Here’s a bit of gossip – Avogadro’s constant, the one that lets you work out how much is in a mole of something, is under threat from a bunch of physicists who want to see it declassified as an absolute number, and instead tied to Planck’s constant, which is altogether more complicated to explain but essentially is used in quantum mechanics to bunch things into packets, or quanta. Not very clearly explained, but I’m no physicist. Check out other definitions here and here.

The person who told me this shocking piece of news is a member of the ACS nomenclature committee. Before you all rush out and try to recalculate the number of moles in your morning coffee – don’t panic. My source tells me that on a practical day to day basis, there will be no change, although explaining moles to a tenth-grader will be more difficult if the change ever makes it through.

The paper that started it all was apparently published in the journal Metrologia, by Ian Mills, although I’m having trouble tracking down the paper.

From my brief conversation, it seems that the idea is to relate Avogadro’s number to Planck’s constant so that the number becomes a relationship between the two numbers rather than an exact number. The grandiose phrase I heard was that this would relate Avogadro’s number to the invariants of nature. What would happen in your world if suddenly you had to redefine Avogadro’s number? Anything? Nothing?

Nature Genetics publishes this month an Editorial (“”https://dx.doi.org/10.1038/ng0807-931">Compete, collaborate, compel") on how to provide incentives and credit to authors who deposit data in public repositories—so called procedures for “microattribution”. The idea is to include at the end of papers a complete list of accession codes identifying all the data used in the study. To provide incentive to data producers, a ranking of the most used accessions could be published, generating a measure of the impact of cited database records. Clearly, such an initiative would require “heroic structural solution at the journal level”.

The issue of finding adequate incentives and credit mechanisms for datasets relates to the increasingly intimate relationship between scientific publishing and databases:

the dividing line between the two realms is getting ever fuzzier, and may eventually disappear altogether. As journals have moved online, they have taken on some of the characteristics of databases (searchable, structured, constantly updated). Meanwhile, some databases are starting to mimic certain aspects of journals (peer-reviewed, archival, citable). This has led to the appearance of ‘hybrid’ publication that are both databases and journals depending on how you look at them (Foo and beyond, Timo Hannay, 2007).

One might wonder whether the idea cannot be pushed even one step further and think of merging the concepts of publication, database and computational model into a single entity (a Document, Record and Model, a DReaM…?). In fact, several initiatives in this direction have already been started (see for example YeastPheromoneModel.org, The Center for the Development of a Virtual Tumor). Publishing services could eventually provide something like a “Publishing Integrated Development Environment”, by analogy with IDEs available for software development, with the option to open new projects integrating progressively various contributions using strict identification and control version systems. Different types of credit would go to those initiating a project and providing the necessary initial components and to those contributing, incrementally, to the development of the project. “Presubmission” inquiries would be evaluated to grant potential authors access to the necessary resources (computational or experimental) of the project, which may represent an additional incentive for participation. Upon analysis and interpretation of the results, individual contributions, including data, model, results and documentation, would be “published” in the project after adequate peer-reviewing to ensure strict quality control. These contributions would be uniquely identified and citable. Perhaps some form of “sensitivity analysis” could even provide an instantaneous measure of the impact and relevance of a contribution.

Such a “DReaM” system would certainly not replace good old-fashioned papers, but would rather live in parallel. Its function would be to structure research around important topics by providing a framework for coherent efforts directed to common goals and to facilitate “microattribution” mechanisms not only for data producers but also for modelers.