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2026
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English
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- Description:
- This data collection template serves the purpose of collecting primary life cycle inventory (LCI) data for the life cycle assessment (LCA) of reuse concrete building elements from reuse practitioners and researchers conducting experimental work. The template aids in documenting building element specific energy and resource consumptions caused during the reuse process. The template was developed in the context of CRC 1683 by sub-project C02, responsible for the LCA of the building element reuse process. , About the CRC 1683: The German construction sector is responsible for a substantial resource and energy consumption, as well as high waste generation. CRC 1683 explores the possibility of a circular modular reuse of cast-in-place concrete load-bearing structures, to mitigate these environmental impacts. Divided into three project groups, the CRC researches all process steps necessary for the reuse, from the disassembly of source load-bearing structures, the characterisation of the reuse building elements properties and conditions, their refurbishment, and their connection and installation into new target structures. More information on CRC 1683 can be obtained from: https://www.sfb1683.ruhr-uni-bochum.de/mru/index.html.en, and Sub-project C02: Sub-project C02 evaluates the environmental benefits of the reuse process developed in CRC 1683 by means of Life Cycle Assessment (LCA) on the building element, building, and national building stock levels. The template presented in this dataset was created to gather the necessary Life Cycle Inventory (LCI) data from sub-projects conducting experimental works for the LCA of the reuse process on the building element level.
- Keyword:
- LCA, Life Cycle Assessment, Circular Economy, CE, Construction, and Sustainability
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-21
- Date Modified:
- 2026-01-23
- License:
- Creative Commons BY Attribution 4.0 International
- Resource Type:
- Dataset
-
- Description:
- The provided Bash scripts are used to convert raw magnetic resonance imaging (Magnetic Resonance Imaging, MRI) data from the Digital Imaging and Communications in Medicine (DICOM) standard format into a Brain Imaging Data Structure (BIDS)-compliant dataset. The scripts convert DICOM files into the Neuroimaging Informatics Technology Initiative (NIfTI) format, which can be used for preprocessing MRI data. In addition to the NIfTI files, the conversion also generates the metadata required by the BIDS standard. Dataset quality and compliance can be checked using a BIDS validator (e.g., https://bids-standard.github.io/bids-validator/). The two scripts are adapted for different experimental sessions: script_dcm2nii_S1.sh is used for data from the first session (S1), while script_dcm2nii_S2.sh is used for the second session (S2). The scripts differ in that S2 additionally processes diffusion-weighted imaging (DWI) data. Both scripts were developed as part of my own work with my individual MRI data. If you want to use them on your own data, you may need to adjust the scripts to match your raw data’s naming conventions. For more information, see the ReadMe file.
- Keyword:
- NIfTI (Neuroimaging Informatics Technology Initiative), conversion, Bash script, DICOM (Digital Imaging and Communications in Medicine), and BIDS (Brain Imaging Data Structure)
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-20
- License:
- MIT License
- Resource Type:
- Software
-
- Description:
- This R script was developed to “translate” movement log files from a navigation task (path integration) experiment into so-called 'event tables'. These event tables summarize the recorded movements and can be used for further analyses, for example, to synchronize movement logs with brain activity. The script processes all CSV log files in a specified folder, classifies movement types, groups consecutive events, calculates onset, duration, and angles, and generates both individual and combined master event tables. Sample data are provided to test the script, though path adjustments are required. For more information, see the ReadMe file.
- Keyword:
- RStudio script, Movement log, and Event Table
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Software
-
- Description:
- Generates configurable path integration (PI) patterns for Virtual Reality (VR) navigation experiments with RStudio. Creates 4-point configurations (Spawn→Start→Distractor→Goal→back to Start) optimized for maximum path length while respecting geometric constraints. The script was developed out of the need for rapid randomized generation of path integration patterns that can be easily adapted to the respective experimental conditions. In addition to the actual RStudio script, the package also contains an accompanying ReadMe file, sample input data, and the corresponding output files.
- Keyword:
- Virtual Experiments, Path Integration, RStudio script, and Virtual Environments
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Dataset
-
- Description:
- Visualizes participant navigation trajectories from Virtual Reality (VR) path integration (PI) experiments, showing target locations, traversed paths, orientation arrows, and drop error distances in RStudio. The script was developed to check whether participants performed the task correctly or whether other problems occurred during a trial (e.g., path integration marker was not deactivated correctly). Such trials were successfully excluded from further data analysis using the visualization script. In addition to the actual RStudio script, the package also includes an accompanying ReadMe file, sample input data, and the corresponding output visualizations.
- Keyword:
- RStudio script, path visualization, and path integration
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Dataset
