Difference between revisions of "Neururer 2017 Abstract Global Biobank Week 2017"
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|authors=Neururer SB, Laner V, Sigl R, Hofer-Picout P, Gnaiger E, Goebel G | |authors=Neururer SB, Laner V, Sigl R, Hofer-Picout P, Gnaiger E, Goebel G | ||
|year=2017 | |year=2017 | ||
|event=Global Biobank Week | |event=Global Biobank Week 2017 | ||
|abstract=Reproducible mitochondrial research strongly relies on high quality of samples and data. In order to standardize mitochondrial data and facilitate data exchange between research groups, we developed a concept for a minimal research data set. This development was based on MIABIS (Minimum Information About Biobank data Sharing) [1], a standard created for sharing meta data related to biobanks and biosample collections. We evaluated, which basic data is necessary for describing a minimal mitochondrial dataset and to which extent MIABIS can be applied and needs extension for this purpose. Therefore, we performed a structured analysis which included a definition and a typological analysis of available free-text information about mitochondrial research and sample information by following the approach of Neururer et al. [2]. This enabled us to identify relevant data fields for mitochondrial research and sample data. The relevant fields were mapped to those offered by MIABIS. This step showed, to which extent MIABIS covered the required data field and which fields had to be added in order to fulfil the requirements of standardizing mitochondrial research data. In the final step, a concept for an innovative mitochondrial data model was developed. The presented project combined different approaches from interdisciplinary fields of research (e.g. computer science, social sciences, biology) and enriched the current state of mitochondrial knowledge management to enhance mitochondrial research networking [3]. | |abstract=Reproducible mitochondrial research strongly relies on high quality of samples and data. In order to standardize mitochondrial data and facilitate data exchange between research groups, we developed a concept for a minimal research data set. This development was based on MIABIS (Minimum Information About Biobank data Sharing) [1], a standard created for sharing meta data related to biobanks and biosample collections. We evaluated, which basic data is necessary for describing a minimal mitochondrial dataset and to which extent MIABIS can be applied and needs extension for this purpose. Therefore, we performed a structured analysis which included a definition and a typological analysis of available free-text information about mitochondrial research and sample information by following the approach of Neururer et al. [2]. This enabled us to identify relevant data fields for mitochondrial research and sample data. The relevant fields were mapped to those offered by MIABIS. This step showed, to which extent MIABIS covered the required data field and which fields had to be added in order to fulfil the requirements of standardizing mitochondrial research data. In the final step, a concept for an innovative mitochondrial data model was developed. The presented project combined different approaches from interdisciplinary fields of research (e.g. computer science, social sciences, biology) and enriched the current state of mitochondrial knowledge management to enhance mitochondrial research networking [3]. | ||
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:::Neururer SB(1), Laner V(2), Sigl R(2), Hofer-Picout P(1), Gnaiger E(2,3), Göbel G(1) | :::Neururer SB(1), Laner V(2), Sigl R(2), Hofer-Picout P(1), Gnaiger E(2,3), Göbel G(1) | ||
:::#Dept Medical Statistics, Informatics Health Economics, Medical Univ | :::# Dept Medical Statistics, Informatics Health Economics, Medical Univ Innsbruck | ||
:::# | :::# Oroboros Instruments, Innsbruck, Austria | ||
:::#Dept Visceral, Transplant Thoracic Surgery, D. Swarovski Research Lab, Medical Univ; Innsbruck, Austria. | :::# Dept Visceral, Transplant Thoracic Surgery, D. Swarovski Research Lab, Medical Univ; Innsbruck, Austria. | ||
:::: [email protected] | |||
== References and support == | == References and support == | ||
:::#Norlin L, Fransson MN, Eriksson M, Merino-Martinez R, Anderberg M, Kurtovic S, Litton JE (2012) A Minimum Data Set for Sharing Biobank Samples, Information, and Data: MIABIS. Biopreserv Biobank 10:343–8. | :::# Norlin L, Fransson MN, Eriksson M, Merino-Martinez R, Anderberg M, Kurtovic S, Litton JE (2012) A Minimum Data Set for Sharing Biobank Samples, Information, and Data: MIABIS. Biopreserv Biobank 10:343–8. | ||
:::#Neururer SB, Lasierra N, Peiffer KP, Fensel D (2016) Formalizing the Austrian Procedure Catalogue: A 4-step methodological analysis approach. J Biomed Inform 60:1–13. | :::# Neururer SB, Lasierra N, Peiffer KP, Fensel D (2016) Formalizing the Austrian Procedure Catalogue: A 4-step methodological analysis approach. J Biomed Inform 60:1–13. | ||
:::#[[MitoPedia]] | :::# [[MitoPedia]] | ||
:::Supported by FFG Austrian Research Promotion Agency and [[ | ::: Supported by FFG Austrian Research Promotion Agency and [[Oroboros Instruments]]. | ||
Latest revision as of 16:31, 23 January 2019
| Extending MIABIS for the development of a standardized minimum dataset for mitochondrial research data. |
Link: [1]
Neururer SB, Laner V, Sigl R, Hofer-Picout P, Gnaiger E, Goebel G (2017)
Event: Global Biobank Week 2017
Reproducible mitochondrial research strongly relies on high quality of samples and data. In order to standardize mitochondrial data and facilitate data exchange between research groups, we developed a concept for a minimal research data set. This development was based on MIABIS (Minimum Information About Biobank data Sharing) [1], a standard created for sharing meta data related to biobanks and biosample collections. We evaluated, which basic data is necessary for describing a minimal mitochondrial dataset and to which extent MIABIS can be applied and needs extension for this purpose. Therefore, we performed a structured analysis which included a definition and a typological analysis of available free-text information about mitochondrial research and sample information by following the approach of Neururer et al. [2]. This enabled us to identify relevant data fields for mitochondrial research and sample data. The relevant fields were mapped to those offered by MIABIS. This step showed, to which extent MIABIS covered the required data field and which fields had to be added in order to fulfil the requirements of standardizing mitochondrial research data. In the final step, a concept for an innovative mitochondrial data model was developed. The presented project combined different approaches from interdisciplinary fields of research (e.g. computer science, social sciences, biology) and enriched the current state of mitochondrial knowledge management to enhance mitochondrial research networking [3].
Labels:
Track: N1) Reproducibility in Research: Quality and Heterogeneity
Affiliations
- Neururer SB(1), Laner V(2), Sigl R(2), Hofer-Picout P(1), Gnaiger E(2,3), Göbel G(1)
- Dept Medical Statistics, Informatics Health Economics, Medical Univ Innsbruck
- Oroboros Instruments, Innsbruck, Austria
- Dept Visceral, Transplant Thoracic Surgery, D. Swarovski Research Lab, Medical Univ; Innsbruck, Austria.
References and support
- Norlin L, Fransson MN, Eriksson M, Merino-Martinez R, Anderberg M, Kurtovic S, Litton JE (2012) A Minimum Data Set for Sharing Biobank Samples, Information, and Data: MIABIS. Biopreserv Biobank 10:343–8.
- Neururer SB, Lasierra N, Peiffer KP, Fensel D (2016) Formalizing the Austrian Procedure Catalogue: A 4-step methodological analysis approach. J Biomed Inform 60:1–13.
- MitoPedia
- Supported by FFG Austrian Research Promotion Agency and Oroboros Instruments.
