Question: **The problem**

When doing a literature review at the start of a process of addressing a specific problem, it's easy to miss related material, if I don't know that it **is** related.

**The example**

Let's say I'm looking at a particular electricity-generation problem relating to pollution costs (in a very broad sense), of combustion and cooling: there might be relevant papers about, say, biodiversity and temperature in river water, that I don't know about, and haven't made the connection to, and it appears in a journal well outside the field of electricity generation.

However, within the literature, there will be authors whose papers span those fields: work on valuing biodiversity (so that loss of biodiversity represents a quantifiable cost), and the effect on biodiversity of changing river temperatures (so that using river-cooling in electricity generation, has a deleterious effect on river biodiversity).

**The proposition**

It should be possible, by doing an analysis of keywords, of co-authorship, and of journals, to automate the building of a network of subjects and of authors, to map out interconnections between specific narrow subject areas, and find the people that work in those interconnecting areas.

**The question**

Is there such a network map of subjects and authors, anywhere? Not just for this specific example, but one that spans a very wide range of literature (e.g. Engineering, Science, Technology, Economics). Ideally, one that gets updated frequently, based on ongoing publications?

As I hope the example above illustrates, it has to be:

* easy to interrogate it;
* very detailed on subject linkages; and
* provide links between people as well as subjects.

Answer: 
Here is a subject map of science:

![Subject map, Borner, K., et al, Plos One](https://i.stack.imgur.com/rM8NB.jpg)

It is taken from the following paper, freely available from Plos One:

<http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039464?imageURI=info:doi/10.1371/journal.pone.0039464.g001>

I think that this is the sort of thing that you are interested in. 

N.B. I am not a co-author, nor have I read the paper, so I make no judgment on its quality.
There is an interactive map on [Eigenfactor](http://www.eigenfactor.org/) (a much better (arguably) way for assessing impact that mere citation counting):

[eigenfactor.org - mapping science](http://www.eigenfactor.org/map/index.php) (currently, only for medicine related)

You can explore disciplines by graph of citations (i.e. which discipline cites which; it need not to be symmetric).