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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Science policies address areas such as basic research, development of new technologies, and facilitation in bringing technologies to the market. They steer science into areas of importance and interest to society. Policies are determined by sets of values or priorities that policy makers have. In an ideal world policy makers should address the greatest needs of the community through the application of science policies, however the world of politics is far from an ideal one. +
The 20<sup>th</sup> century history contains a wide spectrum of controversial and sensitive issues such as treaty violations, military occupations, collaboration with occupying forces, civil wars, religious persecutions, colonialism, war crimes, deportations, ethnic cleansing and the Holocaust, among others.'"`UNIQ--ref-0000001B-QINU`"'
Sensitive topics are those that are connected to exceptionally painful and tragic historical times and events. Examples of sensitive issues are the Holocaust, racism, treatment of Roma/Gypsies and refugees. Teaching about these events can renew old wounds and bring back painful memories.'"`UNIQ--ref-0000001C-QINU`"'
Controversial issues regard disagreements about what happened, why it happened and how significant is the event. Sometimes these disagreements are present only at the academic level, when two or more historians interpret the same evidence in different ways. For example, some historians argue and debate over the war guilt of the outbreak of World War I.'"`UNIQ--ref-0000001D-QINU`"' Other times, however, these issues divide groups, societies, whole nations and neighboring countries with regard to what occurred, why it occurred, who started it, who was right, who provides the best argument and who has been most selective with the evidence.'"`UNIQ--ref-0000001E-QINU`"' Teaching of such topics presents a great challenge particularly in societies that are divided ethnically, nationally or religiously,'"`UNIQ--ref-0000001F-QINU`"' such as Northern Ireland and Cyprus or in some countries from former Yugoslavia. There is no European country without its controversial and sensitive issues.'"`UNIQ--ref-00000020-QINU`"' Controversial topics can be also sensitive because they are disturbing, they challenge peoples’ loyalties and provoke their prejudices.'"`UNIQ--ref-00000021-QINU`"'
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Research data often contains personal characteristics, such as a name, location data, or physical, physiological, genetic or cultural features of a person. For these, the GDPR provides the following principles in [https://gdpr-info.eu/art-5-gdpr/ article 5]:
*"Data should be processed lawfully, fairly and in a transparent manner."
*"Data should be collected for specified, explicit and legitimate purposes and is not further processed in a manner that is incompatible with those purposes."
*"Data should be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed."
*"Data should be kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed. For scientific data, it is often recommended to use pseudonymization as a technique to further protect subject privacy. Long-term archiving for scientific purposes is allowed when in accordance to Article 89 of the GDPR."
*"Data should be processed in a manner that ensures appropriate security of the personal data, including protection against unauthorised or unlawful processing and against accidental loss." +
Whistleblower protection affects not only researchers (including undergraduate, postgraduate and PhD students), but regulatory bodies, university administrators, research technicians, resource suppliers, funding bodies, editors, research ethics committees, research integrity officers and any other individuals and groups that may be indirectly involved in conducting research. +
Ever since its invention, the Internet has become an omnipresent part of everyday communication. It has become common in science to share your articles via Twitter, LinkedIn or Facebook. Measuring that part of online impact is important as it offers different insights into popularity and use of published articles. +
The Eigenfactor metrics, developed in 2007 by Carl Bergstrom and Jevin West,'"`UNIQ--ref-00000023-QINU`"' measures the number of times articles from the journals published in the past five years have been cited in Thompson Scientific’s Journal Citation Reports (JCR).'"`UNIQ--ref-00000024-QINU`"''"`UNIQ--ref-00000025-QINU`"' It considers which journals have contributed to these citations,'"`UNIQ--ref-00000026-QINU`"' therefore this approach identifies the most influential journals, those which are cited by other influential journals.'"`UNIQ--ref-00000027-QINU`"''"`UNIQ--ref-00000028-QINU`"''"`UNIQ--ref-00000029-QINU`"''"`UNIQ--ref-0000002A-QINU`"'
Unlike the IF, the Eigenfactor Score counts citations to journals in social sciences and humanities as well, and it eliminates self-citations.'"`UNIQ--ref-0000002B-QINU`"''"`UNIQ--ref-0000002C-QINU`"''"`UNIQ--ref-0000002D-QINU`"' It considers citations in the period of five years, in contrast to the IF’s number of citations over a two-year window.'"`UNIQ--ref-0000002E-QINU`"' This difference impacts fields where it takes longer for articles to receive citations.'"`UNIQ--ref-0000002F-QINU`"' For example, the average article in leading cell biology journal can receive 10 to 30 citations in two years, whereas the average article in leading mathematics journal can receive 2 citations in the same time scale. Using the entire citation network, the algorithm takes into account these differences and enables better and more accurate comparison of different research areas.'"`UNIQ--ref-00000030-QINU`"'
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The h-index was partially introduced as an improvement over simply counting the quantity of a researcher’s publications. A researcher with 10 publications may have a higher h-index than a researcher with 100 publications.
However, as with any other metric, it is possible to ‘game’, or artificially increase, one’s h-index. Some well-established strategies include:
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*Self-citation (cf. Italian scientists increase self-citations in response to promotion policy '"`UNIQ--ref-00000006-QINU`"'
*Honorary authorship (putting a distinguished researcher on an authorship list often increases citation)
*Publishing on ‘hot topics’
*Writing review papers (often more cited than original studies)
Any aspect of citation bias can be taken advantage of for improving h-index.
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Impact factors are important because they provide an indication of quality of a scientific journal. The idea is that journals with higher IFs are read more frequently, have more of an impact within a field, and are of higher quality. They are also important because some academic institutions ask for publications in journals with high IFs for acquiring a PhD or advancement.'"`UNIQ--ref-00000003-QINU`"' Journal IFs are calculated each year by Clarivate (former Thomson Scientific or Thomson Reuters) and published on Journal Citation Reports platform.
Impact factors, however, can be manipulated. Examples of practices that influence IF are self and cartel citations, limitations of citable items, acceptance of certain types of publications.'"`UNIQ--ref-00000004-QINU`"' Self-citation is a practice of citing one’s own work, to artificially increase a number of citations. Citation cartel is a practice of mutual citing between journals to increase their IF.'"`UNIQ--ref-00000005-QINU`"' Editors can also insist that newly submitted manuscripts cite some of the works already published in that journal. Journals can limit a number of citable items, and not include them in the IF analysis. For example, letter to editor is a type of publication that is often referenced, and journals get the citation. However, that type of publication is not considered a scholarly item and it is therefore not included in the IF formula, thus increasing the IF. Journals can also choose to accept more review articles, which are often cited more, and can increase their IF that way.
It’s also important to note that it takes at least three years to calculate IF of the journal, and IF cannot be calculated for new journals. Because of all this, IF should be used cautiously when determining the quality of a journal, and other bibliometric data should be considered before making the final decision.'"`UNIQ--ref-00000006-QINU`"''"`UNIQ--ref-00000007-QINU`"'
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Although online publication dates back to the mid-1990s, a journal’s IF is calculated based on print publication. Articles are available in electronic form prior to their print publication and the time between is called “online-to-print lag”.'"`UNIQ--ref-00000010-QINU`"' This lag is short for some articles, but it can prolong for months or even years for others.'"`UNIQ--ref-00000011-QINU`"' Since papers available online can be cited immediately and impact factor calculation is based upon their publication in print, this time frame between gives them a greater chance of being cited in the 2-year window compared to articles with no online-to-print lag.'"`UNIQ--ref-00000012-QINU`"' Also, an article published online at the end of a year can be published in print in the next year.'"`UNIQ--ref-00000013-QINU`"' For instance, if a paper is published online in December 2019 and in print in January 2020, one author may cite the paper as being published in 2019 and another in 2020.'"`UNIQ--ref-00000014-QINU`"' Longer online exposure before the beginning of the citation counting can lead to a higher number of citations, which means online-to-print lags might artificially increase journals’ IFs.'"`UNIQ--ref-00000015-QINU`"''"`UNIQ--ref-00000016-QINU`"''"`UNIQ--ref-00000017-QINU`"''"`UNIQ--ref-00000018-QINU`"' +
This bibliometric indicator is criteria when it comes to ranking of scientific journals based on quality. There are many journals which are indexed only on Scopus and can be validated by using SJR, as Impact factor (IF) considers only ISI Web of Science data '"`UNIQ--ref-0000000D-QINU`"''"`UNIQ--ref-0000000E-QINU`"'. Both Web of Science and Scopus database use basically same model of clasification which commites on two levels, first one would be a number of areas and second one subject categories '"`UNIQ--ref-0000000F-QINU`"'. Improvements regarding SJR towards IF are that SJR counts citations in a given year to documents in 3-year publication window, every citation is not of equal value meaning that citations cited by more prestigious journals have more influence, last but not the least would be that Scopus is bigger database than Web of Sciences thus it takes into acocunt more journals '"`UNIQ--ref-00000010-QINU`"'. Meaning that this database ensures not only mesaurament of popularity or impact of certain journal, bit it rather takes into acocunt the prestige of journal and the prestige of the citing journal as well. Another great advantage of this database is that it is free of any charge '"`UNIQ--ref-00000011-QINU`"'.
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Fabricating data is to be discouraged and should be prevented across all scientific disciplines.'"`UNIQ--ref-00000008-QINU`"' Next to falsification and plagiarism, fabrication is seen as one of the most serious forms of research misconduct. It is estimated that 2% of researchers have falsified or fabricated data throughout their careers.'"`UNIQ--ref-00000009-QINU`"' Fabrication of data differs from falsification, as the latter concerns distorting data, where the former is inventing and reporting made up data. Such data can range from making up research participants, creating false laboratory results or writing down invented observations.
The validity of knowledge created by science and the credibility of science;truth and trust, are undermined by fabrication. When detected, the sanctions for perpetrators can be severe and articles will be retracted. Not only does fabrication affect scientific careers, but when fabricated data is presented to be real and is consequently used in real-life practice it can have life-threatening consequences. One case of research misconduct estimates that up to 800,000 lives were lost due to fabrication of data of a single perpetrator.'"`UNIQ--ref-0000000A-QINU`"'
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Falsifying data is a serious form of research misconduct. Falsified data includes omitting or adding data points, removing outliers in a dataset and manipulating images. Image manipulation is a special form of falsifcation, as it uses software to edit photos, usually of laboratory tests, to let the results appear more convincing. This concerns blots, gels, micrographs and radiological images.'"`UNIQ--ref-00000002-QINU`"' Fabricating data is making up non-existing results, where falsifying data is to edit, add, remove or alter results and/or data sets. Falsified results, when detected, lead to sanctions for the perpetrator. Sanctions include retractions of papers, and often the end of a career in research. Falsification of data is to be discouraged and prevented.
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Plagiarism denies authors the credit for their work, but it also gives the perpetrator unfair advantage over peers in terms of publications, researcher evaluations and career progression. It particularly violates the principle of honesty which is integral to research integrity.'"`UNIQ--ref-00000009-QINU`"' Plagiarism is often described as a type of research misconduct which should be prevented and sanctioned in research integrity codes of conduct, statements and declarations. The Singapore Statement on Research Integrity states that “Researchers should report to the appropriate authorities any suspected research misconduct, including fabrication, falsification or plagiarism, and other irresponsible research practices that undermine the trustworthiness of research”. '"`UNIQ--ref-0000000A-QINU`"' Clearly, plagiarism involves deception. However, some have argued, in terms of ‘scientific integrity’, it might be less serious than fabrication and falsification and even some of the less frequently sanctioned ‘questionable research practices’. '"`UNIQ--ref-0000000B-QINU`"' '"`UNIQ--ref-0000000C-QINU`"'
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The integration of artificial intelligence into neurotechnology research introduces ethical challenges that extend beyond traditional biomedical frameworks. Unlike other forms of health data, neural data may reveal sensitive information about thoughts, intentions, or emotional states, raising concerns about privacy, autonomy, and data governance. The involvement of private companies in developing and testing these technologies may also affect research transparency, participant protection, and the management of conflicts of interest. Furthermore, uncertainties regarding long-term safety and the potential use of such devices for cognitive enhancement complicate the process of obtaining truly informed consent from research participants. Addressing these issues is essential to ensure that innovation in neurotechnology does not compromise fundamental ethical standards in human subjects research. +
Peer review is an important part of scientific process, because it identifies both quality and possible flaws in submitted research, and offers room for improvement. However, the peer review process is not perfect, and is susceptible to a number of conflicts, dilemmas and insecurities. '"`UNIQ--ref-00000002-QINU`"''"`UNIQ--ref-00000003-QINU`"'
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Today, research integrity training is implemented in the curriculum of many doctoral schools as an obligatory part of postgraduate education. Alternatively, it is provided by independent research integrity bodies. Either way, the courses have the same important goal, and that is to teach young researchers how to adhere to research integrity practices and avoid involvement in research misconduct. Training on research integrity provides PhD students with knowledge of the principles of good research practice and how to foster them in their research work. Much emphasis is put on research misconduct, both on serious violations (fabrication, falsification and plagiarism), and detrimental research practices.'"`UNIQ--ref-00000008-QINU`"' Besides the theoretical part, trainings also educate on practices of a more administrative nature, e.g., how to apply to obtain ethics committee approval or how to report a case of research misconduct.
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Specific disciplines deal with different problems concerning research integrity and research ethics. For instance, a physicist might have different concerns to a statistician or a researcher in a hospital. As universities have different faculties, often reflecting specific disciplines, research integrity training is often given per discipline. One study looked into the specific differences of doctoral courses on research integrity ('"`UNIQ--ref-00000002-QINU`"'). The main lesson learned from this study concerns the variation of the “problem narrative” underpinning the different courses.
These problem narratives frame the way the research integrity is presented, and also the way that the roles of the doctoral students are articulated.
*In the '''Health Faculty''', for instance, the course was based on the idea that researchers are inherently ‘small cheaters’ who individually have to navigate an inimical culture;a problem narrative that was reproduced in the pedagogical design and the didactical choices made by the course teachers.
*In the '''Social Sciences Faculty''', the problem narrative of the “broken system” was emphasized, where the doctoral students were caught between incentivizing and promotion systems which incentivize questionable practices and a scientific system with inherent biases and poor practices.
*In the '''Humanities Faculty''', ethical dilemmas were accepted as part of scientific practice.
*In the '''Natural Sciences Faculty''', the disciplinary field was thought to be fundamentally sound, and research integrity training merely served to provide early career academics with the research practices and techniques to maintain and strengthen this field of science.
Despite these different problematizations, the solutions that were promoted in the courses were surprisingly similar. While participants were informed about the institutional support that was available, all the courses (explicitly and implicitly) highlighted the responsibility of individuals and research groups for acting with integrity in their own local practice. All the courses used casework and group discussions to focus on everyday dilemmas in the belief that through ‘reflexivity’ participants would be empowered to act responsibly, even when surrounded by ‘small cheaters’ and dealing with structural pressures from an increasingly competitive research environment.
The study suggests that a common trait of the doctoral courses is to responsibilize the early career researchers, while not necessarily giving them the tools necessary to carry this responsibility. The concept of the varying problem narratives emerging from this study is a key insight which might be very valuable in the design of future training activities. Teachers and course leaders are very influential in framing the courses, based on their own conceptions of the “problem of research integrity”. These problem narratives might be based on disciplinary differences, but they may also be influenced by the background of the course leaders and teachers, their own experiences with research integrity or research cultures, and it is vital that course leaders reflect on these problem narratives and how they shape the training activities.
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Supervisors are usually swamped with obligations in the academic world, or with their own reserach projects. They do not have enough time to properly supervise students, or are too tired to do so. Moreover, after supervising a number of students during theses writing/research projects, supervisors take their role for granted and disregard active participation in the supervision process.
However, openeness and honesty in communication should be a priority in the supervision process. Supervision can have a significant impact on the development of virtues in students.'"`UNIQ--ref-00000003-QINU`"' Proper scientific communication can also impact the career development of the supervised student/researcher.'"`UNIQ--ref-00000004-QINU`"' Reserachers have stressed the need for the training of supervisors, and the construction of guidelines for supervisors as a key topic for the 2021-2027 Horizon Europe level.'"`UNIQ--ref-00000005-QINU`"' Ensuring proper communication and approachability can create a better environment for students/early career researchers to develop virtues needed for responsible and ethical research. +
Academic research has a long tradition of master-apprentice relationships, where the apprentice (here: junior researcher) learns the fine skills of the trade (here: research) through the extensive supervision of a master (here: senior researcher). The more one grows in an academic career, the more likely a researcher is to supervise junior researchers (often PhD candidates).
Responsible supervision involves two main things. On the one hand, the supervisor should model responsible research, so that junior researchers are naturally socialized into responsible research practices. This could involve a variety of things: from assuring that the junior researcher is involved in good data management from the start of the project, to an open and timely conversation about (co-) authorship.
On the other hand, responsible supervision involves creating a safe learning climate for junior researchers to learn. The idea here is that if the learning climate is not safe, junior researchers may lack the space and confidence to share their concerns about the interpretation of the data, the planning of a particular research project, or the limitations of their capacity. Hence, if no safe professional relationship exists, certain doubts, concerns or limitations may remain under the radar, ultimately slowing down academic research. +
To be a good researcher, it is not enough just to know rules and codes of conduct of RCR. It is important to learn how to adapt and respond to real life situations. In order to respond ethically, you need to develop skills to recognize the right course of action and the values that will lead you to choose them. This is why many people stress the importance of virtues and virtue ethics in RCR education.'"`UNIQ--ref-00000003-QINU`"''"`UNIQ--ref-00000004-QINU`"' Serious games simulate real life situations and require that players respond to them. They are similar to case based and role play education, but also significantly different. In gaming, there is no room to escape or hide behind the more extroverted members of the group. Here, the player is put into the center and has to reach a decision on his or her own.
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