A Metadata Profile for Numerical Modeling Systems

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Scientific Models: A User-oriented Approach to the Integration of Scientific Data and Digital Libraries

Many scientific communities are struggling with the challenge of how to manage the terabytes of data they are producing, often on a daily basis. Scientific models are the primary method for representing and encapsulating expert knowledge in many disciplines. Scientific models could also provide a mechanism: for publishing and sharing scientific results; for teaching complex scientific concepts; and for the selective archival, curation and preservation of scientific data. As such, they also provide a bridge for collaboration between Digital Libraries and eScience. In this paper I describe research being undertaken within the FUSION project at the University of Queensland to enable scientists to construct, publish and manage scientific model packages that encapsulate and relate the raw data to its associated contextual and provenance metadata, processing steps, derived information and publications. This work involves extending tools and services that have come out of the Digital Libraries domain to support e-Science requirements

Scientific Publication Packages: A Selective Approach to the Communication and Archival of Scientific Output

The use of digital technologies within research has led to a proliferation of data, many new forms of research output and new modes of presentation and analysis. Many scientific communities are struggling with the challenge of how to manage the terabytes of data and new forms of output, they are producing. They are also under increasing pressure from funding organizations to publish their raw data, in addition to their traditional publications, in open archives. In this paper I describe an approach that involves the selective encapsulation of raw data, derived products, algorithms, software and textual publications within "scientific publication packages". Such packages provide an ideal method for: encapsulating expert knowledge; for publishing and sharing scientific process and results; for teaching complex scientific concepts; and for the selective archival, curation and preservation of scientific data and output. They also provide a bridge between technological advances in the Digital Libraries and eScience domains. In particular, I describe the RDF-based architecture that we are adopting to enable scientists to construct, publish and manage "scientific publication packages" - compound digital objects that encapsulate and relate the raw data to its derived products, publications and the associated contextual, provenance and administrative metadata

Design of a Metadata Framework for the Environmental Models with an Example Hydrologic Application in HydroShare

Environmental modelers rely on a variety of computational models to make predictions, test hypotheses, and address specific problems related to environmental science and natural resource management. Scientists and engineers must devote significant effort to preparing these computational models. While significant attention has been devoted to sharing and reusing environmental data, less attention has been devoted to sharing and reusing environmental models. A first step toward increasing environmental model sharing and reuse is to define a general metadata framework for models that is flexible and, therefore, applicable across the wide variety of models used by environmental modelers. This paper proposes a general approach for representing environmental model metadata that extends the Dublin Core metadata framework. The framework is implemented within the HydroShare system and applied for a hydrologic model sharing use case. This example application demonstrates how the metadata framework implemented within HydroShare can assist in model sharing, publication, reuse, and reproducibility

Scientific Publication Packages – A Selective Approach to the Communication and Archival of Scientific Output

The use of digital technologies within research has led to a proliferation of data, many new forms of research output and new modes of presentation and analysis. Many scientific communities are struggling with the challenge of how to manage the terabytes of data and new forms of output, they are producing. They are also under increasing pressure from funding organizations to publish their raw data, in addition to their traditional publications, in open archives. In this paper I describe an approach that involves the selective encapsulation of raw data, derived products, algorithms, software and textual publications within “scientific publication packages”. Such packages provide an ideal method for: encapsulating expert knowledge; for publishing and sharing scientific process and results; for teaching complex scientific concepts; and for the selective archival, curation and preservation of scientific data and output. They also provide a bridge between technological advances in the Digital Libraries and eScience domains. In particular, I describe the RDF-based architecture that we are adopting to enable scientists to construct, publish and manage “scientific publication packages” - compound digital objects that encapsulate and relate the raw data to its derived products, publications and the associated contextual, provenance and administrative metadata

A Proposal on Using Reuse Readiness Levels to Measure Software Reusability

The use of scientific data is becoming increasingly dependent on the software that fosters such use. As the ability to reuse software contributes to capabilities for reusing software-dependent data, instruments for measuring software reusability contribute to the reuse of software and related data. The development and current state of a proposed set of Reuse Readiness Levels (RRLs) are summarized, and potential uses of the software reusability measures are described, along with proposed use cases to support sponsorship of software projects, software production, software adoption, and data stewardship during the systems development lifecycle and the data lifecycle

Parametric computational simulations of unipore cellular structure subjected to compressive loading

Mestrado em Engenharia MecânicaThe thesis study focuses on behaviour of a newly developed cellular UniPore structure with unidirectional pores under transversal and longitudinal loading. The computational model of the cellular structure was based on reconstructed irregular geometry of the manufactured specimens and analysed using ABAQUS. The mechanical properties have been studied using parametric computational simulations considering several material and geometrical parameters. Numerical tests provide data of compressive behaviour of UniPore structures and mechanical properties, such as elastic modulus or yield strength