We recently published a review paper on 58 R packages created to process or analyze tracking data. However, R packages are dynamic, new packages are created, old packages get updated and some even disappear or get deprecated due to lack of maintenance. For that reason, we created a CRAN Task View (CTV) on tracking packages.
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In this new post from the sftraj
series, we now
present a detailed conceptual model for movement, from the basic
location to a complete trajectory. Essentially, this is the logics
behind sftraj
.
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“There is a raccoon that looks stuck on the gate… his head is stuck in a can… Any chance you know what to do in this situation? (pic attached).”
Talk about a weird email to receive first thing in the morning, coffee in hand, as I arrived at the UF Fort Lauderdale Research and Education Center, in Davie, FL. Curious, I opened the attachment to see what appears to be a young raccoon hanging on for dear life at the top of a chain-link fence with an aluminum soup can firmly stuck around its head like a Halloween costume gone wrong.
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We now have a problem, a team, and use cases to consider for our sftraj
package. In order to be relevant, we also need to know what does already exist in R, what other projects have attempted to deal with trajectories and tracking data, and what lessons can we learn from this. In this post of the sftraj
series, we thus review the state of affairs in the R world.
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After introducing the problem and our team in the previous blog
post, we now present in this second post of the
‘sftraj’ series a brief overview of the sftraj
package as projected, and how we will work to implement it. Most
importantly, we also ask your help, and explain how you (developers
and users!) can contribute to the success of sftraj
.
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