Background: Long sequencing reads are information-rich: aiding de novo assembly and reference mapping, and consequently have great potential for the study of microbial communities. However, the best approaches for analysis of long-read metagenomic data are unknown. Additionally, rigorous evaluation of bioinformatics tools is hindered by a lack of long-read data from validated samples with known composition.Methods: We sequenced two commercially-available mock communities containing ten microbial species (ZymoBIOMICS Microbial Community Standards) with Oxford Nanopore GridION and PromethION. Both communities and the ten individual species isolates were also sequenced with Illumina technology. Data: We generated 14 and 16 Gbp from GridION \u001eowcells and 150 and 153 Gbp from PromethION \u001eowcells for theevenly-distributed and log-distributed communities respectively. Read length N50 was 5.3 Kbp and 5.2 Kbp for the evenand log community, respectively. Basecalls and corresponding signal data are made available (4.2 TB in total).Results: Alignment to Illumina-sequenced isolates demonstrated the expected microbial species at anticipated abundances, with the limit of detection for the lowest abundance species below 50 cells (GridION). De novo assembly of metagenomes recovered long contiguous sequences without the need for pre-processing techniques such as binning.Conclusions: We present ultra-deep, long-read nanopore datasets from a well-de\u001fned mock community. These datasetswill be useful for those developing bioinformatics methods for long-read metagenomics and for the validation andcomparison of current laboratory and software pipelines.