I’ve set a goal of bringing the number of entries missing preferred citation information to under 1000, though that might be just beyond possible. When I started this process, there were 1284 entries without a preferred citation; I’ve examined the software sites and documentation of 150+ of these codes so far and have found explicit citation information for just over 14% of these.
In general, we include a preferred citation in an ASCL record when a code’s site or documentation explicitly states what should be cited (“cite [code] with this [ASCL entry/article/DOI/etc.]”). We don’t assume a paper listed under “References” or “Articles” is intended to be for citation, though that may be the intent of some authors listing them, as some list these papers because a code is built upon others’ work, or these papers include research that used the software.
In some cases, a particular software has no citations to the ASCL record and numerous citations (> 25, let’s say) to a code description paper even though the download site or repo does not specify how the software should be cited. Allowing this “apparent established practice” of citation to substitute for an explicit statement and listing the description paper as the preferred citation seems fair to me, and valuable to those who want to do the right thing by citing a software package but don’t find guidance for how to do so on the code’s site.
We very much prefer that authors provide explicit information on their preferred citation for their programming work, but where they don’t, and where there is an apparent established practice of citation, we will now list that citation method as the preferred citation in the ASCL entry. So far, this inferred information has been added to 15 ASCL entries.
Do you want to discuss different software citation methods before selecting a preferred method? Did I get your software’s preferred citation wrong or miss it entirely? If so, please let me know via email or the Suggest a change link at the bottom of your code’s ASCL entry.
At lunch yesterday, I was asked in what year the earliest code ASCL has was written (or was first created). I didn’t know off the top of my head, but thought probably in late 70s. (The earliest I ever pursued was from the 60s, IIRC, & though I found an working email address for the woman who wrote it, which was amazing in itself, she no longer had the code, alas.)
But the question got me to wondering, so in a quick look, here’s what I found: three codes that were initially created in 1978:
All of these have undergone further development and are still in use, as indicated by citations to them in papers published this year.
Are these the most long-lived codes we have? Are there codes that were started even before 1978 that are still in use? Probably. Maybe part of the Starlink (ascl:1110.012) code base? Something else?
If you know of one or can find one in the ASCL with a history that goes back further than 1978, please let us know in the replies.
UPDATE, August 21, 2019
Yes! There is one code that goes back even further, to 1972. Warrick Ball (@warrickball), a postdoc at the University of Birmingham (U.K.), replied on Twitter that the stellar evolution code STARS (ascl:1107.008) got its start in 1971, and the 1972 article which describes the code is listed in the ASCL entry for it. The code is still in use and was cited earlier this year. There’ll be dark chocolate heading Dr. Ball’s way as soon as the weather cools off; kudos to him for finding the answer to this question!
We were asked recently how many of our entries were attributed to one, two, or three authors. Would you guess that over a third of the codes in the ASCL — 35% — have only one author? Codes with 1-3 authors attributed, what we dubbed “short author list” codes, account for 68% of our entries. We ended up writing a short paper, published by Research Notes of the AAS (RNAAS), about authorship and citation numbers for team and short author list codes. It was a quick look and we hope to look more deeply into this; if you’d like to do the same, you can download our public data in JSON and find the code that we used for consolidating citations on GitHub.