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joss.07024/10.21105.joss.07024.crossref.xml | 220 ++++++++++++++++++++ 1 file changed, 220 insertions(+) create mode 100644 joss.07024/10.21105.joss.07024.crossref.xml diff --git a/joss.07024/10.21105.joss.07024.crossref.xml b/joss.07024/10.21105.joss.07024.crossref.xml new file mode 100644 index 0000000000..2b901a6f58 --- /dev/null +++ b/joss.07024/10.21105.joss.07024.crossref.xml @@ -0,0 +1,220 @@ + + + + 20240906141826-4cf413064b14c56ec399a7c7f63b32b3a564ba08 + 20240906141826 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 09 + 2024 + + + 9 + + 101 + + + + densify: An R package to reduce empty cells in data +frames of typological linguistic data + + + + Anna + Graff + https://orcid.org/0000-0002-7703-3471 + + + Marc + Lischka + https://orcid.org/0009-0007-9493-2392 + + + Taras + Zakharko + https://orcid.org/0000-0001-7601-8424 + + + Reinhard + Furrer + https://orcid.org/0000-0002-6319-2332 + + + Balthasar + Bickel + https://orcid.org/0000-0002-9087-0565 + + + + 09 + 06 + 2024 + + + 7024 + + + 10.21105/joss.07024 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.13384828 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/7024 + + + + 10.21105/joss.07024 + https://joss.theoj.org/papers/10.21105/joss.07024 + + + https://joss.theoj.org/papers/10.21105/joss.07024.pdf + + + + + + WALS online (v2020.3) + 10.5281/zenodo.7385533 + 2013 + Dryer, M. S., & Haspelmath, M. +(Eds.). (2013). WALS online (v2020.3) [Data set]. Zenodo. +https://doi.org/10.5281/zenodo.7385533 + + + admmDensestSubmatrix: Alternating direction +method of multipliers to solve dense dubmatrix problem + Ames + 10.32614/cran.package.admmdensestsubmatrix + 2019 + Ames, B., & Bombina, P. (2019). +admmDensestSubmatrix: Alternating direction method of multipliers to +solve dense dubmatrix problem. +https://doi.org/10.32614/cran.package.admmdensestsubmatrix + + + FSelector: Selecting attributes + Romanski + 10.32614/cran.package.fselector + 2023 + Romanski, P., Kotthoff, L., & +Schratz, P. (2023). FSelector: Selecting attributes. +https://doi.org/10.32614/cran.package.fselector + + + Ape 5.0: An environment for modern +phylogenetics and evolutionary analyses in R + Paradis + Bioinformatics + 35 + 10.1093/bioinformatics/bty633 + 2019 + Paradis, E., & Schliep, K. +(2019). Ape 5.0: An environment for modern phylogenetics and +evolutionary analyses in R. Bioinformatics, 35, 526–528. +https://doi.org/10.1093/bioinformatics/bty633 + + + The AUTOTYP database (v1.1.1) + Bickel + 10.5281/zenodo.7976754 + 2023 + Bickel, B., Nichols, J., Zakharko, +T., Witzlack-Makarevich, A., Hildebrandt, K., Rießler, M., Bierkandt, +L., Zúñiga, F., & Lowe, J. B. (2023). The AUTOTYP database (v1.1.1). +https://doi.org/10.5281/zenodo.7976754 + + + Lexibank analysed + List + 10.5281/zenodo.7836668 + 2023 + List, J.-M., Forkel, R., Greenhill, +S. J., Rzymski, C., Englisch, J., & Gray, R. D. (2023). Lexibank +analysed (Version v1.0) [Data set]. Zenodo. +https://doi.org/10.5281/zenodo.7836668 + + + cldf-datasets/phoible: PHOIBLE 2.0.1 as CLDF +dataset + Moran + 10.5281/zenodo.2677911 + 2019 + Moran, S., & McCloy, D. (2019). +cldf-datasets/phoible: PHOIBLE 2.0.1 as CLDF dataset (Version v2.0.1) +[Data set]. Zenodo. +https://doi.org/10.5281/zenodo.2677911 + + + Grambank v1.0 + Skirgård + 10.5281/zenodo.7740140 + 2023 + Skirgård, H., Haynie, H. J., +Hammarström, H., Blasi, D. E., Collins, J., Latarche, J., Lesage, J., +Weber, T., Witzlack-Makarevich, A., Dunn, M., Reesink, G., Singer, R., +Bowern, C., Epps, P., Hill, J., Vesakoski, O., Abbas, N. K., Ananth, S., +Auer, D., … Gray, R. D. (2023). Grambank v1.0 (Version v1.0). Zenodo. +https://doi.org/10.5281/zenodo.7740140 + + + Glottolog/glottolog: Glottolog database +5.0 + Hammarström + 10.5281/zenodo.10804357 + 2024 + Hammarström, H., Forkel, R., +Haspelmath, M., & Bank, S. (2024). Glottolog/glottolog: Glottolog +database 5.0 (Version v5.0) [Data set]. Zenodo. +https://doi.org/10.5281/zenodo.10804357 + + + Varrank: Heuristics tools based on mutual +information for variable ranking + Kratzer + 10.32614/cran.package.varrank + 2022 + Kratzer, G., & Furrer, R. (2022). +Varrank: Heuristics tools based on mutual information for variable +ranking. +https://doi.org/10.32614/cran.package.varrank + + + + + + From f634e3dd54fe72a96236ed0969296d41e4a82713 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Fri, 6 Sep 2024 15:18:51 +0100 Subject: [PATCH 3/3] Creating 10.21105.joss.07024.jats --- .../paper.jats/10.21105.joss.07024.jats | 530 ++++++++++++++++++ 1 file changed, 530 insertions(+) create mode 100644 joss.07024/paper.jats/10.21105.joss.07024.jats diff --git a/joss.07024/paper.jats/10.21105.joss.07024.jats b/joss.07024/paper.jats/10.21105.joss.07024.jats new file mode 100644 index 0000000000..faecfe56a3 --- /dev/null +++ b/joss.07024/paper.jats/10.21105.joss.07024.jats @@ -0,0 +1,530 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +7024 +10.21105/joss.07024 + +densify: An R package to reduce empty cells in data +frames of typological linguistic data + + + +https://orcid.org/0000-0002-7703-3471 + +Graff +Anna + + + + +* + + +https://orcid.org/0009-0007-9493-2392 + +Lischka +Marc + + + + +https://orcid.org/0000-0001-7601-8424 + +Zakharko +Taras + + + + + +https://orcid.org/0000-0002-6319-2332 + +Furrer +Reinhard + + + + + +https://orcid.org/0000-0002-9087-0565 + +Bickel +Balthasar + + + + + + +University of Zurich, Department of Comparative Language +Science + + + + +University of Zurich, Department of Evolutionary Biology +and Environmental Studies + + + + +University of Zurich, Center for the Interdisciplinary +Study of Language Evolution + + + + +University of Zurich, Department of Mathematical Modeling +and Machine Learning + + + + +* E-mail: + + +21 +8 +2024 + +9 +101 +7024 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +sparse matrices +sub-sampling +linguistic data +diversity samples +R + + + + + + Summary +

The R package densify provides a procedure + to prune input data frames containing empty cells (or cells with + values {?} or {NA}) to denser sub-matrices with fewer empty cells. The + pruning process trades off a series of variably weighted concerns, + including data retention, coding density (proportion of non-empty + cells) and taxonomic diversity of rows (representing for example + phylogenetic relations). Users can adapt the relative weights given to + these concerns through various parameters so that the densification + process best fits their needs. As such, the software is useful for + several purposes, including the densification of sparse input matrices + and the subsampling of large input matrices according to a procedure + that is sensitive to taxonomic structure.

+
+ + Statement of Need +

Linguistic typological data is increasingly available in + large-scale databases, and many analyses that aim at exploring + diversity or testing hypotheses rely on such databases. Some of these + resources have information for nearly all features (sometimes also + called characters, parameters or variables) across nearly all + languages in the database (i.e. they have complete or near-complete + coding density), but the dataframe may be too large for certain + computationally intensive analyses (e.g., PHOIBLE + (Moran + & McCloy, 2019), Grambank + (Skirgård + et al., 2023)). Other databases (e.g., WALS + (Dryer + & Haspelmath, 2013), AUTOTYP + (Bickel + et al., 2023), Lexibank + (List + et al., 2023)) exhibit features that are coded for different + sets of languages, resulting in sparse language-feature matrices. + Combining data from various databases via language identifiers like + glottocodes + (Hammarström + et al., 2024) usually increases sparsity because the language + samples do not match.

+

When datasets are too large or too sparse for computational + applications, it can thus be necessary to generate and subsequently + operate on a subset of the data represented in a smaller and denser + matrix. Thereby, researchers might be particularly interested in + maintaining taxonomic diversity in the languages represented, + preferentially removing languages belonging to clades represented by + many other languages in the sample and penalizing the removal of + language isolates or languages which represent small language + families.

+

While certain packages exist to generate sub-matrices from varying + input matrices according to principled criteria (e.g., + admmDensestSubmatrix + (Ames + & Bombina, 2019), which identifies the densest sub-matrix + of an input graph of a specified size; or + FSelector + (Romanski + et al., 2023) and varrank + (Kratzer + & Furrer, 2022), which perform attribute subset selection + based on various tests and entropy measures to identify the most + relevant attributes of a data input), densify + adds sensitivity to taxonomic structure and generally more flexibility + in parameter settings for the user. The algorithm focuses both on the + removal of rows and columns and does not require the size of the + sub-matrix to be specified a priori.

+

The software therefore addresses recurring problems researchers + face when working with typological linguistic data, and it was + primarily designed to handle such data frames (with rows representing + languages and columns representing typological features). However, it + will run on any data frame with rows representing any entities with or + without taxonomic structure and columns representing variables. It may + thus be of use for other applications as well.

+
+ + Usage +

The package densify provides the data from + The World Atlas of Language Structures (WALS) + (Dryer + & Haspelmath, 2013) and the language taxonomy provided by + Glottolog v. 5.0 + (Hammarström + et al., 2024) as example data. The accompanying package + vignette features a detailed demonstration of the utility and + flexibility of densify to subsample an input + matrix according to varying needs, using this data.

+

Input data must be prepared in a dataframe with rows representing + taxa or observations with taxon names specified in a dedicated column, + and columns representing variables with variable names as column + names. Cells that are empty or contain non-applicable or question mark + entries must be coded as NA. If densification + should be sensitive to taxonomic structure, a taxonomy must be + provided as (i) a phylo object (cf. + Paradis + & Schliep, 2019), (ii) as an adjacency table (i.e. a data + frame containing columns id and + parent_id, with each row encoding one + parent-child relationship), or (iii) by the + glottolog_languoids dataframe provided by the + package. Every taxon in the input data frame must be included in the + taxonomy (as a tip or node).

+

Iterative pruning of the input matrix is performed by the + densify() function, which can be modulated by + several parameters (described in detail in the function documentation + and the vignette). It returns a specially formatted tibble (a + densify_result object), which describes the + result of each densification step alongside some summary statistics. + The function rank_results() ranks the densify + results accoring to a specifiable, subjectively useful scoring + function that recruits these summary statistics. The optimal + sub-matrix according to the scoring function receives rank 1 and can + be directly retrieved by the function prune(). + visualize(), an alias of + plot(), visually compares the quality scores + between different pruning steps. The default scoring function used by + rank_results(), prune() + and visualize() maximizes the product of the + number of available data points and the overall coding density, but it + can be adjusted to include other measures and trade off their relative + weight.

+
+ + Conclusions +

The R package densify provides users with a + flexible and explicit method to generate sub-matrices from an input + matrix in a mathematically principled way. The package documents case + examples using a standard sparse linguistic dataset (WALS) and the + standard linguistic taxonomy provided by Glottolog.

+

Examples and further usage details for this software are found in + the vignette hosted in the software repository on GitHub.

+
+ + Acknowledgements +

The authors declare that there are no conflicts of interest.

+
+ + + + + + + WALS online (v2020.3) + + DryerMatthew S. + HaspelmathMartin + + Zenodo + 2013 + https://doi.org/10.5281/zenodo.7385533 + 10.5281/zenodo.7385533 + + + + + + AmesBrendan + BombinaPolina + + admmDensestSubmatrix: Alternating direction method of multipliers to solve dense dubmatrix problem + 2019 + https://doi.org/10.32614/cran.package.admmdensestsubmatrix + 10.32614/cran.package.admmdensestsubmatrix + + + + + + RomanskiPiotr + KotthoffLars + SchratzPatrick + + FSelector: Selecting attributes + 2023 + https://doi.org/10.32614/cran.package.fselector + 10.32614/cran.package.fselector + + + + + + ParadisEmmanuel + SchliepKlaus + + Ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R + Bioinformatics + 2019 + 35 + 10.1093/bioinformatics/bty633 + 526 + 528 + + + + + + BickelBalthasar + NicholsJohanna + ZakharkoTaras + Witzlack-MakarevichAlena + HildebrandtKristine + RießlerMichael + BierkandtLennart + ZúñigaFernando + LoweJohn B + + The AUTOTYP database (v1.1.1) + 2023 + https://doi.org/10.5281/zenodo.7976754 + 10.5281/zenodo.7976754 + + + + + + ListJohann-Mattis + ForkelRobert + GreenhillSimon J. + RzymskiChristoph + EnglischJohannes + GrayRussell D. + + Lexibank analysed + Zenodo + 202304 + https://doi.org/10.5281/zenodo.7836668 + 10.5281/zenodo.7836668 + + + + + + MoranSteven + McCloyDaniel + + cldf-datasets/phoible: PHOIBLE 2.0.1 as CLDF dataset + Zenodo + 201905 + https://doi.org/10.5281/zenodo.2677911 + 10.5281/zenodo.2677911 + + + + + + SkirgårdHedvig + HaynieHannah J. + HammarströmHarald + BlasiDamian E. + CollinsJeremy + LatarcheJay + LesageJakob + WeberTobias + Witzlack-MakarevichAlena + DunnMichael + ReesinkGer + SingerRuth + BowernClaire + EppsPatience + HillJane + VesakoskiOuti + AbbasNoor Karolin + AnanthSunny + AuerDaniel + BakkerNancy A. + BarbosGiulia + BollsAnina + BorgesRobert D. + BrowenMitchell + ChevallierLennart + DanielsenSwintha + DohlenSino?l + DorenbuschLuise + DornElla + DuhamelMarie + AliFarah El Haj + ElliottJohn + FalconeGiada + FehnAnna-Maria + FischerJana + AteYustinus Ghanggo + GibsonHannah + G?belHans-Philipp + GoodallJemima A. + GrunerVictoria + HarveyAndrew + HayesRebekah + HeerLeonard + MirandaRoberto E. Herrera + H?blerNataliia + Huntington-RaineyBiu H. + IngleseGuglielmo + IvaniJessica K. + JohnsMarilen + JustErika + KapitonovIvan + KashimaEri + KipfCarolina + KlingenbergJanina V. + K?nigNikita + KotiAikaterina + KowalikRichard G. A. + KrasnoukhovaOlga + LindseyKate Lynn + LindvallNora L. M. + LorenzenMandy + LutzenbergerHannah + MarleyAlexandra + MartinsT?nia R. A. + GermanCelia Mata + MeerSuzanne van der + MontoyaJaime + M?llerMichael + MuradogluSaliha + HunterGatherer + NashDavid + NeelyKelsey + NickelJohanna + NorvikMiina + OlssonBruno + OluochCheryl Akinyi + OsgarbyDavid + PeacockJesse + PeareyIndia O. C. + PeckNaomi + PeterJana + PetitStephanie + PieperS?ren + PobleteMariana + PrestipinoDaniel + RaabeLinda + RajaAmna + ReimringerJanis + ReySydney C. + RizaewJulia + RuppertEloisa + SalmonKim K. + SammetJill + SchembriRhiannon + SchlabbachLars + SchmidtFrederick W. P. + SchokkinDineke + SiegelJeff + SkiltonAmalia + SousaHil?rio de + SverredalKristin + ValleDaniel + VeraJavier + Vo?Judith + SmithDaniel Wikalier + WitteTim + WuHenry + YamStephanie + ???Jingting Ye + YongMaisie + YudithaTessa + ZariquieyRoberto + ForkelRobert + EvansNicholas + LevinsonStephen C. + HaspelmathMartin + GreenhillSimon J. + AtkinsonQuentin D. + GrayRussell D. + + Grambank v1.0 + Zenodo + 202303 + https://doi.org/10.5281/zenodo.7740140 + 10.5281/zenodo.7740140 + + + + + + HammarströmHarald + ForkelRobert + HaspelmathMartin + BankSebastian + + Glottolog/glottolog: Glottolog database 5.0 + Zenodo + 2024 + https://doi.org/10.5281/zenodo.10804357 + 10.5281/zenodo.10804357 + + + + + + KratzerGilles + FurrerReinhard + + Varrank: Heuristics tools based on mutual information for variable ranking + 2022 + https://doi.org/10.32614/cran.package.varrank + 10.32614/cran.package.varrank + + + + +