Materials Informatics and Data Science

Ethics Policies

1. Conflict of Interest

   A conflict of interest occurs when an individual's objectivity is potentially compromised by a desire for financial gain, prominence, professional advancement or a successful outcome. MIDS Editors strive to ensure that what is published in the Journal is as balanced, objective and evidence-based as possible. Since it can be difficult to distinguish between an actual conflict of interest and a perceived conflict of interest, the Journal requires authors to disclose all and any potential conflicts of interest.

   Conflicts of interest may be financial or non-financial. Financial conflicts include, but are not limited to, financial relationships such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; expert testimony or patent-licensing arrangements. Non-financial conflicts include, but are not limited to, personal or professional relationships, affiliations, academic competition, intellectual passion, knowledge or beliefs that might affect objectivity.

   Authors must declare any and all conflicts of interest at the end of their manuscript, before the References section. MIDS will follow guidelines from the Committee on Publication Ethics to manage any issues related to conflict of interest.

2. Materials Data Governance and Ethics

   The publication of research that involves data science and materials data requires careful consideration of materials data governance, transparency, and ethics. All research articles must include a section on Materials Data Governance and Ethics that will contain one of the following (depending on the type of the papers)

   • Data Governance: Proper materials data governance involves defining guidelines for data collection, storage, and usage to ensure the accuracy, reliability, and security of the data used in research. Ensuring data fairness and appropriate preprocessing is essential to minimize biases in machine learning models. Adhering to data governance principles helps maintain the integrity of the research findings and enables reproducibility by providing a clear and organized data management framework.

   • Transparency: Transparency in data-driven research involves providing clear and detailed information about the data sources, preprocessing steps, and model architecture used in the study. Transparent reporting allows readers to evaluate the validity and potential biases of the machine learning models and materials data, fostering trust in the research outcomes. In materials science, it's crucial to understand the reasoning behind artificial intelligence-generated material designs or predictions. Efforts should be made to develop interpretable artificial intelligence models to promote transparency and trust.

   • Ethical Considerations: includes obtaining informed consent when using human or proprietary data, ensuring data privacy and confidentiality, and considering potential social and environmental impacts of the research. For investigation of human subjects, state explicitly that informed consent was obtained from all participating adult subjects and from parents or legal guardians for minors or incapacitated adults, together with the manner in which informed consent was obtained (i.e., oral or written). Evidence to support the informed consent should be made available to the Editor upon request.

   • Reproducibility: Transparent reporting and proper data governance facilitate reproducibility, allowing other researchers to validate and build upon published research. Open sharing of materials data and machine learning code promotes collaboration and advances scientific knowledge.

3. Authorship

   All those who have made a significant contribution should be cited as authors. Other individuals who have minor contributions to the work should be acknowledged. Articles should include a full list of the current institutional affiliations of all authors, both academic and corporate. Information on financial support should be acknowledged by the authors.

   Before the accepted manuscript is published online, requests to add, remove, or rearrange author names must be sent to mids@wspc.com from the corresponding author of the accepted manuscript and must include: (i) the reason the name should be added or removed, or the author names rearranged; and (ii) a letter with signatures from all authors that they agree with the addition, removal or rearrangement. Online publication of the accepted manuscript is suspended until authorship has been agreed.

   After the accepted manuscript is published online, any requests to add, remove, or rearrange author names in an article will follow the same policies as detailed above and result in a corrigendum.

4. Plagiarism

   Reproducing text from other papers without properly crediting the source (plagiarism) or producing many papers with almost the same content by the same authors (self-plagiarism) is not acceptable. Authors must acknowledge the work of others used in their research and cite publications that have influenced the direction and course of their study. World Scientific is a member of CrossCheck/iThenticate. All manuscripts submitted will be checked for plagiarism and self-plagiarism using the CrossCheck database. Plagiarism is not tolerated. For more information about CrossCheck/iThenticate, please visit http://www.crossref.org/crosscheck.html.

5. Data Foul Play

   Fabrication, falsification or selective reporting of data with the intent to mislead or deceive is unethical, as is the theft of data or research results from others. The results of research should be recorded and maintained to allow for analysis and review. Following publication, the data should be retained for a reasonable period and made available upon request. Exceptions may be appropriate in certain circumstances in order to preserve privacy, to assure patent protection, or for similar reasons.

6. Previous Publication or Duplicate Submission

   Submitted manuscripts are considered with the understanding that they have not been published previously in print or electronic format (except in abstract or poster form) and are not under consideration in totality or in part by another publication or electronic medium. Simultaneous submissions of the same manuscript to different journals will not be tolerated. The submitted article will be removed without consideration.

7. Corrections and Retractions

   All authors have an obligation to inform the Journal to provide prompt retractions or correction of errors in published works.

   The Journal will issue retractions if:

   • there is clear evidence that the findings are unreliable, either as a result of misconduct (e.g. data fabrication) or honest error (e.g. miscalculation or experimental error)
   • the findings have previously been published elsewhere without proper cross-referencing, permission or justification (i.e. cases of redundant publication)
   • it constitutes plagiarism
   • it reports unethical research

   The Journal will issue errata if:

   • a small portion of an otherwise reliable publication proves to be incorrect (especially because of honest error)
   • the author list is incorrect (i.e. a deserving author has been omitted or somebody who does not meet authorship criteria has been included)