Sharing data pipelines: Why sharing data may not be enough, and what to do about it
Author(s) / Creator(s)
Käthner, David
Abstract / Description
New research challenges and low-cost technological solutions drive the motivation to record behavior in multivariate ways using high temporal resolution. Making such data accessible and usable is more complicated than it may seem. Methods like ECG, EEG, and eye tracking can produce very large amounts of data in a short time. Further, context data to explain the observed behavior must be recorded as well. E.g., in a field study using an instrumented research vehicle, the position of the vehicle and the distance to the vehicle in front could act as context data. To make this multitude of data analyzable, data must be cleaned and fused in data pipelines. Cleaning happens in multiple stages, and requires decisions which have direct effects on patterns in the data. Time series data are often up- or down sampled, potentially altering characteristics of signals of interest. Sharing the data pipeline alongside an uncleaned version of the data therefore should be the default when publishing research results. Data science has developed a number of solutions to store and document data and data pipelines, whose benefits and costs will be discussed in this talk. These approaches can be structured in three interdependent dimensions: data storage, data processing, and competencies required by developers and users of data pipelines. Data from empirical studies can be very challenging to store, process, and document. Solutions to these issues do exist, but they require a training which is yet to be implemented in the typical Psychology curriculum.
Keyword(s)
data pipeline data sciene data processing time series data multi variate data data fusionPersistent Identifier
Date of first publication
2020-12-07
Is part of
CSPD 2020, online
Publisher
ZPID (Leibniz Institute for Psychology)
Citation
Käthner, D. (2020). Sharing data pipelines: Why sharing data may not be enough, and what to do about it. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.4479
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Author(s) / Creator(s)Käthner, David
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PsychArchives acquisition timestamp2021-01-18T09:33:03Z
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Made available on2021-01-18T09:33:03Z
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Date of first publication2020-12-07
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Abstract / DescriptionNew research challenges and low-cost technological solutions drive the motivation to record behavior in multivariate ways using high temporal resolution. Making such data accessible and usable is more complicated than it may seem. Methods like ECG, EEG, and eye tracking can produce very large amounts of data in a short time. Further, context data to explain the observed behavior must be recorded as well. E.g., in a field study using an instrumented research vehicle, the position of the vehicle and the distance to the vehicle in front could act as context data. To make this multitude of data analyzable, data must be cleaned and fused in data pipelines. Cleaning happens in multiple stages, and requires decisions which have direct effects on patterns in the data. Time series data are often up- or down sampled, potentially altering characteristics of signals of interest. Sharing the data pipeline alongside an uncleaned version of the data therefore should be the default when publishing research results. Data science has developed a number of solutions to store and document data and data pipelines, whose benefits and costs will be discussed in this talk. These approaches can be structured in three interdependent dimensions: data storage, data processing, and competencies required by developers and users of data pipelines. Data from empirical studies can be very challenging to store, process, and document. Solutions to these issues do exist, but they require a training which is yet to be implemented in the typical Psychology curriculum.
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Review statusunknown
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CitationKäthner, D. (2020). Sharing data pipelines: Why sharing data may not be enough, and what to do about it. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.4479en
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/4058
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.4479
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Language of contenteng
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PublisherZPID (Leibniz Institute for Psychology)
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Is part ofCSPD 2020, online
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Is related tohttps://www.conference-service.com/CSPD2020/xpage.html?xpage=244&lang=en
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Keyword(s)data pipelineen_US
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Keyword(s)data scieneen_US
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Keyword(s)data processingen_US
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Keyword(s)time series dataen_US
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Keyword(s)multi variate dataen_US
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Keyword(s)data fusionen_US
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Dewey Decimal Classification number(s)150
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TitleSharing data pipelines: Why sharing data may not be enough, and what to do about iten_US
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DRO typeconferenceObject
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Visible tag(s)ZPID Conferences and Workshops