Why media reporting on discussion papers can lead to manipulated science

During this week discussions on twitter and on the blogs focused on a discussion paper by James Hansen et al in Earth System Dynamics Discussions. The paper forms part of a legal case in the US and basically states that the current and expected warming over the next decades is unprecedented since the last interglacial. In this context the Guardian has run an article on the paper. While they state that the science is not yet peer-reviewed, the authors have run a series of interviews and comments, which is usually happening only when a paper is actually published. As usual I refrain in this blog from commenting on climate politics, but as I have written my PhD on scientific publication processes I would like to focus here on the implications of the media scrutiny within the discussion paper phase of a scientific publication. Continue reading

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Big Data – More risks than chances?

There is an elephant in the room, at every conference in nearly every discipline. The elephant is so extraordinary that everyone seems to want to watch and hype it. In all this trouble a lot of common sense seems to get lost and especially the little mice, who are creeping around the corners, overlooked.

The big topic is Big Data, the next big thing that will revolutionise society, at least when you believe the advertisements. The topic grew in the past few years into something really big, especially as the opportunities of this term are regularly demonstrated by social media companies. Funding agencies and governments have seen this and put Big Data at their top of their science agenda. A consequence are masses of scientist, sitting in conference sessions about Big Data and discussions vary between the question on what it is and how it can be used. Nevertheless, there are a lot of traps in this field, who might have serious consequences for science in general. Continue reading

Data peer review paper backbround: Statistical quality evaluation? What is that?

A basic point of the new paper is the introduction of quality evaluation. But what does this mean and why do I think it is important? Well, for the first question I have to talk a little bit about the background. The common words we use together with quality are assurance and control. Depending on their definition, they are focussing to make the product or the processes, which lead to the product, better. Since the products we are talking about is data, both are focussing to deliver better datasets.

Nevertheless, in peer review we are handling now a different stage, since we are now in the phase, in which we want to quantify the quality. To do this, some points have to be made clear. First is the fact that quality is subjective. Especially, when we think about the peer review process, it is important to keep in mind that this is not an objective process. The quality of the publication entity is defined by the opinion of the reviewers and editor and has therefore inevitably a personal touch. Of cause the same is true for data peer review. Continue reading