Modeling scientific experiments with an object data model

Abstract Background The advancement of science and technologies play an immense role in the way scientific experiments are being conducted. Understanding how experiments are performed and how results are derived has become significantly more complex with the recent explosive growth of heterogeneous research data and methods. Therefore, it is important that the provenance of results is tracked, described, and managed throughout the research lifecycle starting from the beginning of an experiment to its end to ensure reproducibility of results described in publications. However, there is a lack of interoperable representation of end-to-end provenance of scientific experiments that interlinks data, processing steps, and results from an experiment’s computational and non-computational processes. Results We present the “REPRODUCE-ME” data model and ontology to describe the end-to-end provenance of scientific experiments by extending existing standards in the semantic web. The ontology brings together different aspects of the provenance of scientific studies by interlinking non-computational data and steps with computational data and steps to achieve understandability and reproducibility. We explain the important classes and properties of the ontology and how they are mapped to existing ontologies like PROV-O and P-Plan. The ontology is evaluated by answering competency questions over the knowledge base of scientific experiments consisting of computational and non-computational data and steps. Conclusion We have designed and developed an interoperable way to represent the complete path of a scientific experiment consisting of computational and non-computational steps. We have applied and evaluated our approach to a set of scientific experiments in different subject domains like computational science, biological imaging, and microscopy.

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Inquiry Learning

Zeitschrift für Pädagogische Psychologie ◽

10.1024/1010-0652.23.2.117 ◽

2009 ◽

Vol 23 (2) ◽

pp. 117-127 ◽

Cited By ~ 16

Author(s):

Astrid Wichmann ◽

Detlev Leutner

Keyword(s):

Scientific Reasoning ◽

Inquiry Learning ◽

Instructional Support ◽

Test Results ◽

Knowledge Test ◽

Simulation Based ◽

Scientific Experiments ◽

Specific Support ◽

Science Classes

Seventy-nine students from three science classes conducted simulation-based scientific experiments. They received one of three kinds of instructional support in order to encourage scientific reasoning during inquiry learning: (1) basic inquiry support, (2) advanced inquiry support including explanation prompts, or (3) advanced inquiry support including explanation prompts and regulation prompts. Knowledge test as well as application test results show that students with regulation prompts significantly outperformed students with explanation prompts (knowledge: d = 0.65; application: d = 0.80) and students with basic inquiry support only (knowledge: d = 0.57; application: d = 0.83). The results are in line with a theoretical focus on inquiry learning according to which students need specific support with respect to the regulation of scientific reasoning when developing explanations during experimentation activities.

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Decision Making in Team Sports: Data, model and applied perspective

PsycEXTRA Dataset ◽

10.1037/e509992008-001 ◽

2008 ◽

Author(s):

Pedro J. M. Passos ◽

Duarte Araujo ◽

Keith Davids ◽

Ana Diniz ◽

Luis Gouveia ◽

...

Keyword(s):

Decision Making ◽

Data Model ◽

Team Sports ◽

Sports Data

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On Scientific Experiments in Balloons

Scientific American ◽

10.1038/scientificamerican07151865-32a ◽

1865 ◽

Vol 13 (3) ◽

pp. 32-35

Author(s):

James Glaisher

Keyword(s):

Scientific Experiments

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A Qualified Assertion Database for the History of Places

International Journal of Humanities and Arts Computing ◽

10.3366/ijhac.2019.0233 ◽

2019 ◽

Vol 13 (1-2) ◽

pp. 95-115

Author(s):

Brandon Plewe

Keyword(s):

Data Model ◽

Temporal Change ◽

Religious Congregations ◽

Historical Gis ◽

The Past ◽

Model Based ◽

Complex Information ◽

Invaluable Tool ◽

History Of ◽

The Rich

Historical place databases can be an invaluable tool for capturing the rich meaning of past places. However, this richness presents obstacles to success: the daunting need to simultaneously represent complex information such as temporal change, uncertainty, relationships, and thorough sourcing has been an obstacle to historical GIS in the past. The Qualified Assertion Model developed in this paper can represent a variety of historical complexities using a single, simple, flexible data model based on a) documenting assertions of the past world rather than claiming to know the exact truth, and b) qualifying the scope, provenance, quality, and syntactics of those assertions. This model was successfully implemented in a production-strength historical gazetteer of religious congregations, demonstrating its effectiveness and some challenges.

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3D Subsurface Soil Deformation Data Model

10.15405/epsbs.2020.03.03.7 ◽

2020 ◽

Author(s):

Siti Nurbaidzuri Reli

Keyword(s):

Data Model ◽

Soil Deformation ◽

Subsurface Soil

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Sound as a transverse wave

JOURNAL OF ADVANCES IN PHYSICS ◽

10.24297/jap.v13i1.5670 ◽

2017 ◽

Vol 13 (1) ◽

pp. 4522-4534

Author(s):

Armando TomÃ¡s Canero

Keyword(s):

Quantum Mechanics ◽

Gravitational Waves ◽

Longitudinal Wave ◽

Transverse Wave ◽

Sound Propagation ◽

Correspondence Principle ◽

Classical Mechanics ◽

Wave Model ◽

Scientific Experiments

This paper presents sound propagation based on a transverse wave model which does not collide with the interpretation of physical events based on the longitudinal wave model, but responds to the correspondence principle and allows interpreting a significant number of scientific experiments that do not follow the longitudinal wave model. Among the problems that are solved are: the interpretation of the location of nodes and antinodes in a Kundt tube of classical mechanics, the traslation of phonons in the vacuum interparticle of quantum mechanics and gravitational waves in relativistic mechanics.

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