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[tor-commits] [metrics-web/master] Delete CONTRIB.md.



commit 294a6d097505e0d254ee7019d553b89a41643645
Author: iwakeh <iwakeh@xxxxxxxxxxxxxx>
Date:   Mon Dec 4 11:14:30 2017 +0000

    Delete CONTRIB.md.
    
    CONTRIB.md is partially obsolete and the information it contains is already
    available on the public web-pages.
---
 CONTRIB.md | 89 --------------------------------------------------------------
 1 file changed, 89 deletions(-)

diff --git a/CONTRIB.md b/CONTRIB.md
deleted file mode 100644
index 4f36afe..0000000
--- a/CONTRIB.md
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-Contributor's guide to the Metrics website
-
-Dear contributor to the Metrics website.  This guide shall help you
-understand the design decisions behind building the Metrics website and
-give you starting points where you should look to make it bigger and
-better.
-
-First of all, let's talk briefly about the scope of the Metrics website,
-which we'll be calling Metrics in the following.
-
- - What Metrics is: Metrics is supposed to provide easy access to Tor
-   network data.  The typical Metrics user is neither a researcher nor a
-   developer and is just looking for an easy way to learn more about this
-   Tor network they have been hearing about.  Metrics is giving them data
-   in visual or tabular form, together with explanations that are easy to
-   understand with as little technical language as possible.
-
- - What Metrics is not: The typical Tor researcher or Tor developer would
-   probably want to dive deeper into the data to learn even more about the
-   Tor network.  But in contrast to the average Metrics user they could
-   just fetch the original data from CollecTor and run their own analysis.
-   Metrics is not trying to be the solution for everyone.  If we have to
-   choose, we're aiming for simplicity instead of comprehensiveness.
-
-Now let's take a quick tour of the components that Metrics is made of.
-
- - Data-processing modules: The bulk of Metrics code is running in the
-   background, invisible to Metrics users.  It's the code that takes
-   CollecTor data as input and that produces .csv files that are the basis
-   for graphs and tables on Metrics.  There's usually one such module per
-   generated .csv file that focuses on a different aspect of Tor network
-   data.  All these modules are periodically executed by the system's cron
-   daemon, independent of user requests to the website part of Metrics.
-   See the modules/ subdirectory for the existing data-processing modules.
-   Note that modules don't have to be written in Java even though that's
-   currently the case for all of them.  The only requirement is that
-   there's a shell script to run the module using packages available in
-   Debian stable.  The remaining components of Metrics are all related to
-   its website part.
-
- - Start page: The website part of Metrics is organized into one page per
-   metric, which can be a graph, table, data file, or external link, and
-   the start page to browse available metrics.  Each metric has attributes
-   like a descriptive name, one or more tags (relays, bridges, etc.), a
-   type (graph, table, etc.), and a level (basic or advanced).  All
-   metrics are defined in `website/etc/metrics.json` and displayed in the
-   table on the start page.
-
- - Graph pages: The bulk of graph pages consist of graphing methods in
-   `website/rserve/graphs.R` that are written in R and using the ggplot2
-   graphing library.  These methods read one or more of the .csv files
-   produced by data-processing modules and produce a graph image as
-   output.  Graphs have a few additional attributes in
-   `website/etc/metrics.json` like a description and parameters to
-   customize the graph.  As of writing this guide, there's one exception
-   with the bubble graph which is implemented using JavaScript library
-   D3.js and which might soon be generated on the server using Node.js.
-
- - Table pages: Metrics also provides a few aspects of Tor network data in
-   tabular form with customization options.  Like graphs, the data in
-   these tables is provided using R by reading the previously generated
-   .csv files.  All relevant R code for generating table data is located
-   in `website/rserve/tables.R`.  Again, there are additional attributes
-   in `website/etc/metrics.json` that define what parameters are available
-   to customize table contents and how to format results.
-
- - Data pages: While most Metrics user are not expected to run their own
-   analyses based on raw Tor network data, some of them might want to look
-   deeper into the data they saw in a graph or table.  Metrics provides
-   all pre-aggregated output from its data-processing modules as
-   downloadable .csv files and also documents these file formats in
-   sufficient detail for Metrics users to use them.
-
- - Link pages: Metrics is not the only game in town, and it's great that
-   other developers take the publicly available Tor network data and
-   visualize it in a different way.  Metrics acknowledges these efforts by
-   adding link pages with thumbnails to make it easy for Metrics users to
-   find those external visualizations.
-
- - About page: Most Metrics users have a basic understanding of how Tor
-   works, most likely from reading the main Tor website.  But Metrics
-   should give its users enough explanations to understand where all the
-   Tor network data comes from and how that data is used to learn
-   interesting facts about the Tor network.  That's where the About page
-   comes into play.  The About page consists of a list of frequently used
-   terms and a second list of frequently asked questions.  There could be
-   more documentation, but more text doesn't necessarily mean that users
-   will read more.
-



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