P 1.2
Open Science: open data, open materials, open methods, and open software
2018.09.27 — 09:00-10:30
Introduction 
Chair
Manoel Barral-Netto – Investigator & Vice-President for Education, Information and Communication, Fundação Oswaldo Cruz (Fiocruz)
Panelists
Barend Mons – Co-Leader, GO FAIR Initiative 
Claudia Bauzer Medeiros – Full professor, Universidade Estadual de Campinas (Unicamp); Coordinator, eScience & Data Science Programs, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Luciene Delazari – Professora Associada, Universidade Federal do Paraná (UFPR), Departamento de Geomática; Editora, Boletim de Ciências Geodésicas
Jonathan David Crabtree – Director for Cyberinfrastructure, University of North Carolina at Chapel Hill, Odum Institute for Research in Social Science; Leader, Global Dataverse Community Consortium (GDCC); President, International Federation of Data Organizations (IFDO)
About
Open Science is a movement to make scientific research, its data and dissemination accessible to all levels of society. This movement considers aspects such as Open Access, Open Data, Reproducible Research and Open Software.
Each of these aspects presents discreteness that need to be evaluated and discussed by the scientific community so that guidelines are established that facilitate the dissemination of scientific information.
The great challenge is to establish effective and efficient practices that allow journals to add these demands in their editorial processes, so as not only to allow data, software and methods to be accessible, but also to encourage the community to do so.
Considering these questions, this panel has as a proposal to discuss important aspects about the advancement of research communication. Some of these aspects are placed in the SciELO indexing criteria, as is the case of referencing research materials in favor of transparency and reproducibility.
Syllabus
FAIR criteria, concepts and implementation; challenges for the publication of data and methods; institutional policies for open data; adoption of TOP guidelines (Transparency and Openness Promotion); software repositories; thematic areas data repositories.
How to contribute
You are invited to participate and cooperate with the SciELO 20 Years celebration with comments, testimonies, blog posts, articles, etc, related to the topic of this or other panels.
Glossary
Open Access – Free online access to peer reviewed scientific content with licensing and copyright restrictions.
Open Science Evaluation – Evaluation of research results, not limited to peers, but with the contribution of society.
Open Science – Movement to make scientific research, data, and its dissemination accessible to all levels of society.
Data sharing – The act of distributing data in a format that can be used by other individuals.
Open Data – Online, cost-effective, accessible data that can be used, reused and distributed, provided the data source is assigned.
DataCite – Non-for-profit organization that provides identifiers (DOI) for research data.
Research Data Management Tools – Tools that assist the Data Management process.
Open Science Tools – Refers to the tools that can assist the Open Science building process. Among them there are Open Repositories and Open Services.
GitHub – repository for software sharing.
Registry of Research Data Repositories <https://www.re3data.org/> – An international catalog of data repositories, which are currently the best source for repositories. It started in May 2013, using the Open Science idea, according to Creative Commons, covering all areas of academic knowledge.
Interoperability –The ability of a system (computerized or otherwise) to communicate transparently (or as closely as possible) to another system (similar or not). For a system to be considered interoperable, it is very important that it works with open standards or ontologies.
Open Metrics and Impact – An alternative to traditional metric systems, open metrics allow a new way of assessing research impact. Examples: Altmetrics and Bilibometrics.
Research Data Management Standards – Standards that are relevant in the Data Management process.
Reproducible Open research – Provide users with free access to experimental elements for research reproducibility.
Research Data Management Plans – A data management plan is a formal document that establishes how to handle research data during the research phase and after it has been completed. Examples: DMPTool <https://dmptool.org/> and Oline DMP <https://dmponline.dcc.ac.uk/>.
Open Access Policies – A guide to best practices for applying Open Science and achieving its primary objectives.
Research Data Management Policies – Set of principles, typically produced by different institutions, that must be followed during the management of research data.
FAIR principles – Being Findable, Available, Interoperable, and Reusable.
Data Reuse – Use of data by someone other than the originator.
Research Data Management Services – Refers to (online) services that assist in Data Management process
TOP Guidelines – Transparency and Openness Promotion. They include eight modular standards, each of them with three levels of rigor. The journals select which of the eight standards they intend to adopt and select at the implementation level of each standard.
• Citation Standards
• Design and Analysis
• Transparency of data, analytical methods (code) and research materials
• Replication
• Pre-registration of studies
• Pre-registration of analysis plans
Source: https://osf.io/9f6gx/wiki/Guidelines/?_ga=2.29074296.534388759.1532548354-488636257.1532548354
Data use – Data collected by an individual for a specific research project.
Bibliography
DUDZIAK, Elisabeth A. Gestão de dados de pesquisa: o que precisamos saber hoje! 2018. Available from: <https://www.sibi.usp.br/?p=17574>
Irene V. Pasquetto, Ashley E. Sands, Peter T. Darch, and Christine L. Borgman. 2016. Open Data in Scientific Settings: From Policy to Practice. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16). ACM, New York, NY, USA, 1585-1596. DOI: https://doi.org/10.1145/2858036.2858543
Pasquetto, I.V., Randles, B.M. & Borgman, C.L., (2017). On the Reuse of Scientific Data. Data Science Journal. 16, p.8. DOI: http://doi.org/10.5334/dsj-2017-008
Sayão, Luis Fernando. Guia de Gestão de Dados de Pesquisa para Bibliotecários e Pesquisadores / Luis Fernando Sayão, Luana Farias Sales. – Rio de Janeiro : CNEN/IEN, 2015. 90 p
Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018. DOI: 10.1038/sdata.2016.18 (2016).
Posts
ANAND, S. Geo for All – Open Principles in GeoEducation and Science [online]. SciELO in Perspective, 2018 [viewed 13 July 2018]. Available from: https://blog.scielo.org/en/2018/07/13/geo-for-all-open-principles-in-geoeducation-and-science/
ESTEVÃO, J.S.B. Base de Dados Científicos da Universidade Federal do Paraná [online]. SciELO em Perspectiva, 2018 [viewed 18 September 2018]. Available from: https://blog.scielo.org/blog/2018/09/18/base-de-dados-cientificos-da-universidade-federal-do-parana
MEDEIROS, C.B. Scientific Data Management – from collection to preservation [online]. SciELO in Perspective, 2018 [viewed 22 June 2018]. Available from: https://blog.scielo.org/en/2018/06/22/scientific-data-management-from-collection-to-preservation/
Articles
In development.
Statements
SciELO. SciELO 20 | P1.2 Rafael Port fala sobre o CEDAP. 2018 [viewed 15 October 2018]. Available from: https://youtu.be/6eZVS_DgFIY
