  Virtual Research Environments (VREs) provide user-centric support in the
lifecycle of research activities, e.g., discovering and accessing research
assets, or composing and executing application workflows. A typical VRE is
often implemented as an integrated environment, which includes a catalog of
research assets, a workflow management system, a data management framework, and
tools for enabling collaboration among users. Notebook environments, such as
Jupyter, allow researchers to rapidly prototype scientific code and share their
experiments as online accessible notebooks. Jupyter can support several popular
languages that are used by data scientists, such as Python, R, and Julia.
However, such notebook environments do not have seamless support for running
heavy computations on remote infrastructure or finding and accessing software
code inside notebooks. This paper investigates the gap between a notebook
environment and a VRE and proposes an embedded VRE solution for the Jupyter
environment called Notebook-as-a-VRE (NaaVRE). The NaaVRE solution provides
functional components via a component marketplace and allows users to create a
customized VRE on top of the Jupyter environment. From the VRE, a user can
search research assets (data, software, and algorithms), compose workflows,
manage the lifecycle of an experiment, and share the results among users in the
community. We demonstrate how such a solution can enhance a legacy workflow
that uses Light Detection and Ranging (LiDAR) data from country-wide airborne
laser scanning surveys for deriving geospatial data products of ecosystem
structure at high resolution over broad spatial extents. This enables users to
scale out the processing of multi-terabyte LiDAR point clouds for ecological
applications to more data sources in a distributed cloud environment.
