Evaluation of the OntoSoft Ontology for describing metadata for legacy hydrologic modeling software

Metadata for hydrologic models is rarely organized in machine-readable forms. This lack of formal metadata is important because it limits the ability to catalog, identify, attribute, and understand unique model software; ultimately, it hinders the ability to reproduce past computational studies. Researchers have recently proposed an ontology for scientific software metadata called OntoSoft for addressing this problem. The objective of this research is to evaluate OntoSoft for organizing the metadata associated with a data pre-processing software workflow used in association with the Variable Infiltration Capacity (VIC) hydrologic model. This is accomplished by exploring what metadata are available from online resources and how this metadata aligns with the OntoSoft Ontology. The results suggest that past efforts to document this software resulted in capturing key model metadata in unstructured files that could be formalized into a machine-readable form using the OntoSoft Ontology. The OntoSoft Ontology and Portal are evaluated for capturing and sharing metadata for hydrologic modeling software.Data pre-processing software workflow for the Variable Infiltration Capacity (VIC) hydrologic model is used as a case study.90% of required OntoSoft metadata was obtained for 13 of the 15 software resources.Metadata divided across six sources can now be organized in a constant, machine-readable form.

[1]  A. Pope.  Reproducibly estimating and evaluating supraglacial lake depth with Landsat 8 and other multispectral sensors , 2016 .

[2]  Yolanda Gil,et al.  OntoSoft: A distributed semantic registry for scientific software , 2016, 2016 IEEE 12th International Conference on e-Science (e-Science).

[3]  V. Singh,et al.  Mathematical Modeling of Watershed Hydrology , 2002 .

[4]  Geoffrey C. Fox,et al.  Examining the Challenges of Scientific Workflows , 2007, Computer.

[5]  M. Morsy,et al.  Metadata for Describing Water Models , 2014 .

[6]  Scott D. Peckham,et al.  A component-based approach to integrated modeling in the geosciences: The design of CSDMS , 2013, Comput. Geosci..

[7]  J. Fearon,et al.  Ethnicity, Insurgency, and Civil War , 2003, American Political Science Review.

[8]  Yolanda Gil,et al.  An introduction to the special issue on Geoscience Papers of the Future , 2016 .

[9]  R. H. van Waveren,et al.  Good Modelling Practice in Water Management , 2000 .

[10]  P. Bryan Heidorn,et al.  Shedding Light on the Dark Data in the Long Tail of Science , 2008, Libr. Trends.

[11]  Robinson W. Fulweiler,et al.  A workflow for reproducing mean benthic gas fluxes , 2016 .

[12]  Gail Clement,et al.  Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance , 2017 .

[13]  Alva L. Couch,et al.  HydroShare: Advancing Collaboration through Hydrologic Data and Model Sharing , 2015 .

[14]  Stine Bjerkestrand,et al.  Open science. , 2019, Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke.

[15]  Claudia-Lavinia Ignat,et al.  Enhancing rich content wikis with real‐time collaboration , 2017 .

[16]  Christopher Hutton,et al.  Most computational hydrology is not reproducible, so is it really science? , 2016, Water Resources Research.

[17]  William W. Lytton,et al.  Reproducibility in Computational Neuroscience Models and Simulations , 2016, IEEE Transactions on Biomedical Engineering.

[18]  Eric F. Wood,et al.  One-dimensional statistical dynamic representation of subgrid spatial variability of precipitation in the two-layer variable infiltration capacity model , 1996 .

[19]  Jane Greenberg,et al.  Metadata for Describing Water Models , 2014 .

[20]  Scott D. Peckham,et al.  Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS , 2013, Comput. Geosci..

[21]  Christopher J. Duffy,et al.  Open science in practice: Learning integrated modeling of coupled surface‐subsurface flow processes from scratch , 2016 .

[22]  J. B. Gregersen,et al.  OpenMI: Open modelling interface , 2007 .

[23]  Jeffery S. Horsburgh,et al.  HydroShare: Sharing Diverse Environmental Data Types and Models as Social Objects with Application to the Hydrology Domain , 2016 .

[24]  Reagan Moore,et al.  Using a data grid to automate data preparation pipelines required for regional-scale hydrologic modeling , 2016, Environ. Model. Softw..

[25]  Suzanne A. Pierce,et al.  Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance , 2016 .

[26]  Edward A. Lee,et al.  Scientific workflow management and the Kepler system , 2006, Concurr. Comput. Pract. Exp..

[27]  Carole A. Goble,et al.  The design and realisation of the myExperiment Virtual Research Environment for social sharing of workflows , 2009, Future Gener. Comput. Syst..

[28]  Carole A. Goble,et al.  Towards open science: the myExperiment approach , 2010, Concurr. Comput. Pract. Exp..

[29]  TIM M. BLACKBURN,et al.  Reproducibility and Repeatability in Ecology , 2006 .

[30]  Yolanda Gil,et al.  OntoSoft: Capturing Scientific Software Metadata , 2015, K-CAP.

[31]  Mary C. Whitton,et al.  Server‐side workflow execution using data grid technology for reproducible analyses of data‐intensive hydrologic systems , 2016 .

[32]  R. Peng.  Reproducible Research in Computational Science , 2011, Science.