Development of open science validation framework

Purpose: In the last decade, open science has been a hot topic in the research community.

Since scientific knowledge may be monopolized by certain people and has limited access to

all members of society. The need for a science is felt on a global scale that is available to

everyone without restrictions, but the validation of such science will always be a challenge.

Therefore, the purpose of this research is to develop a validation framework for open science.

Other goals of the research were: identifying the main differences between open science and

traditional science, identifying the main component of open science validation, identifying

open science validation criteria and metrics, identifying open science validation framework.

Method: In terms of the exploratory type and in terms of approach, this research is classified

as qualitative research. Two methods of grounded theory (foundation data) and systematic

literature review were used to conduct the research. The statistical population included all

expert professors and experts in the field of open science. The number of 5 people who were

selected for interview through theoretical saturation as a combination of purposeful sampling

and snowballing according to the level of familiarity with the research topic. In the present

study, semi-structured interviews were used to collect data in the qualitative part. The

implementation of this research has included several stages. First, by identifying the

researchers conducted in the field of evaluation and validation of open science, they were

systematically examined. Due to the lack of resources in this field, more reviewed research

was used to formulate the problem. In the second step, the foundation data theory method

was used. For this, in-depth interviews were conducted with people who have published

articles, books, etc. in the field of evaluation and validation of scientific works. Interviews

continued until saturation was reached. In order to set the interview questions and to ensure

their content validity, the opinions of experts knowledgeable about the subject were first

summarized to prepare the general framework of the semi-structured interview. Data analysis

was done first by open coding and how to code the interviews, and after explaining the way

concepts and categories were formed, a narrative of foundational data theorizing, and the

resulting theory was given. In order to set the interview questions and to ensure their content

validity, the opinions of experts knowledgeable about the subject were first summarized to

prepare the general framework of the semi-structured interview. Data analysis was done first

by open coding and how to code the interviews, and after explaining the way concepts and

categories were formed, a narrative of foundational data theorizing, and the resulting theory

was given.

Findings: According to the findings, causal conditions (free access and usefulness of articles)

on the central category (sharing in knowledge and science) and these two action strategies

(communication messages of published articles) using intervening conditions (research

achievements) and background conditions (evaluation) correct articles, ranking magazines)

led to consequences such as two-way communication in the interactions of knowledge and

science and the development of self-knowledge.



Conclusion: open science is an approach to science. Open scientific validation has several

components that may differ depending on its purpose and method. Overall, open science

validation aims to promote transparency, collaboration and reproducibility in scientific

research and data, leading to more reliable and impactful results that benefit society at large.

Open scientific validation may be based on different criteria and criteria depending on the

type and nature of the research, the type and nature of the source, the type and nature of the

data, the type and nature of the publication, as well as the purpose and method of validation.

Finally, the open science validation framework is a structure that is used to evaluate and

improve the quality, credibility, and transparency of science research. The open science

validation framework may be defined and implemented based on criteria, indicators,

requirements, standards, methods and processes.