moveStore: an extensible cloud-based framework for applications dealing with movement data

In recent decades, huge efforts have been put to make multiple-sources of spatial and temporal data available through data repositories, followed by explosive progress in technological developments of data providers, crowdsourcing, drones, sensor networks, etc. that can be expected to continue for the next decades. Examples are global initiatives such as the movebank data repository containing animal movement data at large spatial scales over long time periods, as well as the ICARUS satellite-based animal tracking technology (Wikelski et al., 2007). The question is that whether and to what extent analytical methods are developed/adopted to deal with such progress in data? This research aims to introduce moveStore, a platform that is designed on a cloud to support and boost the progresses in methods/workflows/applications developments, followed the progresses in data developments. Analogous to a data repository, moveStore provides a specific repository for methodological developments that have been implemented as a suit of functions and classes that may also be framed into an application. moveStore is an open-source and extensible framework (Naimi and Araújo, 2016) that intends to facilitate sharing and distributing of software applications dealing with movement data. Users can share the analytical functions, procedures, workflows either packaged as software applications (Apps) or developed as simple functions. The contributions, followed by appropriate metadata, can then be accessible by other users. The applications in moveStore are usually developed using R shiny web framework, and the platform is implemented on a cloud-based computational engine with a user interface on the web through which users can access to all the Apps registered on the platform and search for a specific App (same as in an App store). REFERENCES: Naimi, B., Araújo, M.B., 2016. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography 39, 368-375. Wikelski, M., Kays, R.W., Kasdin, N.J., Thorup, K., Smith, J.A., Swenson, G.W., 2007. Going wild: what a global small-animal tracking system could do for experimental biologists. J Exp Biol 210, 181-186.


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