The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120–168 MHz survey of the entire northern sky for which observations are now 20% complete. We present our first full-quality public data release. For this data release 424 square degrees, or 2% of the eventual coverage, in the region of the HETDEX Spring Field (right ascension 10h45m00s to 15h30m00s and declination 45°00′00″ to 57°00′00″) were mapped using a fully automated direction-dependent calibration and imaging pipeline that we developed. A total of 325 694 sources are detected with a signal of at least five times the noise, and the source density is a factor of ∼10 higher than the most sensitive existing very wide-area radio-continuum surveys. The median sensitivity is S144 MHz = 71 μJy beam−1 and the point-source completeness is 90% at an integrated flux density of 0.45 mJy. The resolution of the images is 6″ and the positional accuracy is within 0.2″. This data release consists of a catalogue containing location, flux, and shape estimates together with 58 mosaic images that cover the catalogued area. In this paper we provide an overview of the data release with a focus on the processing of the LOFAR data and the characteristics of the resulting images. In two accompanying papers we provide the radio source associations and deblending and, where possible, the optical identifications of the radio sources together with the photometric redshifts and properties of the host galaxies. These data release papers are published together with a further ∼20 articles that highlight the scientific potential of LoTSS.

The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the directiondependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, positiondependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.