Downloading & Using Pipe-Delimited Text Files

These instructions are for users who have trouble connecting to the live PostreSQL database, or who would like to create a local static copy of the AACT database from the pipe-delimited text file extracts. These text files are created monthly from the live AACT database.

General information about Text Files

  1. Structure of Text Files: The text files were created under a PC environment using UTF-8 encoding. Fields within each file are separated by the vertical bar character (“|”) commonly referred to as a “pipe”. A null or missing value for a field is delineated by consecutive “pipes” in the data stream. Records within each file are delimited by the line feed (LF) character. The first row of each file contains a delimited list of field names and the order of these names indicates the order of the data fields in the text file. Most fields are character and are not enclosed within quotes, although single or double quotes may appear embedded within many of the descriptive fields.
  2. Modifications to Source Content to Facilitate Use of Text Files: In rare cases, the content within a field may contain an embedded pipe (“|”). To prevent software from interpreting the embedded pipe as a delimiter, the entire string has been enclosed in double quotes. Line feed and paragraph break characters within fields, which might otherwise be interpreted as end of record characters, have been removed from the text file database extracts.
  3. Users are encouraged to refer to the Schema Diagram and associated information to determine the relationships between the different data files that comprise AACT. These relationships determine how data sets may be merged together. There is one text file for each database table indicated in the Schema Diagram. In addition, text files containing meta data are available (data_definitions.txt, sanity_checks.txt, statistics.txt) are included. The Data Dictionary provides critical information about datasets and variables, including the expected number of records in a dataset, and the length of each variable.

Download Zip File Containing Pipe-Delimited Files

[{:name=>"", :date_created=>"02/01/2018", :size=>"739 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"01/11/2018", :size=>"734 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"12/17/2017", :size=>"727 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"11/02/2017", :size=>"711 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"10/17/2017", :size=>"706 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"09/06/2017", :size=>"695 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"08/11/2017", :size=>"679 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"06/18/2017", :size=>"450 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"05/08/2017", :size=>"367 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"04/16/2017", :size=>"539 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"02/18/2017", :size=>"356 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"02/01/2017", :size=>"440 MB", :url=>"/static/exported_files/"}, {:name=>"", :date_created=>"01/05/2017", :size=>"412 MB", :url=>"/static/exported_files/"}]
Downloadable File Date Created Size 02/01/2018 739 MB 01/11/2018 734 MB 12/17/2017 727 MB 11/02/2017 711 MB 10/17/2017 706 MB 09/06/2017 695 MB 08/11/2017 679 MB 06/18/2017 450 MB 05/08/2017 367 MB 04/16/2017 539 MB 02/18/2017 356 MB 02/01/2017 440 MB 01/05/2017 412 MB


Extract Contents of Zip File

In Windows, this can be done by right clicking on the file and selecting ‘Extract All…’ from the menu. You will be given the opportunity to choose or create a destination folder to contain the extracted text files. Once the file extraction has completed your destination folder will contain the extracted text files. Files are named according to the database table to which they correspond, for example studies.txt contains the records and variables from the studies database table.


Access Content with Favorite Analysis Tool

The text files can be read with many software tools. The files can even be opened in MS Excel (specify the pipe character as delimiter), however some of the files are very large and this is not recommended. Tips are provided for SAS and R software.