0 Introduction

0.1 Background

The massive amounts of data from sensors, which is usually recorded in a high temporal resolution (up to every second) is challenging for data processing and visualisation. Especially if standard tools like MS EXCEL are used, which are not well suited for such tasks to data import restrictions (e.g. rows per spreadsheet limited to maximum 1 million rows in MS EXCEL 2010) or missing built-in features for data aggregation (e.g. calculating one hour median values from the raw data).
In addition operational data often needs to be combined with analytical data (usually with a temporal resolution of days to weeks) for example in order to (1) assess the impact of the plant’s operation scheme (e.g. flow rate) on its performance for reducing specific substances or for (2) calculating substance loads (by multiplying substance concentrations with flow rates)

Within the AQUANES project – in order to address the above challenges for small companies or wa-ter operators – a data visualization and reporting tool was developed with the software R (www.r-project.org), which enables the user to: - Explore online and offline data at different temporal aggregation levels (e.g. raw data or 10 minutes median values)
- Create automated reports not only including the raw (online/offline) data but also with more advanced calculations combining different online and/or offline data (e.g. specific en-ergy demand)

In a first step, the R reporting tool was implemented and tested for the AQUANES site Haridwar, which is described in this report.

0.2 Objective

The objective of this report is to document the following four processes for the R reporting tool:

Note: This report is based on version 0.0.0.9000 of the R package “kwb.pilot”, which is available for download at Github and released using the open-source MIT licence.