Skip to content
Home for the development of the 'sftraj' package for R.
HTML
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.github/ISSUE_TEMPLATE Update issue templates (label) Oct 1, 2019
Figures Logo updated. Sep 27, 2019
Proposal Open repository for contributions. Sep 26, 2019
CODE_OF_CONDUCT.md Create CODE_OF_CONDUCT.md Sep 26, 2019
LICENSE MIT license formatted. Sep 26, 2019
README.md README updated. Sep 27, 2019

README.md

sftraj: A central class for tracking and movement data

sftraj logo

This is the homepage for the development of sftraj, an R package offering a generic and flexible approach for a central trajectory class to support all stages of movement studies (pre-processing, post-processing and analysis). The only aim of the package will be to present this central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R.

Project plan

All of the work is going to happen openly on GitHub, in this repository. The code will be released under the MIT license for the package, a fully open license that allows for more contributions, and wide acceptation by other package developers. Last but not least, we abide by a strict code of conduct to enforce a safe and inclusive environment for the community interested in sftraj.

The time frame of this project is over 6 months, until March 2020. Following the MoSCoW method, we determined what will be delivered from this project, starting from a minimum viable product to future development.

Must have

Must have are requirements necessary for project completion, which define together our minimum viable product, i.e. a usable sftraj package:

  • Use cases described [month 1–2]
  • Data model revisited and class definitions [month 3]
  • Creators and converters from basic objects (data.frames, sf, trajectories) [month 4]
  • Installable package (GitHub) [months 4–6]
  • Accessors and summaries (print, summary) [month 5]
  • Full function documentation and unit testing [months 5–6]

Should have

Should have are important requirements, which are however not necessary for project completion:

  • Vignette [month 6]

Could have

Could have are desirable requirements developed if time allows:

  • Package on CRAN (the package will be installable from GitHub as a must have)
  • Basic plot (static) of trajectory object

Won't have

Won’t have are requirements that are identified, but not planned at this stage of the work:

  • Full-fledged package, including submission to CRAN and rOpenSci.
  • Preparation of a detailed article (targeting the R Journal) to present the technical choices and the solution offered by sftraj, in order to favor adoption by users and package developers.
  • Broad adoption by package developers, by continuing open conversation with them, and help them develop conversion tools to major existing classes.
  • Dynamic visualization of trajectories, allowing keyboard- and mouse-controlled exploration of trajectories, step by step (based on the solution provided in rpostgisLT).

How can you help?

Although we have set out a precise work plan, the very first step will decide if the package is successful and meet the requirements for broad acceptance by the movement community. Even before we start writing a single line of code, we need to precisely understand what is expected from such a package. This is the raison d'être of the use cases mentioned above. And this is why your contribution would be much critical, whether you are a package developer, an R guru, or simply a casual R user interested in movement data.

We need your feedback!

The idea is to collect all possible use cases for a trajectory object in R. We know they are multiple, and will contribute our own use cases — however, we want sftraj to be as useful as possible, and to act as a center piece for movement in R, so we need you to tell us how you would use it. In other words, we want to understand what you expect from such a package, as a user or as a developer. For this, we ask you to fill out special issues in the GitHub tracker of the package, following the 'Use case' template.

Use cases do not need to be very complicated, but need to present a specific use in human terms, the technical requirements associated to it, and the input and output of the use case. Such use case could look like this:

[Use case] Amazing plot for trajectory

Use case:

Plot a trajectory using my special_trajplot function, which shows [something amazing].

Requirements:

  • spatial coordinates (x,y) as geographic coordinates with projection information

  • a time (t) as POSIXt object, ordered in time

  • information that identifies individuals (e.g. animal) for each location

  • data associated to each location directly accessible

Input: a sftraj object

Output: a plot with [something amazing] about the trajectory

Additional information: See my special_trajplot function here [with link].

Another example could be like this:

[Use case] Fill in missing locations in a sequence

Use case: Fill in the missing locations of a trajectory that contains spatial or temporal gaps. (for instance coming from GPS with failed fixes); In other words add in the missing values of a trajectory, i.e. timestamps with no geographic coordinates.

Requirements:

  • a time (t) as POSIXt object, ordered in time

  • information that identifies sequences of locations (optional, if several sequences), which could be different circuits of one individual, or different individuals, etc.

  • sftraj should be capable of handling/storing missing values

Input: a sftraj object

Output: a sftraj object with additional timestamps for gaps (but otherwise identical in every way to the original sftraj)

Additional information: See adehabitatLT::setNA, which does exactly that on ltraj objects.

You can’t perform that action at this time.