The sustainable interaction between humankind and planet Earth poses huge hydraulic and environmental engineering challenges.
Confronting these challenges one-project-at-atime, while seemingly attractive from a budget management perspective, results in grave inefficiencies in developing and archiving the basic elements that are invariably involved: data, models and tools. Hardly any project is by itself of sufficient scale to develop easily accessible and high-quality data archives, state-of-the-art modelling systems and well-tested analysis tools under version control.
Research, consultancy as well as major construction projects commonly spend a significant part of their budgets to set up some basic data and knowledge management infrastructure, most of which dissipates again once the project is finished.
Internally institutions generally employ intranet services and internal networks to collaborate and exchange information. However, owing to increasing complexity, large projects nowadays are regularly executed by consortia. The internal services of individual institutions do not allow for collaboration because of technical limitations or simply denial of permission for exchanges.
As a result the way data, models and tools are currently managed, while presumably aimed at protecting the knowledge capital of organisations, in fact also inhibits (individual as well as collective) progress.
Over many years Delft University of Technology and Deltares, together with many partners from the hydraulic engineering industry, developed OpenEarth (www.openearth.eu) as a clonable, free and open source alternative to the project-by-project and institution-byinstitution approaches to deal with data, models and tools (e.g, Van Koningsveld et al., 2004; Van Koningsveld et al., 2010; Baart et al., 2012; De Boer et al., 2012)).
OpenEarth transcends the scale of single projects facilitating that each project builds on the heritage of previous projects. OpenEarth at its most abstract level represents the philosophy that data, models and tools should flow as freely and openly as possible across the artificial boundaries of projects and organisations (or at least departments).
Put in practice OpenEarth exists only because of a robust user community that works according to this philosophy (a bottom-up approach).
In its most concrete and operational form, OpenEarth facilitates collaboration within its user community by providing an open ICT infrastructure, built from the best available open source components, in combination with a well-defined workflow, described in open protocols based as much as possible on widely accepted international standards.
OpenEarth as a whole (philosophy, user community, infrastructure and workflow) is the first comprehensive approach to handling data, models and tools that actually works in hydraulic engineering practice at a truly significant scale.
It is implemented effectively not only at its original founding organisations, Delft University of Technology and Deltares, but also in a number of sizeable research programmes with multiple partners (such as the €28 million 4-year research programme Building with Nature with 19 partners from one country) and from multiple countries (such as the €4.6 million 3-year European Union FP7 research programme MICORE with 15 partners from 9 countries).
It has been adopted as the main data management workflow for all research programmes around the Sand Engine Delfland and was awarded the Dutch Data Prize 2012 for technical sciences by 3TU.datacentrum, the data archiving institute of the Dutch technical universities, and DANS, the data archiving institute of the Dutch National Science Foundation (NOW) and the Royal Dutch Academy of Sciences (KNAW).
As a result OpenEarth is now carried by a rapidly growing user community that as of April 2013 comprises some 1000 users, over 280 LinkedIn group members, more than 150 active developers, creating upwards of 6500 contributions, originating from a multitude of organisations and countries.
Together they share and co-develop thousands of tools, tera-bytes of data and numerous models (source code, raw data and data products, model schematisations and pre- and post-processing tools).
Press Release, June 3, 2013