TR32DB — Management and visualization of heterogeneous scientific data

Particularly in interdisciplinary long-term research projects, management of heterogeneous scientific data is an important task that includes storage, accurate description with metadata, exchange, visualization and provision. Therefore, this paper presents the implementation of a centralized system that focuses on management and visualization of heterogeneous scientific project data for the Transregional Collaborative Research Center 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems’ funded by the German Research Foundation. Its design is basically a combination of file management, database, and web-interface including web mapping functions.

[1]  Bruce Alberts,et al.  Making Data Maximally Available , 2011, Science.

[2]  W. Amelung,et al.  Rapid assessment of black carbon in soil organic matter using mid-infrared spectroscopy , 2008 .

[3]  David J. DeWitt,et al.  Scientific data management in the coming decade , 2005, SGMD.

[4]  K. Bennett,et al.  Developing Web Interfaces for Scientific Data Archives , 2009 .

[5]  Alexandre Eremenko,et al.  Project Summary , 2018, Clifton Quarry, Worcestershire.

[6]  Clemens Simmer,et al.  A downscaling scheme for atmospheric variables to drive soil–vegetation–atmosphere transfer models , 2010 .

[7]  Christine L. Borgman,et al.  Research Data: Who Will Share What, with Whom, When, and Why? , 2010 .

[8]  Georg Bareth,et al.  GIS- and RS-based spatial decision support: structure of a spatial environmental information system (SEIS) , 2009, Int. J. Digit. Earth.

[9]  Jan Brase Using Digital Library Techniques - Registration of Scientific Primary Data , 2004, ECDL.

[10]  S. Crewell,et al.  The influence of leaf photosynthetic efficiency and stomatal closure on canopy carbon uptake and evapotranspiration – a model study in wheat and sugar beet , 2010 .

[11]  Dirk Hoffmeister,et al.  High-resolution Crop Surface Models (CSM) and Crop Volume Models (CVM) on field level by terrestrial laser scanning , 2009, International Symposium on Digital Earth.

[12]  Karl Schneider,et al.  Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions , 2009 .

[13]  Bryn Nelson Data sharing: Empty archives , 2009, Nature.

[14]  Karl Schneider,et al.  Temporal Downscaling of Soil Carbon Dioxide Efflux Measurements Based on Time‐Stable Spatial Patterns , 2011 .

[15]  Anne E. Trefethen,et al.  The Data Deluge: An e-Science Perspective , 2003 .

[16]  Georg Bareth,et al.  GIS- and RS-based land use and land cover analysis: case study Rur-Watershed, Germany , 2009, Geoinformatics.