Abstract: 【Purpose/significance】The upsurge of“Open Government Data”in the digital era has produced fruitful results.A compre⁃hensive and accurate visualization of the thematic structure and evolution of its research will help to further enrich and improve the re⁃search and scientifically guide the practice in China.【Method/process】Firstly.literature on "Open Government Data" from the WOS database from 2000 to 2019 was selected.and keywords co-occurrence network was extracted.Secondly.the new SLM algorithm is used to detect the thematic community.and the distribution of the research is organized.At the same time.the Social Network Analysis meth⁃od is embedded and the "conductivity" index is introduced to quantitatively evaluate the maturity and internal and external relevance of the thematic community.Finally.the Cortext platform is used to construct the time series evolution process【. Result/conclusion】For⁃eign OGD research has formed four types of themed communities:Health communities.Open Data communities.Management communi⁃ties and Security communities.At present.there are still some problems.such as the granularity of the theme spread is not fine enough.the emerging theme community needs to grow up urgently.and the evolution line is obviously discontinuous【. Innovation/limitation】A new algorithm SLM is embedded to divide the thematic community.and then the thematic relevance and evolution of OGD research abroad are fully explained combined with LDA model.But this article only selects related subject literatures in the WOS core collection
as the data source and there is room for further expansion.