v1.1
ILORA version 1.1
ILORA version 1.0 had occurrence records extracted from the Global Biodiversity Information Facility (GBIF). We know that the occurrence records in GBIF are not exhaustive and often poorly represent the actual distribution of a species in India. Therefore, to increase the resolution of occurrence data, we have extracted location information (and associated variables) from literature records (more than 3000 published articles) and herbarium sheets (currently restricted to three digital herbaria of the country).
The data, being more than 12,000 coordinate values for 362 invasive and naturalized aliens, form ILORA version 1.1. Each record is associated with 22 variable information and citable data sources. The data is arranged in a table having the Darwin Core (DwC) term names as column names.
ILORA version 1.1 supplements GBIF data by 60.39% and holds records for 64 species for which no occurrence record is available in GBIF.
Access to data
All data in ILORA are free to access.
Users can access the data in different formats through multiple channels:
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From the publications
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From the website: log-in required
The benefits of accessing data from the website:
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All data are available in .csv format - ready to use in any analysis
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You may not need data for all variables or you want to explore the data before downloading it - you can access the data through a query-directed search developed using the R Shiny framework
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Log-in makes you a member of the ILORA team, a prerequisite to access unpublished data and collaborate on the ongoing projects
Submit data
We also welcome the submission of occurrence data from the community. Users can submit occurrence-related information of the invasive and naturalized alien plant species present in India. ILORA has provisions for users to submit data online; however, for a large number of occurrences, users can send the data through email.
Check the standard for data formatting HERE
As is the case for other variables included in ILORA, the submitted data will undergo verification and thorough quality checks by the curators before integration in the database to ensure data quality. All data will be associated with source information and users will be encouraged to refer back to the primary sources so that the content providers can get full credit and acknowledgment.