This dataset provides the Global Naturalized Alien Flora (GloNAF) database, version 1.2. GloNAF represents a data compendium on the occurrence and identity of naturalized alien vascular plant taxa across geographic regions (e.g. countries, states, provinces, districts, islands) around the globe. The dataset includes 13,939 taxa and covers 1,029 regions (including 381 islands). The dataset is based on 210 data sources. For each taxon‐by‐region combination, we provide information on whether the taxon is considered to be naturalized in the specific region (i.e. has established self‐sustaining populations in the wild). Non‐native taxa are marked as “alien”, when it is not clear whether they are naturalized. To facilitate alignment with other plant databases, we provide for each taxon the name as given in the original data source and the standardized taxon and family names used by The Plant List Version 1.1 (http://www.theplantlist.org/). We provide an ESRI shapefile including polygons for each region and information on whether it is an island or a mainland region, the country and the Taxonomic Databases Working Group (TDWG) regions it is part of (TDWG levels 1–4). We also provide several variables that can be used to filter the data according to quality and completeness of alien taxon lists, which vary among the combinations of regions and data sources. A previous version of the GloNAF dataset (version 1.1) has already been used in several studies on, for example, historical spatial flows of taxa between continents and geographical patterns and determinants of naturalization across different taxonomic groups. We intend the updated and expanded GloNAF version presented here to be a global resource useful for studying plant invasions and changes in biodiversity from regional to global scales. We release these data into the public domain under a Creative Commons Zero license waiver (https://creativecommons.org/share-your-work/public-domain/cc0/). When you use the data in your publication, we request that you cite this data paper. If GloNAF is a major part of the data analyzed in your study, you should consider inviting the GloNAF core team (see Metadata S1: Originators in the Overall project description) as collaborators. If you plan to use the GloNAF dataset, we encourage you to contact the GloNAF core team to check whether there have been recent updates of the dataset, and whether similar analyses are already ongoing.

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is a region of high plant diversity with an estimated 50,000 flowering plant species. Estimates of plant diversity in the region continue to grow as large numbers of new species are described even though there have been suggestions that there are few new species to be Gard. Bull. Singapore 71 (2) 2019 268 found in some parts of Southeast Asia. It is likely that most estimates of species numbers in the countries of Southeast Asia are too low due to the lack of taxonomic work on groups which have many locally endemic species. Differing collecting densities across the region can profoundly affect our understanding of plant diversity and lead to large underestimates of species diversity in poorly collected countries and regions. Progress on each of the major Flora

Four new species of Syzygium (Myrtaceae) are described for Papua New Guinea: Syzygium cravenii, S. kuiense, S. lababiense, and S. pterotum. Syzygium platycarpum (Diels) Merr. & L.M.Perry is described and discussed because this species is inadequately known, with last known collection of this species from Papua New Guinea in 1919 and from Indonesian Papua in 1926.

Beaman, Reed S. (Natural History Museum and Biodiversity Research Center, University of Kansas, 1345 Jayhawk Boulevard, Lawrence, KS 66045, USA) and Conn, Barry J. (Royal Botanic Gardens Sydney, Mrs Macquaries Road, Sydney, NSW 2000 Australia) 2003. Geoparsing and georeferencing of Malesian collection locality data. Telopea 10(1) 43-52. Some form of geographic reference is almost always present on specimen labels, an essential source of information for mapping species distributions and performing biogeographic analyses. The prospect of databasing large herbarium collections is now reality, but the task of manually georeferencing each specimen would be enormous. The fields of biological informatics and geomatics (biogeomatics) provide tools that streamline and automate acquisition, sharing, analysis, and visualisation of biogeographic data. Digitisation of specimens, particularly type specimens is now commonplace, but specimen imaging and optical character recognition (OCR) may also facilitate the data entry process. Natural language processing of digital data significantly reduces the time required to database and georeference a specimen. A prototype for a geoparsing and georeferencing web service has been developed that utilises a digital gazetteer of over 330 000 Malesian place names. This service is demonstrated using Urticaceae collections from Malesia and comparisons are made between automated and manual georeferencing methods.