Some high principles

I will try to stick to a few high principles of conduct:
I will never hide how the numbers presented are calculated. I explain the operations and the source code is available for download here.
You shall be able to trace all the numbers presented back to the sources.
Although I don’t think it is even possible to be 100 percent objective in all situations, but I will try my best to draw a line between objective facts and my own, or other people’s opinions and reflections. I do not intend to cherry pick the data or suppress any evidence, and I think the best guarantee for avoiding that is to have a blog open to comment the statistics.
Multiple independent sources
It is always a good practice to check more than one source before you make up your mind. This principle applies here as well as any other place.
Trustworthy data sources use data from a variety of sources. Some of the data comes from primary sources such as the NASA CERES data. Other types of data come from parties that have gathered primary data and publish processed statistics. These parties are notable organizations like UN, The World Bank, National Environmental agencies, metrological organization and some corporations like RSS and BP
Renowned references
The most trustworthy references are peer-reviewed articles published in reputable scientific journals. Some of the references goes to such primary sources. However, academic papers are often aimed at a narrow audience in a specific scientific discipline. Providing links to scientific papers alone could be a barrier to understanding. I have therefore also included links to good articles written for the general public audience as long as they come from reputable sources who takes responsibility for the content. Anonymous Internet articles are not used.

Moreover, the data sources should also fulfill these requirements:

The time series should span at least two decades. focus on the long term trends because those trends tells which direction the world is heading. Short-term statistics with trends that go up one year, down the next and then up again the third does not tell anything.
Avoidance of excessive data processing.
Data closer to the original source are in general more trustworthy than highly transformed data. For pollution, I would for example prefer a measurement of “average number of particles per cubic meter” rather than “number of people affected by unhealthy particle pollution”. For the latter there is a long way from the instrument readings to the numbers presented. I think it would be difficult to maintain a consistent measurement standard for such transformations over time and by different nations around the globe.

Please tell me if you think these principles are inadequate or if I deviate from these principles. I am very grateful for corrections, and suggestions to make this a better site.