Global research alliance modelling platform (GRAMP): an open web platform for modelling greenhouse gas emissions from agro-ecosystems

Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.

Looking for the Holy Grail of Software Development

The history of Software Engineering has been marked by many famous project failures documented in papers, articles and books. This pattern of lack of success has prompted the creation of dozens of software analysis, requirements definition, and design methods, programming languages, software development environments and software development processes all promoted as solving ?the software problem.? What we hear less about are software projects that were successful. This article reports on the findings of an extensive analysis of successful software projects that have been reported in the literature. It discusses the different interpretations of success and extracts the characteristics that successful projects have in common. These characteristics provide Software Project Managers with an agenda of topics to be addressed that will help ensure, not guarantee, that their software project will be successful.