stargazer-count
 ```
 
 <div class="note">
-    <p>Note that you must first create a frame with Range Encoding enabled and a field. View <a href="../api-reference/#create-frame">Create Frame</a> for more details.</p>
+    <p>Note that you must first create a frame with range-encoding enabled and a field. View <a href="../api-reference/#create-frame">Create Frame</a> for more details.</p>
 </div>
 
 #### Exporting

docs/data-model.md

@@ -63,7 +63,7 @@ The LRU cache maintains the most recently accessed Rows.
 
 ### Time Quantum
 
-Setting a time quantum on a frame creates extra indices which allow Range queries down to the interval specified. For example - if the time quantum is set to `YMD`, Range queries down to the granularity of a day are supported. 
+Setting a time quantum on a frame creates extra views which allow Range queries down to the time interval specified. For example - if the time quantum is set to `YMD`, Range queries down to the granularity of a day are supported.
 
 ### Attribute
 
@@ -112,7 +112,7 @@ SetBit(frame="A", rowID=8, columnID=3, timestamp="2017-05-19T00:00")
 #### BSI Range-Encoding
 
 Bit-Sliced Indexing (BSI) is the storage method Pilosa uses to represent multi-bit integers in a bitmap index. Integers are stored as n-bit, range-encoded
-bit-sliced indexes of base-2, along with an additional bitmap indicating "not null". This means that a 16-bit integer will require 17 bitmaps: one for each 0-bit of the 16 bit-slice components (the 1-bit does not need to be stored because with range-encoding the highest bit position is always 1) and one for the non-null bitmap. Pilosa can evaluate, aggregate, and range queries on these BSI integers. 
+bit-sliced indexes of base-2, along with an additional bitmap indicating "not null". This means that a 16-bit integer will require 17 bitmaps: one for each 0-bit of the 16 bit-slice components (the 1-bit does not need to be stored because with range-encoding the highest bit position is always 1) and one for the non-null bitmap. Pilosa can evaluate `Sum` and `Range` queries on these BSI integers.
 
 Internally Pilosa stores each BSI `field` as a `view` within a `frame`. The 'rowIDs' of the `view` are composed of the base-2 representation of the integer. Pilosa manages the base-2 offset and translation that efficiently packs the integer value within the minimum set of rows.
 
@@ -129,3 +129,5 @@ SetFieldValue(col=3, frame="A", field1=6)
 
 ![BSI frame diagram](/img/docs/frame-bsi.svg)
 *BSI frame diagram*
+
+Check out this [blog post](/blog/range-encoded-bitmaps/) for some more details about BSI in Pilosa.

docs/query-language.md

@@ -473,7 +473,7 @@ Returns bits that are true for the comparison operator.
 **Examples:**
 
 In our source data, commitactivity was counted over the last year.
-The following greater-than Range query returns all repositories having more than 100 commits.
+The following greater-than `Range` query returns all repositories having more than 100 commits.
 
 ```
 Range(frame="stats", commitactivity > 100)
@@ -513,7 +513,7 @@ Sum([BITMAP_CALL], <frame=STRING>, <field=STRING>)
 
 **Description:**
 
-Returns the count and computed sum of all bitmap encoded integer values across the `field` in this `frame`. The optional Bitmap call filters the bits used in this computation.
+Returns the count and computed sum of all BSI integer values across the `field` in this `frame`. The optional `Bitmap` call filters the bits used in this computation.
 
 **Result Type:** object with the computed sum and count of the bitmap field.
 

docs/tutorials.md

@@ -241,7 +241,7 @@ Check out our [Administration Guide](https://www.pilosa.com/docs/latest/administ
 
 #### Introduction
 
-Pilosa can store integer values associated to the columns in an index, and those values are used to support range and aggregate queries. In this tutorial we will show how to set up integer fields, populate those fields with data, and query the fields. The example index we're going to create will represent fictional patients at a medical facility and various bits of information about those patients.
+Pilosa can store integer values associated to the columns in an index, and those values are used to support `Range` and `Sum` queries. In this tutorial we will show how to set up integer fields, populate those fields with data, and query the fields. The example index we're going to create will represent fictional patients at a medical facility and various bits of information about those patients.
 
 First, create an index called `patients`:
 ``` request