ASCL News
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Abstract: Software citation is good for research transparency and reproducibility, and maybe, if you work it right, for your CV, too. You can get credit and recognition through citations for your code! This presentation highlights several powerful methods for increasing the probability that use of your research software will be cited, and cited correctly. The presentation covers how to create codemeta.json and CITATION.cff automagically from Astrophysics Source Code Library (ASCL ascl.net) entries, edit, and use these files, the value of including such files on your code site(s), and efforts underway in astronomy and other fields to improve software citation and credit.Authors: A. Allen1,2, R. Nemiroff3, P. Ryan1, J. Schmidt1, P. Teuben2
1Astrophysics Source Code Library
2Astronomy Department, University of Maryland, College Park, MD
3Michigan Technological University, Houghton, MIDownload (PDF)
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The ASCL is participating in the American Astronomical Society (AAS) meeting that started yesterday in Honolulu, Hawai'i. We have two events, both on Sunday, January 5:
Best ways to let others know how to cite your research software
January 5; Poster 109.12
Software citation is good for research transparency and reproducibility, and maybe, if you work it right, for your CV, too. You can get credit and recognition through citations for your code! This presentation highlights several powerful methods for increasing the probability that use of your research software will be cited, and cited correctly. The presentation covers how to create codemeta.json and CITATION.cff automagically from Astrophysics Source Code Library (ASCL ascl.net) entries, edit, and use these files, the value of including such files on your code site(s), and efforts underway in astronomy and other fields to improve software citation and credit.The Future and Future Governance of the Astrophysics Source Code Library
January 5, 2:00 PM - 3:30 PM; HCC - Room 301B
Over the past ten years, the Astrophysics Source Code Library (ASCL, ascl.net) has grown from a small repository holding about 40 codes with hand-coded HTML pages maintained by one person to a resource with citable entries on over 2000 codes with a modern database structure that is user- and editor-friendly maintained by a small group of volunteers. With its 20th anniversary now behind it, it's time to look at the resource and its governance and management. Does its current structure best serve the astro community? What changes would you like to see to its governance? We don't know the answers to these and other questions! Please join us for an open discussion on the resource and what a new governance model for the ASCL might be.
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Twenty-four codes were added to the ASCL in November 2019:
ATHOS: A Tool for HOmogenizing Stellar parameters
ATLAS: Turning Dopplergram images into frequency shift measurements
CLUSTEREASY: Lattice simulator for evolving interacting scalar fields in an expanding universe on parallel computing clusters
comb: Spectral line data reduction and analysis packageFFTLog-and-beyond: Generalized FFTLog algorithm
frbpoppy: Fast radio burst population synthesis in Python
Fruitbat: Fast radio burst redshift estimation
HeatingRate: Radioactive heating rate and macronova (kilonova) light curveHLattice: Scalar fields and gravity simulator for the early universe
IDG: Image Domain Gridding
LATTICEEASY: Lattice simulator for evolving interacting scalar fields in an expanding universe
MARTINI: Mock spatially resolved spectral line observations of simulated galaxiesmiluphcuda: Smooth particle hydrodynamics code
MORDI: Massively-Overlapped Ring-Diagram Inversion
OpenSPH: Astrophysical SPH and N-body simulations and interactive visualization tools
OrbWeaver: Galaxy/(sub)halo orbital processing toolPLAN: A Clump-finder for Planetesimal Formation Simulations
planetplanet: General photodynamical code for exoplanet light curves
PypeIt: Python spectroscopic data reduction pipeline
TreeFrog: Construct halo merger trees and compare halo catalogsuvplot: Interferometric visibilities plotter
VELOCIraptor-STF: Six-dimensional Friends-of-Friends phase space halo finder
WhereWolf: Galaxy/(sub)Halo ghosting tool for N-body simulations
Zeltron: Explicit 3D relativistic electromagnetic Particle-In-Cell code -
Twenty-two codes were added to the ASCL in October 2019:
a3cosmos-gas-evolution: Galaxy cold molecular gas evolution functions
ANNz2: Estimating photometric redshift and probability density functions using machine learning methods
AOtools: Adaptive optics modeling and analysis toolkit
AOTOOLS: Reduce IR images from Adaptive Optics
ChainConsumer: Corner plots, LaTeX tables and plotting walksCobaya: Bayesian analysis in cosmology
DM_phase: Algorithm for correcting dispersion of radio signals
E0102-VR: Virtual Reality application to visualize the optical ejecta in SNR 1E 0102.2-7219
ECLIPS3D: Linear wave and circulation calculations
EMERGE: Empirical ModEl for the foRmation of GalaxiEsexoplanet: Probabilistic modeling of transit or radial velocity observations of exoplanets
GetDist: Monte Carlo sample analyzer
LEO-Py: Likelihood Estimation of Observational data with Python
MarsLux: Illumination Mars maps generator
MiSTree: Construct and analyze Minimum Spanning Tree graphsOCD: O'Connell Effect Detector using push-pull learning
orbitize: Orbit-fitting for directly imaged objects
PEXO: Precise EXOplanetology
PINK: Parallelized rotation and flipping INvariant Kohonen maps
PreProFit: Pressure Profile Fitter for galaxy clusters in Pythonqnm: Kerr quasinormal modes, separation constants, and spherical-spheroidal mixing coefficients calculator
TLS: Transit Least Squares -
Fourteen codes were added to the ASCL in September 2019:
AREPO: Cosmological magnetohydrodynamical moving-mesh simulation code
Auto-multithresh: Automated masking for clean
ChempyMulti: Multi-star Bayesian inference with Chempy
CLOVER: Convolutional neural network spectra identifier and kinematics predictor
EBHLIGHT: General relativistic radiation magnetohydrodynamics with Monte Carlo transportEPOS: Exoplanet Population Observation Simulator
fgivenx: Functional posterior plotter
HADES: Hexadecapolar Analysis for Dust Estimation in Simulations (of CMB B-mode thermal dust emission)
HISS: HI spectra stacker
MultiColorFits: Colorize and combine multiple fits images for visually aesthetic scientific plotsRascalC: Fast code for galaxy covariance matrix estimation
SecularMultiple: Hierarchical multiple system secular evolution model
TPI: Test Particle Integrator
WVTICs: SPH initial conditions using Weighted Voronoi Tesselations -
Twenty-five codes were added to the ASCL in August 2019:
actsnclass: Active learning for supernova photometric classification
Analysator: Quantitative analysis of Vlasiator files
BEAST: Bayesian Extinction And Stellar Tool
bias_emulator: Halo bias emulator
dips: Detrending periodic signals in timeseriesDustCharge: Charge distribution for a dust grain
EBAI: Eclipsing Binaries with Artificial Intelligence
FastCSWT: Fast directional Continuous Spherical Wavelet Transform
FIRST Classifier: Automated compact and extended radio sources classifier
GBKFIT: Galaxy kinematic modelingGramsci: GRAph Made Statistics for Cosmological Information
JPLephem: Jet Propulsion Lab ephemerides package
MAESTROeX: Low Mach number stellar hydrodynamics code
Molsoft: Molonglo Telescope Observing Software
MosfireDRP: MOSFIRE Data Reduction PipelineNuRadioMC: Monte Carlo simulation package for radio neutrino detectors
oscode: Oscillatory ordinary differential equation solver
PyRADS: Python RADiation model for planetary atmosphereS
PYSAT: Python Satellite Data Analysis Toolkit
QAC: Quick Array Combinations front end to CASAQLF: Luminosity function analysis code
SNAPDRAGONS: Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems
TRISTAN-MP: TRIdimensional STANford - Massively Parallel code
Vlasiator: Hybrid-Vlasov simulation code
YMW16: Electron-density model -
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.
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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:
Cloudy (ascl:9910.001)
AIPS (ascl:9911.003)
ADIPLS (ascl:1109.002)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! -
Thirty-two codes were added to the ASCL in July 2019:
Astro-SCRAPPY: Speedy Cosmic Ray Annihilation Package in Python
astrodendro: Astronomical data dendrogram creator
beamconv: Cosmic microwave background detector data simulator
CMDPT: Color Magnitude Diagrams Plot Tool
Dewarp: Distortion removal and on-sky orientation solution for LBTI detectorsGaussPy: Python implementation of the Autonomous Gaussian Decomposition algorithm
GaussPy+: Gaussian decomposition package for emission line spectra
GIST: Galaxy IFU Spectroscopy Tool
healvis: Radio interferometric visibility simulator based on HEALpix maps
intensitypower: Spectrum multipoles modelerMCRGNet: Morphological Classification of Radio Galaxy Network
MGB: Interactive spectral classification code
molly: 1D astronomical spectra analyzer
OMNICAL: Redundant calibration code for low frequency radio interferometers
Plonk: Smoothed particle hydrodynamics data analysis and visualizationPOCS: PANOPTES Observatory Control System
PRISM: Probabilistic Regression Instrument for Simulating Models
pyGTC: Parameter covariance plots
pyuvdata: Pythonic interface to interferometric data sets
REVOLVER: REal-space VOid Locations from suVEy ReconstructionROHSA: Separation of diffuse sources in hyper-spectral data
RVSpecFit: Radial velocity and stellar atmospheric parameter fitting
SARA-PPD: Preconditioned primal-dual algorithm for radio-interferometric imaging
sbpy: Small-body planetary astronomy
schwimmbad: Parallel processing pools interfaceSkyfield: High precision research-grade positions for planets and Earth satellites generator
SPAM: Hu-Sawicki f(R) gravity imprints search
StePar: Inferring stellar atmospheric parameters using the EW method
TurbuStat: Turbulence statistics in spectral-line data cubes
Wōtan: Stellar detrending methodsXDF-GAN: Mock astronomical survey generator
ZChecker: Zwicky Transient Facility moving target checker for short object lists -
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.
