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Sharing data pipelines: Why sharing data may not be enough, and what to do about it.

Käthner, David (2020) Sharing data pipelines: Why sharing data may not be enough, and what to do about it. Sharing psychological research data: Best practices and new developments (CSPD2020), 07.-08.Dez. 2020, Online.

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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.

Item URL in elib:https://elib.dlr.de/140472/
Document Type:Conference or Workshop Item (Speech)
Title:Sharing data pipelines: Why sharing data may not be enough, and what to do about it.
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Käthner, DavidUNSPECIFIEDhttps://orcid.org/0000-0003-4168-2266UNSPECIFIED
Date:7 December 2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:data pipeline; data; reproducible research;
Event Title:Sharing psychological research data: Best practices and new developments (CSPD2020)
Event Location:Online
Event Type:international Conference
Event Dates:07.-08.Dez. 2020
Organizer:Leibniz Institute for Psychology Information (ZPID)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Energie und Verkehr (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Käthner, David
Deposited On:15 Jan 2021 10:52
Last Modified:15 Jan 2021 10:52

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