There is a particularly insidious trend in meta-analysis, that the size of research fields doubles every nine years. If you have tried a meta-analysis before, overwhelmed by the effort, consider that nine years later it will be twice as difficult. Try it yourself. Search a topic at Semantic Scholar and use the Date Range function to see just what has been done in the last nine years and find it is probably more than half. Something has to give.
At the beginning, during the 1970s when Glass and Hunter & Schmidt as well as Hedges and Rosenthal got their start, the challenge was finding enough data. Though my own start was a mite bit later, it was still in the days of inter-library loans, going to the stack and searching through micro-fiches. Today, it is quite the opposite. There is an explosion of resources and the goal is often to whittle your topic down to a manageable size, something that hopefully can be done to allow graduation or at least to get into your tenure file.
Consequently, yes, we have HubMeta, which focuses on the improving the coding platform. Part of my path here was developing my coding platform, MetaExcel back in 2001, and it allowed me to tackle topics larger than what others could traditionally do. Truly, better science is often the result of improved tools rather than new theories, which we have too many of anyway (everyone wants to develop their own and no one wants to prune away the redundancy). Even better than HubMeta would be us learning how to co-author together.
To this end, a really great read is “The Cooperative Revolution Is Making Psychological Science Better.” It reviews all these other large science efforts, such as ManyLabs, the Psychological Science Accelerator, and Curate Science, efforts to self-organize fellow scientists into more powerful groups. The essence of progress is reciprocal altruism, so when the authors conclude “The value of tools like these — both during these projects and after the research is complete — cannot be overstated,” you can’t but help to agree.
Enabling collaboration is what we still need to refine on HubMeta. We are making really amazing strides in increasing the rate of individual coders, up an entire of magnitude, but piecing multiple coders together is the challenge. Right now, we made a forum to help like minded individuals, but issues of contribution and trust are always difficult in co-authorship. As they say, the juice is worth the squeeze as it allows tackling projects no one else can. I’ll be giving this more discussion, but if you have principles to share, sharing is caring. We will put them together, along with other resource, for recommended steps as you tackle your own mega projects.