{"refrec":{"BRefID":405941,"RR":"<b>Oggioni, A.; Silver, M.; Tagliolato, P.; Karnieli, A.</b> (2025). ReLTER: An R interface for environmental observation in long term ecological research. <i>Ecological Informatics 85</i>: 102915. <a href=\"https://dx.doi.org/10.1016/j.ecoinf.2024.102915\" target=\"_blank\">https://dx.doi.org/10.1016/j.ecoinf.2024.102915</a>","BEntID":403736,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Ecological Informatics 85</i>: 102915. <a href=\"https://dx.doi.org/10.1016/j.ecoinf.2024.102915\" target=\"_blank\">https://dx.doi.org/10.1016/j.ecoinf.2024.102915</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Oggioni, A.; Silver, M.; Tagliolato, P.; Karnieli, A.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Oggioni, A. <i>et al.</i>","Englishabstract":"Ecological datasets are inherently complex, heterogeneous, and often span different time series. The links between spatial and temporal data and ecological/environmental science are framed in the discipline of ecoinformatics. The rapid growth of ecoinformatics has led to a demand for software collections specifically designed for environmental data analysis. This article introduces a new R package, ReLTER, simplifying user interaction with web data and the Dynamic Ecological Information Management System-Site and Dataset Registry (DEIMS-SDR). This package was motivated by users within the eLTER community and the emerging eLTER Research Infrastructure Management System (eLTER-RI), as well as other stakeholders to facilitate interaction with data and tools provided by eLTER-RI. Furthermore, DEIMS-SDR is currently used as a site catalogue by European environmental research projects, and has the potential to develop as the a reference for the EU ecological site registry.The ReLTER package, written in the R language, is based on several auxiliary packages that enrich the data collected within the Long-Term Ecological Research (eLTER) network with data from other repositories. More than forty functions have been implemented that allow the retrieval of species occurrence data from third-party online networks, such as GBIF, iNaturalist, and OBIS, as well as earth observation images from various internet archives, and to harmonize the downloaded data (in terms of structure, semantics, taxonomy, etc.) for combining and linking them in subsequent analyses. 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