rOpenSci HQ

Software 📩

CRAN: GitHub:

New Packages

  • A new package parzer (v0.1.4) is on CRAN - parse messy geographic coordinates. Checkout the docs to get started.

New Versions

  • A new version (v0.1.13) of spatsoc is on CRAN - detecting spatial and temporal groups in GPS relocations. See the release notes for changes. Checkout the docs to get started.
  • A new version (v0.2.9) of ropenaq is on CRAN - Air quality data from the open data platform OpenAQ. See the release notes for changes. Checkout the docs to get started.
  • A new version (v7.12.0) of drake is on CRAN - a pipeline toolkit for reproducible computation at scale. See the release notes for changes. Checkout the docs to get started.
  • A new version (v1.0.2) of plater is on CRAN - read, tidy, and display data from microtiter plates. See the release notes for changes. Checkout the docs to get started.
  • A new version (v0.6.2) of webmockr is on CRAN - stubbing and setting expectations on HTTP requests. See the release notes for changes. Checkout the HTTP testing book to get started.
  • A new version (v0.0.7) of plotdap is on CRAN - easily visualize data from ERDDAP servers via the rerddap package. See the release notes for changes. Checkout the vignette to get started.
  • A new version (v0.9.93) of taxize is on CRAN - taxonomic toolbelt for R. See the release notes for changes. Checkout the taxize book to get started.
  • A new version (v1.0.0) of rcrossref is on CRAN - R client for the Crossref API. See the release notes for changes. Checkout the docs to get started.
  • A new version (v0.2.0) of rbraries is on CRAN - interface to the Libraries.io API. See the release notes for changes. Checkout the docs to get started.
  • A new version (v1.3.1) of UCSCXenaTools is on CRAN - download and explore datasets from UCSC Xena data hubs. See the release notes for changes. Checkout the docs to get started.



Software Review ✔

In the interest of reducing load on reviewers and editors as we manage the COVID-19 crisis, rOpenSci is temporarily pausing new submissions for software peer review. Please check back at our software review repository after 17 April for updates. In this period new submissions will not be handled, nor new reviewers assigned. Reviews and responses to reviews will be handled on a ‘best effort’ basis, but no follow-up reminders will be sent. Other rOpenSci community activities continue. We express our continued great appreciation for the work of our authors and reviewers.



On the blog

Tech notes

Scott Chamberlain wrote a post on the new parzer package: parzer: Parse Messy Geographic Coordinates.



Use Cases

The following 23 works use/cite rOpenSci software:



From the Forum

We have a discussion forum (using Discourse) for the rOpenSci community. It’s a really nice way to have conversations on the internet. From time to time we’ll highlight recent discussions of interest.


The R-Journal is seeking reviewers - checkout the forum thread for more.

A new use case was reported in the forum recently:



In The News

  • python: Python 101: Learning About Lists
    • A good introduction to lists in Python; they’re kind of like R lists. It’s an important data structure to know if you’re going to be learning Python
  • testing: Necessary & Sufficient
    • A good read on how to think about testing in general



Call For Maintainers

Part of the mission of rOpenSci is making sustainable software that users can rely on. Some software maintainers need to give up maintenance due to a variety of circumstances. When that happens we try to find new maintainers. Checkout our Contributing Guide for why and how to contribute to rOpenSci.

We’ve had eight recent examples of maintainer transitions within rOpenSci:

We don’t have any packages looking for new maintainers - if you are a maintainer and want to hand over that role to someone else get in touch with us.



Get involved with rOpenSci

We maintain a Contributing Guide that can help direct you to the right place, whether you want to make code contributions, non-code contributions, or other things like sharing use cases.





Keep up with rOpenSci


Footnotes

  1. Hsu, C. W. (2019). Disparities in public charging infrastructure deployment and inequitable electric vehicle ownership cost based on income and race (Doctoral dissertation, Humboldt State University). http://bit.ly/2MQDAAF ↩

  2. Fatikhunnada, A., Liyantono, Solahudin, M., Buono, A., Kato, T., & Seminar, K. B. (2020). Assessment of pre-treatment and classification methods for Java paddy field cropping pattern detection on MODIS images. Remote Sensing Applications: Society and Environment, 17, 100281. https://doi.org/10.1016/j.rsase.2019.100281 ↩

  3. Hansen, O. L. P., Svenning, J., Olsen, K., Dupont, S., Garner, B. H., Iosifidis, A., 
 HĂžye, T. T. (2019). Species‐level image classification with convolutional neural network enables insect identification from habitus images. Ecology and Evolution, 10(2), 737–747. https://doi.org/10.1002/ece3.5921 ↩

  4. Kovalenko, Y. (2019). Stop and smell the grapes : altering cultivar-typical aromas in GewĂŒrztraminer (Vitis vinifera L.) berries via regulated deficit irrigation and crop load management (T). University of British Columbia. https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0387322 ↩

  5. Mienna, I. M., Speed, J. D. M., Bendiksby, M., Thornhill, A. H., Mishler, B. D., & Martin, M. D. (2019). Differential patterns of floristic phylogenetic diversity across a post‐glacial landscape. Journal of Biogeography. https://doi.org/10.1111/jbi.13789 ↩

  6. Asevedo, L., D’Apolito, C., Misumi, S. Y., Barros, M. A. de, Barth, O. M., & Avilla, L. dos S. (2020). Palynological analysis of dental calculus from Pleistocene proboscideans of southern Brazil: A new approach for paleodiet and paleoenvironmental reconstructions. Palaeogeography, Palaeoclimatology, Palaeoecology, 540, 109523. https://doi.org/10.1016/j.palaeo.2019.109523 ↩

  7. MilĂ , C., Curto, A., Dimitrova, A., Sreekanth, V., Kinra, S., Marshall, J. D., & Tonne, C. (2020). Identifying predictors of personal exposure to air temperature in peri-urban India. Science of The Total Environment, 707, 136114. https://doi.org/10.1016/j.scitotenv.2019.136114 ↩

  8. Nguyen, V. T., Dietrich, J., & Uniyal, B. (2020). Modeling interbasin groundwater flow in karst areas: Model development, application, and calibration strategy. Environmental Modelling & Software, 124, 104606. https://doi.org/10.1016/j.envsoft.2019.104606 ↩

  9. Torregroza-Espinosa, A. C., Restrepo, J. C., Correa-Metrio, A., Hoyos, N., Escobar, J., Pierini, J., & MartĂ­nez, J.-M. (2020). Fluvial and oceanographic influences on suspended sediment dispersal in the Magdalena River Estuary. Journal of Marine Systems, 204, 103282. https://doi.org/10.1016/j.jmarsys.2019.103282 ↩

  10. Akpoti, K., Kabo-bah, A. T., Dossou-Yovo, E. R., Groen, T. A., & Zwart, S. J. (2020). Mapping suitability for rice production in inland valley landscapes in Benin and Togo using environmental niche modeling. Science of The Total Environment, 709, 136165. https://doi.org/10.1016/j.scitotenv.2019.136165 ↩

  11. Mingione, M., Cristofaro, M., & Mondi, D. (2020). If I give you my emotion, what do I get? Conceptualizing and measuring the co-created emotional value of the brand. Journal of Business Research, 109, 310–320. https://doi.org/10.1016/j.jbusres.2019.11.071 ↩

  12. D’Amen, M., & Azzurro, E. (2019). Integrating univariate niche dynamics in species distribution models: A step forward for marine research on biological invasions. Journal of Biogeography, 47(3), 686–697. https://doi.org/10.1111/jbi.13761 ↩

  13. Meng, S., Zhan, S., Dou, W., & Ge, W. (2019). The interactome and proteomic responses of ALKBH7 in cell lines by in-depth proteomics analysis. Proteome Science, 17(1). https://doi.org/10.1186/s12953-019-0156-x ↩

  14. Czernecki, B., GƂogowski, A., & Nowosad, J. (2020). Climate: An R Package to Access Free In-Situ Meteorological and Hydrological Datasets For Environmental Assessment. Sustainability, 12(1), 394. https://doi.org/10.3390/su12010394 ↩

  15. Shi, L., Tian, H., Wang, P., Li, L., Zhang, Z., Zhang, J., & Zhao, Y. (2020). Spaceflight and simulated microgravity suppresses macrophage development via altered RAS/ERK/NFÎșB and metabolic pathways. Cellular & Molecular Immunology. https://doi.org/10.1038/s41423-019-0346-6 ↩

  16. Lestina, F. Trends in US Foreign Policy Prioritizations, 2000–2019. Proceedings of the 53rd Hawaii International Conference on System Sciences. https://scholarspace.manoa.hawaii.edu/bitstream/10125/63832/0074.pdf ↩

  17. Quintero, E., Pizo, M. A., & Jordano, P. (2020). Fruit resource provisioning for avian frugivores: The overlooked side of effectiveness in seed dispersal mutualisms. Journal of Ecology. https://doi.org/10.1111/1365-2745.13352 ↩

  18. Blowes, S. A., Chase, J. M., Di Franco, A., Frid, O., Gotelli, N. J., Guidetti, P., 
 Belmaker, J. (2020). Mediterranean marine protected areas have higher biodiversity via increased evenness, not abundance. Journal of Applied Ecology, 57(3), 578–589. https://doi.org/10.1111/1365-2664.13549 ↩

  19. Wunderlich, F., & Memmert, D. (2020). Innovative Approaches in Sports Science—Lexicon-Based Sentiment Analysis as a Tool to Analyze Sports-Related Twitter Communication. Applied Sciences, 10(2), 431. https://doi.org/10.3390/app10020431 ↩

  20. Nguyen, H. N., Hung, C.-M., Yang, M.-Y., & Lin, S.-M. (2020). Sympatric competitors have driven the evolution of temporal activity patterns in Cnemaspis geckos in Southeast Asia. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-019-56549-x ↩

  21. Carta, A., Bedini, G., & Peruzzi, L. (2020). A deep dive into the ancestral chromosome number of flowering plants. bioRxiv preprint. https://doi.org/10.1101/2020.01.05.893859 ↩

  22. Alves, D. M. C. C., Eduardo, A. A., da Silva Oliveira, E. V., Villalobos, F., Dobrovolski, R., Pereira, T. C., 
 Gouveia, S. F. (2020). Unveiling geographical gradients of species richness from scant occurrence data. Global Ecology and Biogeography, 29(4), 748–759. https://doi.org/10.1111/geb.13055 ↩

  23. Jaric, I., & Djeric, M. (2019). Curriculum and labor market: Comparative analysis of the curricular outcomes of the study program in sociology at the Faculty of Philosophy, University of Belgrade and the required competences in the labor market. Sociologija, 61(Suppl. 1), 718–741. https://doi.org/10.2298/soc19s1718j ↩