This is a backend for Transparency Toolkit's other tools (LookingGlass, Harvester, Catalyst). It indexes data, stores the documents, and processes queries all in one place. All the specifications for what data sources are available and what fields they have are also handled by DocManager.

• elasticsearch 5.4.0
• ruby 2.4.1
• rails 5
• postgresql

1. Install the dependencies and configure

• Download elasticsearch (https://www.elastic.co/downloads/elasticsearch)
• Install postgresql: apt-get install postgresql postgresql-client
• Download rvm (https://rvm.io/rvm/install)
• rvm install 2.4.1 and rvm use 2.4.1
• gem install rails
• bundle install
• rake db:create db:migrate

2. Run

• Start elasticsearch (exact method depends on installation method)
• rails server

Configuration files for data sources and projects are stored in the dataspec_files directory. This has three directories with three types of sub-files-

• projects: A project is a collection of all data on a particular topic (or that you want stored in the same elasticsearch index). It is only possible to access one project at a time, but you can switch between multiple projects. Each project can have multiple data sources. The configuration files specifying what data sources a project includes, what it is called, etc. are in the projects directory.
• data_sources: Each data source needs a config file to specify what fields it has, where each should show up on the various apps, it's name, etc. The correct data source file is automatically loaded into the other apps when needed and all supported data sources have pre-written config files.
• fields_for_all_sources: These config files specify what fields every data source has, such as those Harvester uses for managing versions and threads. The fields in this directory will be loaded into every data source automatically.

These files are automatically loaded into DocManager and used by the apps that query it. But the specific project you want to access/use may need to be set in configuration options in the other apps.

The code is divided into the following components:

• analyzers: Config files that elasticsearch uses to determine how it should index data in various languages.
• controllers: Handle incoming requests to the API. These don't have much content themselves, but mostly include other functions for managing indexing, queries, and dataspecs.
• dataspec: Load in the project and data source config files, generate models for new data sources using metaprogramming, and retrieves the appropriate source and project objects when requested.
• index: Indexes the data in elasticsearch, including preprocessing tasks like setting a unique ID (that is consistent across reindexes), tracking different versions of the same data, handling different formats of date fields, and generally managing messy data. Also handles data deletion.
• models: Specify the fields that should be saved in the database for projects and data sources. Most of the management and creation of these sources is initially handled in the modules in the dataspec directory.
• queries: Process and run elasticsearch queries. Includes everything from getting the documents to load and showing the total number to actual search queries.