Quantitative Archaeology Wiki

wiki:navigation - created

steko — Tue, 18 Oct 2011 17:35:02 +0100

* Start page * Digging Numbers * Spatial Analysis * Bibliography

wiki:site_notice - created

steko — Tue, 18 Oct 2011 16:57:23 +0100

Quantitative Archaeology Wiki has some code to share with you at

Databases - old revision restored

steko — Fri, 14 Oct 2011 23:05:38 +0100

Commonly used databases include Microsoft access, postgis and MySQL MySQL Once installed a very useful php based web front end can be added (Php must be installed at least but a full LAMP server is recommended). PhpMyAdmin allows a user friendly way of maintaining the database including allowed other people to add, amend, update and delete data depending on the privileges the administrator sets.

navigation - old revision restored

steko — Mon, 12 Sep 2011 18:24:39 +0100

* Start page * Digging Numbers * Spatial Analysis * GRASS GIS * GRASS Scripts * R (with GRASS) * GRASS, R and Databases * Databases * Bibliography

GRASS, R and Databases - old revision restored

steko — Mon, 12 Sep 2011 18:24:16 +0100

In this section we will discuss databases, the GRASS and R commands have already been discussed The databases we will discuss are PostgresGIS and MySQL MySQL As usuall we need to add in the right libraries, spgrass6 and RMySQL amd maptools for nice displays

Quantitative Archaeology Wiki - [Mailing List]

Thu, 12 May 2011 23:19:42 +0100

Welcome. This wiki is dedicated to the development of free documentation about quantitative methods in archaeology, using free/open source software. This means that: * you can contribute and improve the existing documentation, even with small pieces * you should contribute documentation about free and open source software (but general documentation about algorithms and statistical methods is also good) * anyone will be able to read, edit and possibly improve your contributions

Data description - [Importing data]

jd — Sun, 17 Apr 2011 09:10:23 +0100

Starting R for the first time The recommended way to use R is to create a new empty directory (named something like “Digging Numbers” and start R from the command line into that directory. This way, data and command history will be saved just for this workspace. Here's an example for UNIX operating systems.