Why is this important? (Important Because)
From The Embassy of Good Science
A description to provide more focus to the theme/resource (max. 200 words)
- ⧼SA Foundation Data Type⧽: Text
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Editors play a special role in science, as they ultimately determine what gets published in their journals. We often say that editors are gate-keepers of science, because of their control over journal policies.'"`UNIQ--ref-00000007-QINU`"' Publishing new discoveries is important in science, and following established methods of control such as the peer-review process is necessary. Sometimes, having an undisclosed interest could influence editorial decisions or hinder the proper review of manuscripts. This could lead to a loss of confidence in science, which can be particularly harmful when science is publicly funded.'"`UNIQ--ref-00000008-QINU`"'
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There is concern that intellectual conflicts of interest may cause bias in research. The idea is that if researchers prefer one intervention over another, they will intentionally or unintentionally introduce bias into the design of the study, data analysis or data interpretation so that the results are in favor of the preferred intervention. However, there is not enough evidence on this. In psychotherapy research, it has been shown that researcher allegiance (i.e. intellectual conflicts of interest) is associated with study results: therapies with higher allegiance are shown to be more effective in randomized clinical trials.'"`UNIQ--ref-00000013-QINU`"''"`UNIQ--ref-00000014-QINU`"''"`UNIQ--ref-00000015-QINU`"' It is not clear, though, whether this correlation is causal. It could be that researchers have allegiance towards more effective interventions because they are effective, rather than that the interventions appear to be more effective because the researchers have an allegiance to them.'"`UNIQ--ref-00000016-QINU`"' Although some argue that the association between researcher allegiance and study results might be causal since the association exists even when there is evidence that two interventions are equally effective, the evidence remains inconclusive on how researcher allegiance/ intellectual conflicts of interest might affect study results.'"`UNIQ--ref-00000017-QINU`"'
At the same time, some argue that intellectual conflicts of interest are unavoidable.'"`UNIQ--ref-00000018-QINU`"' Researchers will have a certain educational background, prior research experience, and personal and professional affiliations, which will naturally make them more likely to favor one research outcome over another.'"`UNIQ--ref-00000019-QINU`"' Not only is this unavoidable, but it is what drives science forward: researchers would not spend years researching a topic that they did not feel passionate about. It is precisely the passion and intellectual interest that researchers have that inspires them to delve into research.
'''What conclusions can we make?'''
If intellectual conflicts of interest lead researchers to introduce systematic biases into their research (e.g. selection bias, reporting bias, etc.), then they can be said to be problematic.'"`UNIQ--ref-0000001A-QINU`"' More evidence is needed to establish whether this is the case. However, if intellectual conflicts of interest do not lead to systematic bias, it is hard to argue that they are problematic even if they do affect study results.'"`UNIQ--ref-0000001B-QINU`"' For example, if researchers that prefer intervention A are more likely to have results that favor intervention A even in the absence of systematic bias, it could be that:
1) they are better trained in intervention A than other researchers, or
2) they know more about intervention A than other researchers , or
3) they carry out intervention A more diligently than other researchers.
It would be difficult to argue that possibilities 1, 2 or 3 are problematic. Innovation in science is driven by passionate researchers who develop and propose new hypotheses, which they often strongly believe in. It makes sense that if these passionate researchers who know more about the hypotheses than others are not able to show their truthfulness, then no one else will be able to, indicating that the hypotheses are not correct. Yet, if the innovative researchers are able to provide evidence on the truthfulness of the hypotheses, the hypotheses remain open to a closer scrutiny by the rest of the scientific community.'"`UNIQ--ref-0000001C-QINU`"' Since science is a self-correcting process, it may not matter if the researcher with the intellectual conflict of interest is more likely to obtain study results in line with their allegiances. Other researchers with different allegiances will be able to scrutinize and test the results, thereby correcting for the intellectual conflict of interest.
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Delayed drug availability may affect research results. +
Correct attribution of research outputs is a central aspect of research integrity. However, identifying individual contributions can be difficult due to common names, name changes, inconsistent authorship practices, and long lists of collaborators. These issues can lead to misattribution, reduced visibility, or unfair recognition of work.
ORCID addresses these challenges by assigning a unique identifier to each researcher, ensuring that their work is accurately connected to them regardless of institutional affiliation or name variations. This improves transparency and accountability in research, while also supporting fair evaluation of academic performance.
In addition, ORCID simplifies administrative processes such as manuscript submission and grant applications, as researchers can reuse their verified profiles instead of repeatedly entering the same information. As its adoption grows, many publishers and funding bodies increasingly require ORCID identifiers, making it an essential tool in modern research practice. +
Children are a vulnerable population in research, as they cannot make participation decisions on their own. For this reason, informed consent from parents or legal caregivers is typically documented through a written, signed, and dated form. In pediatric research, informed consent ensures that parents or caregivers receive all relevant information and can voluntarily decide whether their child will participate. Failure to follow ethical standards can have legal, professional, and reputational consequences, particularly when data are not securely protected or informed consent procedures are ignored. Following proper ethical procedures, including informed consent, helps protect children and promotes responsible research practices. In all research involving children, maintaining the highest ethical standards is essential, regardless of the research context. +
Data protection is defined as a fundamental human right and using personal data raises significant ethics issues '"`UNIQ--ref-00000003-QINU`"'. Pseudonymisation and anonymisation are methods used to protect one's privacy and minimize the risk in the event of unauthorized access. Pseudonymised data are considered personal data and therefore are in the scope of GDPR, unlike irreversibly anonymised data which are no longer defined as personal data and are outside of the scope of GDPR '"`UNIQ--ref-00000004-QINU`"'
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Since research funders, organisations, reviewers, and individual researchers all have different needs from data management , DPMs are becoming integral parts of grant applications and research organisations.'"`UNIQ--ref-00000016-QINU`"' They are usually short, and state which data will be created and how. DMPs also define the plans for data sharing and presentation,'"`UNIQ--ref-00000017-QINU`"' prescribe how the data will be stored, who will have access to it, what documentation and metadata will be created with it, and how it will be preserved.'"`UNIQ--ref-00000018-QINU`"' Creating DMPs provides several benefits for researchers, such as reducing the loss of data, monitoring the research progress, and preparing data for future use. Apart from that, they are also time saving.'"`UNIQ--ref-00000019-QINU`"'
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While conducting our research we (as researchers) produce different kind of data: we write research designs and workflows, we collect raw data, we analyse them, we write about them. However, most of the time the only part of our research which is publicly shared is represented by the articles which we produce as a result of the entire research cycle. In fact, all phases of research could be of potential interest for other researchers, who could reuse the data we produce in a different way.
By maximizing access to and re-use of research data we can optimize the impact of the data that we produce. In line with the principles of Open Science, good data management becomes a fundamental instrument to promote and facilitate the reusability, accessibility and exploitation of research data, thereby allowing for the generation of new knowledge.'"`UNIQ--ref-00000002-QINU`"'
In 2014, a workshop named [https://www.lorentzcenter.nl/lc/web/2014/602/info.php3?wsid=602 ‘Jointly Designing a data FAIRPORT’] was organized in Leiden by a group of academic and private sector stakeholders. The aim of the workshop was to improve the infrastructure supporting humans and machines in the discovery and analysis of scientific data and their associated algorithms and workflows. A set of guidelines was developed by the participants to support data producers, scientists and data publishers to take full advantage of the generation of data.'"`UNIQ--ref-00000003-QINU`"' Four foundational principles were agreed by the community to allow stakeholders to discover, integrate, re-use and adequately cite the massive quantities of information being generated by contemporary data intensive science.
These foundational principles were subsequently improved, detailed and elaborated on by the [https://www.force11.org/group/fairgroup/fairprinciples FORCE 11] working group, which is still engaged in fostering the implementation and continued update of the FAIR principles. These foundational principles are known as FAIR principles, see below for specification of the principles. '"`UNIQ--ref-00000004-QINU`"'
==='''FAIR principles'''===
'''Findable:'''
#(Meta)data are assigned a globally unique and eternally persistent identifier.
#Data are described with rich metadata.
#(meta)data are registered or indexed in a searchable resource.
#Metadata specify the data identifier.
'''Accessible'''
#(meta)data are retrievable by their identifier using a standardized communications protocol.
#the protocol is open, free, and universally implementable.
#the protocol allows for an authentication and authorization procedure, where necessary.
#metadata are accessible, even when the data are no longer available.
'''Interoperable'''
#(meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
#(meta)data use vocabularies that follow FAIR principles.
#(meta)data include qualified references to other (meta)data.
'''Re-usable'''
#meta(data) have a plurality of accurate and relevant attributes.
#(meta)data are released with a clear and accessible data usage license.
#(meta)data are associated with their provenance.
#(meta)data meet domain-relevant community standards.
All researchers at all levels but also society as a whole can benefit from the implementation of FAIR data management. Granting access to data produced throughout the entire research cycle is also important on a global scale since it allows researchers who operate in countries with less developed research infrastructures to benefit from others scientists’ work.'"`UNIQ--ref-00000005-QINU`"'
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The first sequencing of the whole human genome in 2003 cost roughly $2.7 billion. Advances in whole genome scanning technologies have enabled commercial companies to make genomic information available to the end consumer at competitive prices. Consumers can now have access to commercial genotyping of their genome from direct-to-consumer testing companies. According to NHGRI-funded genome-sequencing groups, the cost to generate a high-quality 'draft' whole human genome sequence in mid-2015 was just above $4,000;by late in 2015, that figure had fallen below $1,500.
This changing of landscape and technologies in which GWAS takes place is likely to affect the problem of reporting of findings. Is it possible that the participants in GWAS will expect a feedback similar to the information provided by consumer genetics companies? +
After deciding what research data to keep for long-term preservation, researchers should select the right repository. There is a variety of repositories – those that are focused on a specific research area and those for general purpose.'"`UNIQ--ref-00000009-QINU`"' Funders, journals, and universities also have their own repositories.'"`UNIQ--ref-0000000A-QINU`"''"`UNIQ--ref-0000000B-QINU`"' Since there are more than 2,000 data repositories,'"`UNIQ--ref-0000000C-QINU`"' researchers should use certain principles and standards in their selection process. They should:
-check whether there are any funder requirements that may mandate which repository to use
-check with the journal they are submitting their paper to, because some journals keep a list of approved repositories they will accept or have specific policies on data archiving
-check for discipline specific repositories because they could be more suitable to their datasets and other researchers expect to find them there
-or deposit their data into a University repository.'"`UNIQ--ref-0000000D-QINU`"'
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Missing data are unavoidable in clinical trials. Frequently, complete cases analysis is used only including individuals with no missing data '"`UNIQ--ref-00000009-QINU`"'. However, that can generate bias and can lead to exclude several individuals, causing loss of precision and power '"`UNIQ--ref-0000000A-QINU`"'. The risk of bias from missing data depends on the cause '"`UNIQ--ref-0000000B-QINU`"':
Missing completely at random: There are no systematic differences between the missing values and the observed values.
Missing at random: Any systematic difference between the missing values and the observed values can be explained by differences in observed data.
Missing not at random: Systematic differences remain between the missing values and the observed values.
The determination of the type of missing values is difficult due to the nature of missing values '"`UNIQ--ref-0000000C-QINU`"'. Therefore, practical guidelines are needed to deal with missing data. +
Data access is extremely important for transparent modern science. The rising number of research studies impedes the filtering of research findings, aggravates peer-review process and increases the possibility of false study reports. Having in mind the direct implications of scientific findings on everyday practice, data availability is further prioritized. The ''open data movement'' follows the principles of transparency, participation, and collaboration (1). Open data policy is important because it nurtures the virtues of transparency and honesty, which allows each respondent to check the authenticity of the published results at any time. Data sharing represents a significant part of research ethics and nowadays, many journals require researchers to publish resources to make them available to other investigators (2,3). However, deposited published data may be incomplete, in some cases intentionally because authors could feel like losing priority in future publishing, which may complicate new analyses on previously published data (2).
In an effort to enhance data-sharing practices, some journals have mandatory data availability statement (DAS). However, according to a recent study on data availability statements, 93% of authors of manuscripts with DASs that stated authors are eager to share their data either didn't respond or refused to share their data. In conclusion, the level of compliance is disappointing even when the authors state in their article that they will share data upon request, indicating that the DAS may not be enough to guarantee data sharing (4). +
Not storing data properly and disregarding safeguards can lead to losing important research data. This does not occur rarely. A study carried out on 516 articles published from 1991 to 2011 has revealed that availability of research data in biology decreases about 17% per year.'"`UNIQ--ref-00000002-QINU`"' Various reasons can lead to unavailability of research data, whether researchers change their contact information and are not reachable anymore or they use outdated technology, such as floppy disks, to store their data.'"`UNIQ--ref-00000003-QINU`"' Apart from that, even when researchers are able to access their data, they often lose hours and hours searching for them in their computer files.'"`UNIQ--ref-00000004-QINU`"' Therefore, depositing data into repositories can save a considerable amount of time. There are several benefits for researchers who deposit their data into repositories:
-data is clustered together which enables easier and faster analysis and reporting
-potential problems are detected easier because repositories are categorised
-data is preserved and archived.'"`UNIQ--ref-00000005-QINU`"'
Overall, such practice promotes transparency in research and reduce misconduct.'"`UNIQ--ref-00000006-QINU`"' However, data repositories also have some downsides. For example, there is a possibility of a system crash that could affect the stored data, so it is important always to back up datasets.'"`UNIQ--ref-00000007-QINU`"'
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The integration of AI in research offers game-changing opportunities, such as accelerating discoveries, enhancing reproducibility, and processing huge datasets. However, it also brings significant ethical dilemmas. AI systems can be biased due to the data they are trained on, leading to skewed results. Misuse of AI, such as automated paper generation or data fabrication, undermines the integrity of scientific work. Additionally, tools like ChatGPT can generate text that blurs the line between legitimate use and misconduct, raising questions about plagiarism, authorship, and attribution.
Another critical concern is data privacy: the use of personal or sensitive data to train AI models can compromise participant confidentiality if not handled with care. Researchers may also face difficulties in understanding or explaining how AI models generate conclusions, which challenges transparency, accountability, and trust in scientific findings.
This topic is crucial as it emphasizes the need for responsible AI use that upholds ethical principles like honesty, fairness, and respect for participants and society. It encourages dialogue on setting guidelines for AI use in research to ensure that technological advancements do not compromise trust in science. +
Paper mills pose significant threats to the integrity and trustworthiness of academic research, and to the scholarly record. The possibility that hundreds, if not thousands, of ‘fake’ papers are published in academic journals seriously compromises the trust that scholars and the public have in published research. Paper mills also contribute to resource waste, as the investigation and retraction of fake papers is a costly and time consuming process for publishers. Moreover, more money could be wasted if fake papers are used to obtain funding for further research, and in the case of clinical research the health of patients may be put at risk.'"`UNIQ--ref-00000015-QINU`"'
Paper mills present a growing problem for the scientific community, with one estimate in 2022 suggesting that 2% of paper submissions across all scientific journals are likely to come from paper mills;in some subject areas, this figure is likely to be much higher .'"`UNIQ--ref-00000016-QINU`"' Estimates made using the Paper Mill Alarm indicate that the number of articles bearing a close textual similarity to paper mill products have been steadily rising since 2000.'"`UNIQ--ref-00000017-QINU`"' There is also concern that the proliferation of generative artificial intelligence (AI) tools will exacerbate this problem, by providing paper mills with the ability to generate new papers and avoid detection techniques at greater speed.'"`UNIQ--ref-00000018-QINU`"'
Paper mills can thrive because of the pressure for researchers to publish in order to advance their careers. Publication may be necessary to obtain their doctorate for example, or to be considered eligible for a promotion by their institution. For example, the Beijing municipal health authority had a policy in place as recently as 2021 requiring attending physicians in non-research roles to meet a minimum number of first-author publications in professional journals in order to gain promotion.'"`UNIQ--ref-00000019-QINU`"' In other cases, researchers may make use of paper mills to boost their chances of obtaining research funding when applying for a grant.'"`UNIQ--ref-0000001A-QINU`"'
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By not declaring COIs, reviewers undermine the transparancy and honesty of the application process. The role of reviewers and the process of reviewing grant applications differs greatly among RFOs. However, many RFOs stipulate the role of reviewers for internal (staff) members, invited external reviewers and appointed committee members. In all instances having a COI when reviewing a grant proposal needs to be declared +
Collaborations are essential to scientific progress, but should not undermine the independence of research. The Wellcome Trust, a UK based funder, does not for example fund any researchers that receive funding from the tobacco industry. They state “There is overwhelming evidence that tobacco damages the health of smokers and non-smoker” .'"`UNIQ--ref-00000018-QINU`"'The goals of industry (maximizing profit) and researchers (furthering knowledge) are often not aligned.'"`UNIQ--ref-00000019-QINU`"' There are a number of examples where the industry clearly interfered with scientific research to promote their own products. Industry stakeholders are known to have sponsered research to supress evidence showing the adverse effects of their products. For example, the tobacco industry funded research to show that second hand smoking was not harmful. '"`UNIQ--ref-0000001A-QINU`"' The sugar industry funded research to show the harmful effect of total fat, saturated fat and cholesterol were more harmful than sugar intake for causing coronary heart disease.'"`UNIQ--ref-0000001B-QINU`"' These are clear cases of intereference. There are also other ways in which industry sponsors affect research. Many systematic reviews and meta-analyses have shown that industry sponsored research has more favourable outcomes than non-industry sponsored research. This is also called the funding effect. However, some systematic reviews have also shown that there is little or no difference between industry sponsors and study outcomes.'"`UNIQ--ref-0000001C-QINU`"' Per discipline and type of research the “funder effect” may differ.
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Continuing education is essential for physicians navigating rapidly evolving medical knowledge, new therapies, and emerging technologies. However, high-quality CME is expensive, and many educational providers rely on pharmaceutical and device‑industry funding to sustain programs. This creates a structural tension: industry support can enhance educational reach, but it also risks shaping content, speaker selection, or topic emphasis in ways that align with commercial interests. (1) +
IP rights allow individuals or organizations to earn recognition or to benefit financially from their inventions.'"`UNIQ--ref-00000009-QINU`"' In addition, IP rights stimulate creativity and let innovations flourish.'"`UNIQ--ref-0000000A-QINU`"' Before the start of a research project, all stakeholders should make an agreement concerning ownership of IP rights. Research funding organizations and private companies are important stakeholders, when it comes to research that may result in development of intellectual property.
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RFOs want to ensure that the research projects they fund have a positive societal impact. In the most severe cases, research monitoring can result in the termination of project funding. Funders can monitor the allocation of finances, the quality of research, adherence to the research proposal, and whether laws, regulatory frameworks and contracts are upheld.
After the conclusion of a research project, a funder can have a follow-up period to assess the real-time impact of the research. In addition, RFO’s can perform regular Standard Evaluation Protocols (SEP’s). For example, in the Netherlands, all institutions receiving public funding are subject to a SEP every 6 years.'"`UNIQ--ref-00000008-QINU`"'
When a researcher wants to diverge from the research proposal, approval from the RFO needs to be sought. This often involves providing an explanation as to why the researcher wants to change the methodology.
According to research misconduct guidelines from the UK Research Integrity Office (UKRIO), when an allegation of misconduct is made to the organization performing the research, the RFO must be informed.'"`UNIQ--ref-00000009-QINU`"' Both the confidentiality of the whisteblower and the accused needs to be guaranteed when informing the RFO. In addition, allegations of research misconduct can be presented directly to the funding organization. RFOs should have guidelines in place to deal with allegations of misconduct involving their funded projects. In most instances, the funding organization will inform the research performing organization about the allegation, and the appropriate procedures will be started by the RPO (also see research misconduct). However, the person making the allegation may fear repercussions, and may wish to remain anonymous. The Wellcome Trust, a UK-based funding agency, states the following:'"`UNIQ--ref-0000000A-QINU`"'
“If an informant wishes to remain anonymous, this will be respected unless:
*there are overriding legal requirements that we reveal the identity of the informant
*it is impossible to maintain anonymity to conduct an investigation
*the informant subsequently agrees to relinquish anonymity.
The informant will be notified of any proposed change to their anonymity”
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