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==Abstract== | ==Abstract== | ||
The transformation and consequent use of new digital technologies not only have a substantial impact on society and companies, but also on science. Analog documentation and research, as we have known it for centuries, will eventually be replaced by intelligent, more [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|FAIR]] (findable, accessible, interoperable, and reusable) digital methods ands systems. In addition to the actual [[research]] data and results, [[metadata]] now plays an important role not only for individual, independently existing projects, but also for future scientific use and interdisciplinary research groups and disciplines. The solution presented here, consisting of an [[electronic laboratory notebook]] (ELN) and [[laboratory information management system]] (LIMS) based on the [[openBIS]] (open Biology Information System) environment, offers interesting features and advantages, especially for interdisciplinary work. The Collaborative Research Centre (CRC) 1411 "Design of Particulate Products" of the German Research Foundation is characterized by the cooperation of different working groups of synthesis, characterization, and simulation, and therefore serves as a model environment to present this implementation of openBIS. OpenBIS, as an [[Open-source software|open-source]] ELN-LIMS solution following FAIR principles, provides a common set of general entries, with the possibility of [[Data sharing|sharing]] and linking (meta-)data to improve the scientific exchange between all users. | The transformation of existing technologies and consequent use of new digital technologies not only have a substantial impact on society and companies, but also on science. Analog documentation and research, as we have known it for centuries, will eventually be replaced by intelligent, more [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|FAIR]] (findable, accessible, interoperable, and reusable) digital methods ands systems. In addition to the actual [[research]] data and results, [[metadata]] now plays an important role not only for individual, independently existing projects, but also for future scientific use and interdisciplinary research groups and disciplines. The solution presented here, consisting of an [[electronic laboratory notebook]] (ELN) and [[laboratory information management system]] (LIMS) based on the [[openBIS]] (open Biology Information System) environment, offers interesting features and advantages, especially for interdisciplinary work. The Collaborative Research Centre (CRC) 1411 "Design of Particulate Products" of the German Research Foundation is characterized by the cooperation of different working groups of synthesis, characterization, and simulation, and therefore serves as a model environment to present this implementation of openBIS. OpenBIS, as an [[Open-source software|open-source]] ELN-LIMS solution following FAIR principles, provides a common set of general entries, with the possibility of [[Data sharing|sharing]] and linking (meta-)data to improve the scientific exchange between all users. | ||
'''Keywords''': open science, research data management, databases, ELN-LIMS, interdisciplinary work | '''Keywords''': open science, research data management, databases, ELN-LIMS, interdisciplinary work | ||
==Introduction== | ==Introduction== | ||
Digital transformation is a key challenge that impacts our entire society. The main players here are companies that use intelligent information technologies (IT) and networks for machines and processes. Starting with flexible production via modular, changeable production processes and moving to customer-specific solutions and products requires the help of sophisticated data acquisition, processing, and [[Data analysis|analysis]]. [Bauernhansl et al. 2014; Lasi et al. 2014] Further examples of digital transformation include automation processes, machine-to-machine communication, [[internet of things]] (IoT) process implementation, or even augmented-reality-based [[workflow]]s. [Bauernhansl et al. 2014; Egger & Masood, 2020; Lasi et al. 2014; Li et al. 2015] | |||
However, not only companies are subject to this change, but also government institutions (eGovernment) [Gisler 2001] and science itself. [Kimmig et al. 2021] Thus, the topic of "open science" has become a growing movement. [National Academies of Sciences, Engineering, and Medicine (U.S.) et al. 2018] Open science has been supported in the European context of the ''Open Research Data and Data Management Plans'' of the European Research Council (ERC), established by the European Commission for almost five years. However, the ERC has been promoting the causes of open science since 2007. [ERC Scientific Council 2021] This also has manifested in other ways, as, for example, open access publications from funded projects that have already become mandatory to a certain extent. Exemplarily, the DFG (German Research Foundation) supports infrastructure projects within Collaborative Research Centres (CRCs), which are long-term university-based [[research]] institutions established for up to 12 years, and whose funding objective is to establish powerful information systems for research in a holistic perspective. [German Research Foundation 2021] Accordingly, new infrastructure on a national (i.e., Germany's National Research Data Infrastructure; Nationale Forschungsdateninfrastruktur or NFDI) and European level (i.e., the European Open Science Cloud or EOSC) [European Commission 2016; Mons et al. 2017] have been established, fostering the subject of research [[Information management|data management]], data publications, and open science. Nevertheless, the topic of open science includes more than just the public provision of data in the context of open-access publications; it also includes the approaches of open methodologies, sources, and data. The necessary implementation and representation of good scientific data management, [[data quality]], and stewardship (data governance) are tremendously important. [Brous et al. 2016; Hildebrand et al. 2011; Ladley 2020; Wilkinson et al. 2016] The resulting benefits can be measured directly, such as in terms of improvements in process efficiency or cost and risk reductions, and indirectly, such as increased acceptance, perception, and trust. [Brous et al. 2016; Hildebrand et al. 2011; Tallon 2013] | |||
This paper presents an implementation of [[openBIS]], an [[electronic laboratory notebook]] (ELN) and [[laboratory information management system]] (LIMS) to support open science broadly, including data management, handling, storage, and publishing within a scientific [[laboratory]] environment. | |||
==Current state of research data management== | |||
===FAIR as part of research data management=== | |||
One of the cornerstones of this overall research data management (RDM) is the [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|FAIR principles]], which encourage research objects to be more findable, accessible, interoperable, and reusable. The emphasis placed on and the growing awareness of FAIRness is, however, more than just an essential duty that public funding agencies impose on research. Moreover, it is the key to conduct knowledge discovery, innovation, and [[information]] transfer, as well as the subsequent integration and reuse of research objects by the scientific community. [Wilkinson et al. 2016] Events such as the global [[Coronavirus disease 2019|COVID-19]] [[pandemic]] demonstrate the need for, and the overall benefits of, making data available online in a reusable fashion. [Besançon et al. 2021; Tse et al. 2020] This leads not only to efficient research and increased innovation, but also to fair and transparent use of public funds and tax capital, as well as increased visibility and scientific reputation and reliability, to name just a few benefits of open science. [Janssen et al. 2012] | |||
The FAIR principles propose that all scholarly output should embody the characteristics of being findable, accessible, interoperable, and reusable. While these principles provide guidance on the expected behaviors of data resources, their practical implementation has been subject to varying interpretations. As the support for these principles has grown, so has the diversity of interpretations surrounding their application. [Mons et al. 2017] FAIR principles recognize the need for data accessibility under defined conditions, but do not necessitate complete openness. While transparency and clarity are required for accessing and reusing data, restrictions can still remain based on privacy, security, and competitive concerns. FAIR promotes a balanced approach that allows diverse participation and partnerships while ensuring the availability of data within specified guidelines. [Mons et al. 2017] | |||
Revision as of 17:50, 4 June 2024
| Full article title | Using OpenBIS as a virtual research environment: An ELN-LIMS open-source database tool as a framework within the CRC 1411 Design of Particulate Products |
|---|---|
| Journal | Data Science Journal |
| Author(s) | Plass, Fabian; Englisch, Silvan; Zubiri, Benjamin A.; Pflug, Lukas; Spiecker, Erdmann; Stingl, Michael |
| Author affiliation(s) | Friedrich-Alexander-Universität Erlangen-Nürnberg |
| Primary contact | Email: michael dot stingl ay fau dot de |
| Year published | 2023 |
| Volume and issue | 22 |
| Article # | 44 |
| DOI | 10.5334/dsj-2023-044 |
| ISSN | 1683-1470 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://datascience.codata.org/articles/10.5334/dsj-2023-044 |
| Download | https://datascience.codata.org/articles/1500/files/655de35843b0d.pdf (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
The transformation of existing technologies and consequent use of new digital technologies not only have a substantial impact on society and companies, but also on science. Analog documentation and research, as we have known it for centuries, will eventually be replaced by intelligent, more FAIR (findable, accessible, interoperable, and reusable) digital methods ands systems. In addition to the actual research data and results, metadata now plays an important role not only for individual, independently existing projects, but also for future scientific use and interdisciplinary research groups and disciplines. The solution presented here, consisting of an electronic laboratory notebook (ELN) and laboratory information management system (LIMS) based on the openBIS (open Biology Information System) environment, offers interesting features and advantages, especially for interdisciplinary work. The Collaborative Research Centre (CRC) 1411 "Design of Particulate Products" of the German Research Foundation is characterized by the cooperation of different working groups of synthesis, characterization, and simulation, and therefore serves as a model environment to present this implementation of openBIS. OpenBIS, as an open-source ELN-LIMS solution following FAIR principles, provides a common set of general entries, with the possibility of sharing and linking (meta-)data to improve the scientific exchange between all users.
Keywords: open science, research data management, databases, ELN-LIMS, interdisciplinary work
Introduction
Digital transformation is a key challenge that impacts our entire society. The main players here are companies that use intelligent information technologies (IT) and networks for machines and processes. Starting with flexible production via modular, changeable production processes and moving to customer-specific solutions and products requires the help of sophisticated data acquisition, processing, and analysis. [Bauernhansl et al. 2014; Lasi et al. 2014] Further examples of digital transformation include automation processes, machine-to-machine communication, internet of things (IoT) process implementation, or even augmented-reality-based workflows. [Bauernhansl et al. 2014; Egger & Masood, 2020; Lasi et al. 2014; Li et al. 2015]
However, not only companies are subject to this change, but also government institutions (eGovernment) [Gisler 2001] and science itself. [Kimmig et al. 2021] Thus, the topic of "open science" has become a growing movement. [National Academies of Sciences, Engineering, and Medicine (U.S.) et al. 2018] Open science has been supported in the European context of the Open Research Data and Data Management Plans of the European Research Council (ERC), established by the European Commission for almost five years. However, the ERC has been promoting the causes of open science since 2007. [ERC Scientific Council 2021] This also has manifested in other ways, as, for example, open access publications from funded projects that have already become mandatory to a certain extent. Exemplarily, the DFG (German Research Foundation) supports infrastructure projects within Collaborative Research Centres (CRCs), which are long-term university-based research institutions established for up to 12 years, and whose funding objective is to establish powerful information systems for research in a holistic perspective. [German Research Foundation 2021] Accordingly, new infrastructure on a national (i.e., Germany's National Research Data Infrastructure; Nationale Forschungsdateninfrastruktur or NFDI) and European level (i.e., the European Open Science Cloud or EOSC) [European Commission 2016; Mons et al. 2017] have been established, fostering the subject of research data management, data publications, and open science. Nevertheless, the topic of open science includes more than just the public provision of data in the context of open-access publications; it also includes the approaches of open methodologies, sources, and data. The necessary implementation and representation of good scientific data management, data quality, and stewardship (data governance) are tremendously important. [Brous et al. 2016; Hildebrand et al. 2011; Ladley 2020; Wilkinson et al. 2016] The resulting benefits can be measured directly, such as in terms of improvements in process efficiency or cost and risk reductions, and indirectly, such as increased acceptance, perception, and trust. [Brous et al. 2016; Hildebrand et al. 2011; Tallon 2013]
This paper presents an implementation of openBIS, an electronic laboratory notebook (ELN) and laboratory information management system (LIMS) to support open science broadly, including data management, handling, storage, and publishing within a scientific laboratory environment.
Current state of research data management
FAIR as part of research data management
One of the cornerstones of this overall research data management (RDM) is the FAIR principles, which encourage research objects to be more findable, accessible, interoperable, and reusable. The emphasis placed on and the growing awareness of FAIRness is, however, more than just an essential duty that public funding agencies impose on research. Moreover, it is the key to conduct knowledge discovery, innovation, and information transfer, as well as the subsequent integration and reuse of research objects by the scientific community. [Wilkinson et al. 2016] Events such as the global COVID-19 pandemic demonstrate the need for, and the overall benefits of, making data available online in a reusable fashion. [Besançon et al. 2021; Tse et al. 2020] This leads not only to efficient research and increased innovation, but also to fair and transparent use of public funds and tax capital, as well as increased visibility and scientific reputation and reliability, to name just a few benefits of open science. [Janssen et al. 2012]
The FAIR principles propose that all scholarly output should embody the characteristics of being findable, accessible, interoperable, and reusable. While these principles provide guidance on the expected behaviors of data resources, their practical implementation has been subject to varying interpretations. As the support for these principles has grown, so has the diversity of interpretations surrounding their application. [Mons et al. 2017] FAIR principles recognize the need for data accessibility under defined conditions, but do not necessitate complete openness. While transparency and clarity are required for accessing and reusing data, restrictions can still remain based on privacy, security, and competitive concerns. FAIR promotes a balanced approach that allows diverse participation and partnerships while ensuring the availability of data within specified guidelines. [Mons et al. 2017]
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
