Although similar integrative tools exist (Supplementary Note 2), no other open platform shares all KBase’s features, which include the following:(i) comprehensive support for data provenance and analysis reproducibility;(ii) a flexible system for sharing data and workflows;(iii) an integrated database of genomes and biochemistry;(iv) a point-and-click interface that enables users to build, store, run, and share complex scientific analyses of fully integrated data;(v) built-in support for the use of custom code interleaved with point-and-click apps; and (vi) a software development kit that enables external developers to add applications to KBase (Supplementary Table 1). KBase has a suite of scientific applications that enables users to build and share sophisticated workflows. For example, a user can predict species interactions from metagenomic data by assembling raw reads, binning assembled contigs by species, annotating genomes, aligning RNA-seq reads, and reconstructing and analyzing individual and community metabolic models. KBase supports numerous branch points, alternative pipelines, alternative entry points, and internal curation loops that facilitate a wide range of scientific analyses, some of which are not available elsewhere (eg, merging individual metabolic models into community models and using these to predict interspecies interactions). Although KBase was developed to support analysis of microbes, plants, and their communities, it is potentially applicable to any area of science. There is, however, a policy on use restriction for projects that require HIPAA compliance. KBase’s primary user interface, the Narrative Interface, provides a user experience distinct from other analysis platforms available today, although it shares some common features with a few other systems (Supplementary Note 2). From this interface, which is built on the Jupyter10, 11 platform, users can upload their private data, search and retrieve extensive public reference data, access data shared by others, share their data with others, select and run applications on their data, view and analyze the results from those applications, and record their thoughts and interpretations along with the analysis steps. These activities take place within a point-and-click ‘notebook’environment (Fig. 1). When a user begins a new computational experiment in KBase, they create a new ‘notebook’(referred to as a Narrative in KBase) to hold this experiment. Every action performed by a user appears as a ‘cell’in the Narrative. App cells show the chosen input parameters for the application and the results of the analysis. Markdown cells allow users to add formatted text and figures to a Narrative to describe the thought process behind the scientific workflow being crafted. A finished Narrative is a precise record of everything the authors did to complete their analysis. Although Narratives are private by default, users may choose to make their Narratives public, or share them with other individual users. This recording of a user’s KBase activities within a sharable Narrative is a central pillar of KBase’s support for reproducible, transparent research (Supplementary Note 1). Once a Narrative has been shared or made public, other users can copy the Narrative and rerun it on their own data, or modify it to suit their scientific needs. Thus, public Narratives serve as resources for the user community by capturing valuable data sets, associated computational analyses, and scientific context describing the rationale behind a scientific study in a form that is immediately reproducible and reusable. A growing number of public Narratives are available in KBase, some of which are showcased in the Narrative Library …