From Open Data to Open Science

Ramachandran, Rahul; Bugbee, Kaylin; Murphy, Kevin

doi:10.1029/2020ea001562

Cited by 57 publications

(45 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The FAIR principles also refer to the software hosting infrastructures that need to be supported and maintained. Therefore, both researchers/software developers and repositories need to enhance the visibility to promote reuse of the research software, and to enable computational reproducibility and transparency (Ramachandran et al, 2021) to speed up scientific advance and innovation. Within the framework of the EOSC Synergy Project (2022), DIGITAL.CSIC is developing an evaluation tool that will automatically assess the FAIRness of their digital objects to help: 1) researchers to better describe and manage their research products and, 2) repository administrators to identify technological issues for further development.…”

Section: Open Questions and Further Stepsmentioning

confidence: 99%

Towards a Digital Twin of the Earth System: Geo-Soft-CoRe, a Geoscientific Software & Code Repository

et al. 2022

View full text Add to dashboard Cite

The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.Systematic Review Registration: https://digital.csic.es/handle/10261/193580.

show abstract

Section: Open Questions and Further Stepsmentioning

confidence: 99%

Towards a Digital Twin of the Earth System: Geo-Soft-CoRe, a Geoscientific Software & Code Repository

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Open Science [16] is a movement promoted by the OECD 2 countries and promoted by the European Commission. It advocates free access by citizens to the results of scientific research, data, resources, results, thoughts, as well as that the results and discoveries of scientific research are universally accessible and unrestricted.…”

Section: Open Sciencementioning

confidence: 99%

“…To ease off those limitations, we have designed FMRepo, a first prototype of a new repository for feature model exchange and knowledge sharing. FMRepo aims to integrate both the common variability language and feature model analysis capabilities that are in consonance with other MODEVAR initiatives, such as the proposed universal variability language (UVL) [1], and the framework for automated analysis of feature models (AAFM) [6], as well as adhering to open science principles [16]. Meet open science standards.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A first prototype of a new repository for feature model exchange and knowledge sharing

Romero

Galindo

Horcas

et al. 2021

Proceedings of the 25th ACM International Systems and Software Product Line Conference - Volume B

View full text Add to dashboard Cite

Feature models are the "de facto" standard for variability modelling and are used in both academia and industry. The MODEVAR initiative tries to establish a common textual feature modelling language that can be used by different communities and can allow information sharing. Feature model related researches use different models for different purposes such as analysis, sampling, testing, debugging, teaching, etc. Those models are shared in private repositories and there is a risk that all that knowledge is spread across different platforms which hinder collaboration and knowledge reuse. In this paper, we propose a first working version of a new feature model repository that allows to centralise the knowledge generated in the community together with advanced capabilities such as DOI generation, an API, analysis reports, among others. Our solution is a front end interface that uses the popular open science repository Zenodo as an end point to materialise the storage of all the information. Zenodo is enhanced with characteristics that facilitate the management of the models. The idea of our repository is to provide existing but also new features that are not present in other repositories (e.g., SPLOT). We propose to populate our repository with all the existing models of many sources including SPLOT. CCS CONCEPTS• Software and its engineering → Software product lines; Requirements analysis; Software design engineering; Software implementation planning;␣

show abstract

“…It is as important to include these data and the conclusions drawn from them. The availability of published data has been recognised as being of crucial importance (Ramachandran et al, 2021;Reichman et al, 2011). For comparative studies and for meta-analyses, data are more valuable than interpretations.…”

mentioning

confidence: 99%

Field studies need to report essential information on social organisation – independent of the study focus

2021

View full text Add to dashboard Cite

Comparative studies on social evolution are ideally based on large datasets to ensure high statistical power, but their scientific validity also relies on the quality of the data. However, even though social organization, i.e., the composition of social units, is measured in many field studies testing specific hypotheses, these data are often not adequately reported. Here, 2 we summarise which data on social organization should always be reported regardless of the study focus to make them available for comparative studies. As an example, we report data from a literature survey on one of the four superorders of placental mammals, the Xenarthra from South America (armadillos, anteaters and sloths), of which all 30 species are generally assumed to be solitary living. In total we found 4510 articles. The titles and abstracts of 61 publications indicated that data on social organization were collected, but only 12 publications contained sufficient information for us to determine the social organization. We found reliable information on nine species, of which seven were strictly solitary. Two species showed a combination of solitary-living and pair-living with one including female groups. This review therefore indicates that Xenarthra may not be exclusively solitary. Our literature survey further shows that valuable data are often not reported even though it can be assumed that these data had been collected. We report examples from 23 additional studies on monotremes, marsupials, and two other placental superorders showing similar issues in reporting data. It is important to make authors aware that this information would be valuable for comparative studies. In sum, we recommend including data on the composition of social units, sex of individuals, occupancy of sleeping sites, frequency of observations and trapping events, home range overlap, and the proportion of the individuals in the study area, independent of the study question in all publications.

show abstract

From Open Data to Open Science

Cited by 57 publications

References 59 publications

Towards a Digital Twin of the Earth System: Geo-Soft-CoRe, a Geoscientific Software & Code Repository

Towards a Digital Twin of the Earth System: Geo-Soft-CoRe, a Geoscientific Software & Code Repository

A first prototype of a new repository for feature model exchange and knowledge sharing

Field studies need to report essential information on social organisation – independent of the study focus

Contact Info

Product

Resources

About