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An empirical or computational research project only becomes a useful building block for science when all steps can be easily repeated and modified by others. This means that we should automate as much as possible, compared to pointing and clicking with a mouse or, more generally, keeping track yourself of what needs to be done. This is a collection of templates where much of this automation is pre-configured via describing the research workflow as a directed acyclic graph DAG using Waf. You just need to: Use cookiecutter to install the template for the main language in your project (Stata, R, Matlab, Python, ...). Move your programs to the right places and change the placeholder scripts. Run Waf, which will build your entire project the first time you run it. Later, it will automatically figure out which parts of the project need to be rebuilt.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 5 |

Views provided by UsageCounts