incorporating more of Aviva's comments, #30

01_considerations.Rmd

@@ -52,15 +52,16 @@ and space. There are different considerations for data management when you are
 working on a project alone, as a collaboration, or archiving data for future 
 use. However, similar best practices for data management will benefit them all.
 
-Even if you are the only person who will ever interact with your data, data
-management is still something to consider. If you collect or modify your data
-over time, you need to make sure you keep track of those changes, and make sure
-you are always working with the most up to date version of your data. This could
-be because you are adding new data or correcting errors in older data. This is
-doubly important if data gets entered by hand. Some data stores keep track of
-changes to your data for you and even provide some quality control tools. Others
-require you to do track versions of your data and do quality control on your
-own.
+Data Management is a crucial part of valid and reproducible research. Even if
+you are the only person who will ever interact with your data, you must manage
+your data in a way that you in the future will be able to recall what past you
+did, and why. If you collect or modify your data over time, you need to make
+sure you keep track of those changes, and make sure you are always working with
+the most up to date version of your data. This could be because you are adding
+new data or correcting errors in older data. This is doubly important if data
+gets entered by hand. Some data stores keep track of changes to your data for
+you and even provide some quality control tools. Others require you to track
+versions of your data and do quality control manually.
 
 However, science is a collaborative process, so it is more than likely you won't
 be the only one working with your data. Any time more than one person needs to

02_data.Rmd

@@ -31,18 +31,19 @@ Note: there are other definitions of data structure from other disciplines
 (ex. in comp sci), we will not be using those definitions
 -->
 
-If you are doing research, chances are you are going to be working with data in
-some form or another. Even if you do not use traditional rows and columns, you
-are certainly working with some form of information. And if you have translated
-information into a form that is more easily shared or stored for later use, you
-are working with data. Information becomes data when we give it some sort of
-structure. That could be the rows and columns of a table, or something more
+I think the first paragraph should be “Information becomes data when we give it
+some sort of structure. If you are doing research, chances are you are going to
+be working with data in some form or another. If you have translated information
+into a form that is more easily shared or stored for later use, you are working
+with data. That could be the rows and columns of a table, or something more
 human readable, like the grammar and syntax of natural language in text form.
+Even if you do not use traditional rows and columns, you are certainly working
+with some form of information that you have turned into data.
 
 One of the challenges of working with data is figuring out a useful way to store
 it. Thankfully, we have mostly left behind the 20th century's favorite way of
 storing data: paper in filing cabinets. Modern digital methods definitely take
-up less space but also have a higher barrier to entry. There are many more types
+up less space but also require more technical knowledge. There are many more types
 of data stores available now as well. This means you will need to make a
 decision on which one to use. **Ultimately, the best way to store your data**
 **will depend on the data you want to store and the questions you want to ask**
@@ -56,13 +57,13 @@ type and data structure.
 Your data's type tells the computer what sorts of operations make sense. Common
 data types include:
 
--   integers
--   decimal
--   floating point numbers
--   categories (small, medium, large)
--   characters (text)
+-   Integers
+-   Decimal
+-   Floating point numbers
+-   Categories (small, medium, large)
+-   Characters (text)
 -   Boolean values (TRUE and FALSE)
--   dates and times
+-   Dates and times
 
 All data, including individual data points, have a type. However, a given piece
 of information can be stored using multiple data types. For example, you can

03_data-stores.Rmd

@@ -27,8 +27,11 @@ computer through text commands.
 **Query:** commands that create, read, update, or delete information from a data
 store, generally entered through a command line interface.
 
-**Transaction:** the unit of work in a data store. Ideally a transaction 
-succeeds or fails as a unit.
+**Transaction:** the unit of work in a data store. The database keeps track of
+the order of transactions submitted by each user, to prevent conflicts. A
+transaction succeeds or fails as a unit, so if an update affects multiple parts
+of a database, the update only succeeds if every individual part of it is
+allowed.
 
 
 ## Types of Data Stores

data/sql_software.csv

@@ -4,3 +4,4 @@ PostgreSQL,"Technical documentation, with robust community support",Free,Open So
 MySQL,"Large community base, No professional support without a paid subscription",Free,Partially Open Source,Built-in vector support
 Microsoft SQL Server,Robust professional and community support,Paid,Proprietary,Built-in vector support
 Oracle,Robust professional and some community support,Paid,Proprietary,Raster and vector support with Spatial Studio
+Microsoft Access,"Not supported, do not use",NA,Proprietary,None