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Publications

Publications by Yulia Karimova

2017

Involving data creators in an ontology-based design process for metadata models

Authors
Castro, JA; Amorim, RC; Gattelli, R; Karimova, Y; Da Silva, JR; Ribeiro, C;

Publication
Developing Metadata Application Profiles

Abstract
Research data are the cornerstone of science and their current fast rate of production is disquieting researchers. Adequate research data management strongly depends on accurate metadata records that capture the production context of the datasets, thus enabling data interpretation and reuse. This chapter reports on the authors' experience in the development of the metadata models, formalized as ontologies, for several research domains, involving members from small research teams in the overall process. This process is instantiated with four case studies: vehicle simulation; hydrogen production; biological oceanography and social sciences. The authors also present a data description workflow that includes a research data management platform, named Dendro, where researchers can prepare their datasets for further deposit in external data repositories. © 2017, IGI Global.

2017

Promoting Semantic Annotation of Research Data by Their Creators: A Use Case with B2NOTE at the End of the RDM Workflow

Authors
Karimova, Y; Castro, JA; da Silva, JR; Pereira, N; Ribeiro, C;

Publication
Metadata and Semantic Research - 11th International Conference, MTSR 2017 Tallinn, Estonia, November 28 - December 1, 2017, Proceedings

Abstract
Research data management is promoted at different levels with awareness actions carried out to encourage cooperation between researchers. However, data management requires tools to set the scene for researchers and institutions to disseminate the research data they produce. In this context good quality metadata play an important role by enabling data reuse. EUDAT is an European common data infrastructure, with integrated services for data preservation and dissemination. The TAIL project, at the University of Porto, proposes workflows based on Dendro, a collaborative environment that helps researchers prepare well described datasets and deposit them in a data repository. We propose a data deposit workflow use case for a small research project with emphasis in data annotation. Data is organized and described in Dendro; deposited in B2SHARE; and semantic annotation is performed with the new B2NOTE service from EUDAT. © Springer International Publishing AG 2017.

2017

Description + annotation: semantic data publication workflow with Dendro and B2NOTE

Authors
Karimova, Y; Castro, JA; da Silva, JR; Pereira, N; Rodrigues, J; Ribeiro, C;

Publication
Int. J. Metadata Semant. Ontologies

Abstract
Metadata puts research data in their context, making data intelligible and apt to sustain technology evolution and to be reused, in compliance with the FAIR principles. The workflow proposed in this work includes metadata generation in the context of research projects, created with the Dendro platform, and metadata originated in the interaction of people with the deposited data, created with the B2NOTE service from EUDAT. In our experiments, datasets are prepared with Dendro, taking into consideration general-purpose descriptors and domain-specific ones, then transparently deposited in B2SHARE. After publication, B2NOTE provides an environment where authors, other researchers, and any interested party can enrich the description with less formal comments, tags or keywords. This work contributes with (a) a set of use cases in several domains, (b) details on the descriptors used by authors in each case, and (c) reflections on the use of data after publication, using the B2NOTE contributions. © Copyright 2017 Inderscience Enterprises Ltd.

2019

Data Deposit in a CKAN Repository: A Dublin Core-Based Simplified Workflow

Authors
Karimova, Y; Castro, JA; Ribeiro, C;

Publication
Digital Libraries: Supporting Open Science - 15th Italian Research Conference on Digital Libraries, IRCDL 2019, Pisa, Italy, January 31 - February 1, 2019, Proceedings

Abstract
Researchers are currently encouraged by their institutions and the funding agencies to deposit data resulting from projects. Activities related to research data management, namely organization, description, and deposit, are not obvious for researchers due to the lack of knowledge on metadata and the limited data publication experience. Institutions are looking for solutions to help researchers organize their data and make them ready for publication. We consider here the deposit process for a CKAN-powered data repository managed as part of the IT services of a large research institute. A simplified data deposit process is illustrated here by means of a set of examples where researchers describe their data and complete the publication in the repository. The process is organised around a Dublin Core-based dataset deposit form, filled by the researchers as preparation for data deposit. The contacts with researchers provided the opportunity to gather feedback about the Dublin Core metadata and the overall experience. Reflections on the ongoing process highlight a few difficulties in data description, but also show that researchers are motivated to get involved in data publication activities.

2020

Institutional Support for Data Management Plans: Five Case Studies

Authors
Karimova, Y; Ribeiro, C; David, G;

Publication
Metadata and Semantic Research - 14th International Conference, MTSR 2020, Madrid, Spain, December 2-4, 2020, Revised Selected Papers

Abstract
Researchers are being prompted by funders and institutions to expose the variety of results of their projects and to submit a Data Management Plan as part of their funding requests. In this context, institutions are looking for solutions to provide support to research data management activities in general, including DMP creation. We propose a collaborative approach where a researcher and a data steward create a DMP, involving other parties as required. We describe this collaborative method and its implementation, by means of a set of case studies that show the importance of the data steward in the institution. Feedback from researchers shows that the DMP are simple enough to lead people to engage in data management, but present enough challenges to constitute an entry point to the next level, the machine-actionable DMP. © 2021, Springer Nature Switzerland AG.

2021

Institutional support for data management plans: case studies for a systematic approach

Authors
Karimova, Y; Ribeiro, C; David, G;

Publication
Int. J. Metadata Semant. Ontologies

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community. © 2021 Inderscience Enterprises Ltd.. All rights reserved.