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"markdown": "---\ntitle: \"How to cite code\"\nsubtitle: \"citation...\"\ndate: 2025-04-28\nsummary: \"summary of how to cite\"\nsidebar: true\nformat:\n html:\n toc: true\n toc-expand: 2\n\ncategories:\n - citation\n - findability\n - code\n---\n\nCiting software is historically not something that researchers have done. Code can\noften be hard to cite and the software used to derive the results of a paper was\nusually seen as a \"detail\" that is not worth mentioning in the body of paper. \n(Perhaps to avoid too many questions about how, exactly, the results in the\npaper were derived.) The last decade has seen a move towards more reproducible\nresearch in economics---mainstream journals require code and usually data for\nquantitative papers---and the proliferation of open-source research software\nhas made it easier to reliably cite the software used for research.\n\nCiting code is particularly important in the area of price statistics to\nfacilitate reproducible research. There are a great many price index methods,\noften with fiddly variations, used by different researchers and it is important to know the exact\nimplementation used to generate a price index in order to reproduce the\nconstruction of that index. Research for price statistics is also\nusually done by government agencies; transparency about the code to generate the results that inform\nthe methods used by government agencies is important to maintain the trust in\nofficial statistics.\n\nFor further reading, the [Turing Way](https://book.the-turing-way.org/communication/citable) provides\na good overview for citing code in research and represents the current state of\nthe world of open-source research software.\n\n## Citing research software\n\nUnlike academic papers, there is no one way to cite a piece of software. How to\ncite a piece of software usually depends on how easy the author makes it. For\nexample, R packages are easy to cite within R using the `citation()` function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ncitation(\"IndexNumR\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nTo cite package 'IndexNumR' in publications use:\n\n White G (2023). _IndexNumR: Index Number Calculation_. R package\n version 0.6.0, <https://github.com/grahamjwhite/IndexNumR>.\n\nA BibTeX entry for LaTeX users is\n\n @Manual{,\n title = {IndexNumR: Index Number Calculation},\n author = {Graham White},\n year = {2023},\n note = {R package version 0.6.0},\n url = {https://github.com/grahamjwhite/IndexNumR},\n }\n\nATTENTION: This citation information has been auto-generated from the\npackage DESCRIPTION file and may need manual editing, see\n'help(\"citation\")'.\n```\n\n\n:::\n:::\n\n\nModern R packages tend to have their own [website with this information on\ndisplay](https://marberts.github.io/piar/authors.html#citation)\nand all [CRAN packages get a DOI](https://cran.r-project.org/web/packages/PriceIndices/index.html)\nto facilitate referencing the use of R packages. Things are less standardized in\nthe Python ecosystem, but the same ideas apply to make projects citeable\n(e.g., [pandas](https://doi.org/10.5281/zenodo.3509134)).\n\nAnother way to cite a piece of research software is to the cite the paper\nintroducing this software, usually in a journal like the [Journal of Open Source\nSoftware](https://joss.theoj.org/), the [Journal of Statistical Software](https://www.jstatsoft.org/index),\nor the [R Journal](https://journal.r-project.org/).\n\n```\n@article{RJ-2021-038,\n author = {Saavedra-Nieves, Alejandro and Saavedra-Nieves, Paula},\n title = {IndexNumber: An R Package for Measuring the Evolution of Magnitudes},\n journal = {The R Journal},\n year = {2021},\n note = {https://rjournal.github.io/},\n volume = {13},\n issue = {1},\n issn = {2073-4859},\n pages = {253-275}\n}\n```\n\nFinally, for code that is not in a mainstream repository like CRAN, or does not\nhave a website with citation information, [citation information can sometimes be\nfound in the source code](https://raw.githubusercontent.com/marberts/piar/refs/heads/main/CITATION.cff).\nGithub helps to find the citation information for a \npackage and displays a button to cite the repository.\n\n## Making software citable\n\nGiven the variety of ways to cite research software, the key to making it\nciteable is making it easy to generate a reference for that software. For R\npackages this happens automatically if the package is available on CRAN; for\nPython packages (and R packages not on CRAN), a service like [Zenodo](https://zenodo.org/) can be used\nto get a DOI to facilitate referencing the software. Although consumers of\nsoftware tend not to get it directly from a source-code\nrepository, citation metadata can be added to github repositories to make them\nmore citeable.\n\n## Example\n\nThe {piar} R package is an example of a piece of software for making price indexes\nthat is highly citeable.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ncitation(\"piar\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nTo cite package 'piar' in publications use:\n\n Martin S (2024). \"piar: Price Index Aggregation R.\" _Journal of Open\n Source Software_, *9*(101), 6781. doi:10.21105/joss.06781\n <https://doi.org/10.21105/joss.06781>.\n\n Martin S (2025). _piar: Price Index Aggregation_.\n doi:10.5281/zenodo.10110046\n <https://doi.org/10.5281/zenodo.10110046>, R package version 0.8.2,\n <https://cran.r-project.org/package=piar>.\n\nTo see these entries in BibTeX format, use 'print(<citation>,\nbibtex=TRUE)', 'toBibtex(.)', or set\n'options(citation.bibtex.max=999)'.\n```\n\n\n:::\n:::\n\n\nThis information is displayed on the [project website](https://marberts.github.io/piar/authors.html#citation)\nand [CRAN](https://cran.r-project.org/web/packages/piar/citation.html).\nThe citation information is contained in the source code, and consequently displayed\nby github, and the readme for the project is adorned with badges giving citation\ninformation. The goal is to have citation information available at each entry\npoint at which a prospective user may first engage with {piar} and to have it\nbe easy to add to a reference list.\n\n",
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"markdown": "---\ntitle: \"How to cite code\"\ndate: 2025-04-28\nsidebar: true\nformat:\n html:\n toc: true\n toc-expand: 2\n\ncategories:\n - citation\n - findability\n - code\n---\n\nCiting software is historically not something that researchers have done. Code can\noften be hard to cite and the software used to derive the results of a paper was\nusually seen as a \"detail\" that is not worth mentioning in the body of paper. \n(Perhaps to avoid too many questions about how, exactly, the results in the\npaper were derived.) The last decade has seen a move towards more reproducible\nresearch in economics---mainstream journals require code and usually data for\nquantitative papers---and the proliferation of open-source research software\nhas made it easier to reliably cite the software used for research.\n\nCiting code is particularly important in the area of price statistics to\nfacilitate reproducible research. There are a great many price index methods,\noften with fiddly variations, used by different researchers and it is important to know the exact\nimplementation used to generate a price index in order to reproduce the\nconstruction of that index. Research for price statistics is also\nusually done by government agencies; transparency about the code to generate the results that inform\nthe methods used by government agencies is important to maintain the trust in\nofficial statistics.\n\nFor further reading, the [Turing Way](https://book.the-turing-way.org/communication/citable) provides\na good overview for citing code in research and represents the current state of\nthe world of open-source research software.\n\n## Citing research software\n\nUnlike academic papers, there is no one way to cite a piece of software. How to\ncite a piece of software usually depends on how easy the author makes it. For\nexample, R packages are easy to cite within R using the `citation()` function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ncitation(\"IndexNumR\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nTo cite package 'IndexNumR' in publications use:\n\n White G (2023). _IndexNumR: Index Number Calculation_. R package\n version 0.6.0, <https://github.com/grahamjwhite/IndexNumR>.\n\nA BibTeX entry for LaTeX users is\n\n @Manual{,\n title = {IndexNumR: Index Number Calculation},\n author = {Graham White},\n year = {2023},\n note = {R package version 0.6.0},\n url = {https://github.com/grahamjwhite/IndexNumR},\n }\n\nATTENTION: This citation information has been auto-generated from the\npackage DESCRIPTION file and may need manual editing, see\n'help(\"citation\")'.\n```\n\n\n:::\n:::\n\n\nModern R packages tend to have their own [website with this information on\ndisplay](https://marberts.github.io/piar/authors.html#citation)\nand all [CRAN packages get a DOI](https://cran.r-project.org/web/packages/PriceIndices/index.html)\nto facilitate referencing the use of R packages. Things are less standardized in\nthe Python ecosystem, but the same ideas apply to make projects citeable\n(e.g., [pandas](https://doi.org/10.5281/zenodo.3509134)).\n\nAnother way to cite a piece of research software is to the cite the paper\nintroducing this software, usually in a journal like the [Journal of Open Source\nSoftware](https://joss.theoj.org/), the [Journal of Statistical Software](https://www.jstatsoft.org/index),\nor the [R Journal](https://journal.r-project.org/).\n\n```\n@article{RJ-2021-038,\n author = {Saavedra-Nieves, Alejandro and Saavedra-Nieves, Paula},\n title = {IndexNumber: An R Package for Measuring the Evolution of Magnitudes},\n journal = {The R Journal},\n year = {2021},\n note = {https://rjournal.github.io/},\n volume = {13},\n issue = {1},\n issn = {2073-4859},\n pages = {253-275}\n}\n```\n\nFinally, for code that is not in a mainstream repository like CRAN, or does not\nhave a website with citation information, [citation information can sometimes be\nfound in the source code](https://raw.githubusercontent.com/marberts/piar/refs/heads/main/CITATION.cff).\nGithub helps to find the citation information for a \npackage and displays a button to cite the repository.\n\n## Making software citable\n\nGiven the variety of ways to cite research software, the key to making it\nciteable is making it easy to generate a reference for that software. For R\npackages this happens automatically if the package is available on CRAN; for\nPython packages (and R packages not on CRAN), a service like [Zenodo](https://zenodo.org/) can be used\nto get a DOI to facilitate referencing the software. Although consumers of\nsoftware tend not to get it directly from a source-code\nrepository, citation metadata can be added to github repositories to make them\nmore citeable.\n\n## Example\n\nThe {piar} R package is an example of a piece of software for making price indexes\nthat is highly citeable.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ncitation(\"piar\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nTo cite package 'piar' in publications use:\n\n Martin S (2024). \"piar: Price Index Aggregation R.\" _Journal of Open\n Source Software_, *9*(101), 6781. doi:10.21105/joss.06781\n <https://doi.org/10.21105/joss.06781>.\n\n Martin S (2025). _piar: Price Index Aggregation_.\n doi:10.5281/zenodo.10110046\n <https://doi.org/10.5281/zenodo.10110046>, R package version 0.8.2,\n <https://cran.r-project.org/package=piar>.\n\nTo see these entries in BibTeX format, use 'print(<citation>,\nbibtex=TRUE)', 'toBibtex(.)', or set\n'options(citation.bibtex.max=999)'.\n```\n\n\n:::\n:::\n\n\nThis information is displayed on the [project website](https://marberts.github.io/piar/authors.html#citation)\nand [CRAN](https://cran.r-project.org/web/packages/piar/citation.html).\nThe citation information is contained in the source code, and consequently displayed\nby github, and the readme for the project is adorned with badges giving citation\ninformation. The goal is to have citation information available at each entry\npoint at which a prospective user may first engage with {piar} and to have it\nbe easy to add to a reference list.\n\n",
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