Individual Scientists Research Articles

ESTATES AS PLACES OF POWER

Book Review: The estate and the dacha in the literature of the Soviet era: losses and acquisitions: collective monograph; comp. O.A. Bogdanova; ed. by V.G. Andreeva, O.A. Bogdanova. Moscow, IWL RAS Publ., 2024, 672 p. (Russian Estate in the World Context; issue 8) The object of the review is the eighth issue of the book series “Russian Estate in the World Context”, the collective monograph “Estate and Dacha in the Literature of the Soviet Era: Losses and Gains” (2024). Project manager about the estate, Doctor of Philology O.A. Bogdanova and other prominent scientists, using material from a large number of writers, explore the metamorphosis of the estate text in Soviet times. The author of the review notes the integrity of the concept, the unified style with the brightness of the idiostyles of individual scientists (the reviewer pays special attention to their points of view) and the overall high analytical level of the monograph. The estate text of the Soviet era, for the first time comprehensively studied in this publication, appears as different open facets – it is part of the “garden city” as a development of the locus of the noble estate, and a rhetorical cluster of meanings, and a place for a “journey around the house”, and a regional estate as a place concentration of cultural forces, and, most importantly, the degeneration in the post-estate world of the estate into a dacha, so poeticized by B.L. Pasternak. The reviewer draws attention to the fact that the collective monograph provides materials for compiling an anthology of excerpts from world estate texts.

Promising the earth: Forms of capital promised and pursued in Australian-Chinese research collaborations

Science is a space of both collaboration and competition, illustrated by international research collaboration (IRC) and its advantages for individual countries, institutions and scientists. IRC also brings together countries positioned unequally in global epistemic hierarchies. Little is known about how scientists navigate these tensions within IRC. We explore this through a study of Australian–Chinese IRC, drawing on interviews with Australian scientists and Bourdieu's theoretical framework. We identify specific capitals that are sought and promised in Australian–Chinese IRC, namely, scientific, economic and ‘environmental’ capital, with successful collaboration depending also on social and cultural capital. Differences in how Australia and China are positioned in global academic and scientific fields, and differences between national scientific fields, mean that collaboration facilitates access to forms of capital unobtainable in scientists’ home settings. Because the benefits of IRC are fundamentally relational and promissory, these will change alongside the global hierarchies that are, themselves, being reshaped by IRC.

Gender differences in the patterns and consequences of changing research directions in scientific careers

Abstract Changes of research direction in scientific careers are related to the so-called “essential tension” between the exploration of new knowledge and the exploitation of established knowledge in research and innovation. Changes of research direction are thereby assumed to influence the evolution of science in general. Research has shown that such changes may also affect the success of individual scientists in their careers. However, the gender dimension of this aspect of career development is so far understudied. There is also a need for more dynamic indicators to record and interpret career developments in macro data. This study combines the gender perspective with the introduction of new indicators. We selected more than 29,000 scientists in Physics & Astronomy and studied them over six decades using a bibliographic data set from Scopus. We find that women are less likely to change research direction than their men counterparts, and that the research performance of women is less negatively affected by changing research direction. We discuss the policy implications of these findings as well as the methodological advancement related to the new indicators of career development.

Big Science: before and after the Manhattan Project

Abstract Although the concept of Big Science is not well defined, it is often identified with expensive and government-funded post-World-War II projects in physics and space research. However, this definition is too narrow both with regard to chronology and with regard to the sciences in question. Apart from offering some general comments on the notion of Big Science this paper adopts a historical perspective by singling out a few cases of pre-twentieth century Big Science projects in physics and astronomy. These were exceptions, however, and it was only with the Manhattan Project and the early generations of high-energy accelerators that the Big Science era truly started. As argued the development involved new forms of organisation as well as new ethical problems relating to the role and responsibility of the individual scientist.

The Technopolitics of Agronomic Knowledge and Tropical(izing) Vegetables in Brazil

This article critically analyzes the social and political factors behind the advancement of technoscientific development in modern Brazilian agriculture. In the second half of the 20th century, Brazil underwent a rapid industrialization in the agricultural sector by more than doubling productivity in key global commodities and a widespread migration of people from rural to urban areas. Most observers point to the Brazilian Agricultural Research Corporation (Embrapa) as the technological engine that drove the industrialization of Brazilian agriculture. Existing approaches to analyze technoscientific development tend to overlook the role of the environment and individual scientists in enacting change. I argue that, especially in the case of agriculture, technoscientific development hinges on the extent to which the environment is disregarded or embraced by those who have the institutional support and capacity to innovate. To support my argument, I draw on two contrasting cases of crop development spearheaded by Embrapa scientists: the tropicalization of the carrot and participatory research on non-conventional vegetables. Through those two cases, the article demonstrates how the general and specific, the transnational and local, and the industrial and agroecological are all key contrasting factors for understanding technoscientific development in agriculture. This research is based on extensive interviews and participant observation at Embrapa’s vegetable research center near Brasilia, Brazil.

The Collective Responsibilities of Science: Toward a Normative Framework

Abstract Scientists have the epistemic responsibility of producing knowledge. They also have the social responsibility of aligning their research with the needs and values of various societal stakeholders. Individual scientists may be left with no guidance on how to prioritize and carry these different responsibilities. As I will argue, however, the responsibilities of science can be harmonized at the collective level. Drawing from debates in moral philosophy, I will propose a theory of the collective responsibilities of science that accounts for the internal diversity of research groups and for their different responsibilities.

Quantifying attrition in science: a cohort-based, longitudinal study of scientists in 38 OECD countries

AbstractIn this paper, we explore how members of the scientific community leave academic science and how attrition (defined as ceasing to publish) differs across genders, academic disciplines, and over time. Our approach is cohort-based and longitudinal: We track individual male and female scientists over time and quantify the phenomenon traditionally referred to as “leaving science.” Using publication metadata from Scopus—a global bibliometric database of publications and citations—we follow the details of the publishing careers of scientists from 38 OECD countries who started publishing in 2000 (N = 142,776) and 2010 (N = 232,843). Our study is restricted to 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine), and we track the individual scholarly output of the two cohorts until 2022. We use survival analysis to compare attrition of men and women scientists. With more women in science and more women within cohorts, attrition is becoming ever less gendered. In addition to the combined aggregated changes at the level of all STEMM disciplines, widely nuanced changes were found to occur at the discipline level and over time. Attrition in science means different things for men versus women depending on the discipline; moreover, it means different things for scientists from different cohorts entering the scientific workforce. Finally, global bibliometric datasets were tested in the current study, opening new opportunities to explore gender and disciplinary differences in attrition.

Vectors of Legal Interpretation Activity when Interpreting Contracts

Introduction: the official interpretation of the norms of law is one of the elements that support the efficiency of the mechanism of legal regulation in public relations. In the vast majority of cases, it is implemented in relation to the norms of the law, but its role is not limited to this area alone. The official interpretation of contracts has an independent significance in law, which, due to its lack of study, requires increased attention. Purpose: to consider specific areas of using the official interpretation of the law in interpreting the content of contracts, an attempt to systematize knowledge about contractual legal interpretation activity. Methods: the methodological framework for the study is a set of methods of scientific cognition, including systematicity, analysis, comparative law, and formal law. Results: the author’s position, substantiated in the work, on the possibility of identifying the vectors of legal interpretation activity in the interpretation of contracts is based on the work of individual scientists, the provisions of current legislation, interpretative acts of the supreme judicial authorities of the Russian Federation, and the results of law enforcement practice. Conclusions: as a result of the conducted research, it was found that specific independent and interrelated directions of official interpretation should be recognized as vectors, which are aimed at ensuring a clear understanding of the methods of concluding and executing contracts. It is advisable to consider them as some kind of starting point, landmarks that contribute to the systematization of all interpretative activities and characterize interpretation as a single production process. Their presence makes it possible to influence the contractual interpretation point-by-point and, if necessary, adjust the latter to the required extent. The list of vectors of legal interpretation activity in the interpretation of contracts is not exhaustive.

Scientists and scientific journals should adhere to ethical standards for the use and reporting of data from Indigenous people.

Internationally, governments and scientists are bound by legal and treaty rights when working with Indigenous nations. These rights include the right of Indigenous people to control the conduct of science with Indigenous nations. Unfortunately, in some cases, individual scientists and scientific teams working with biological and genetic data collected from Indigenous people have not respected these international rights. Here, we argue that the scientific community should understand and acknowledge the historical harms experienced by Indigenous people under the veil of scientific progress (truth) and implement existing standards for ethical conduct of research and sovereign control of data collected within Indigenous communities (reconciliation). Specifically, we outline the rationale for why scientists, scientific journals and research integrity and institutional review boards/ethics committees should adopt, and be held accountable for upholding, current international standards of Indigenous data sovereignty and ethical use of Indigenous biological samples.

Developing the Svalbard Integrated Arctic Earth Observing System (SIOS)

Abstract. Based on the ongoing large climatic and environmental changes and the history of science coordination in Svalbard leading to the development of Svalbard Integrated Arctic Earth Observing System (SIOS), we present an overview of the current gaps in knowledge and infrastructure based on a synthesis of the recommendations presented in the annual State of Environmental Science in Svalbard (SESS) reporting of SIOS. Recommendations from the first 4 years of SESS reporting represent the point of view of the wide scientific community operating the large observing system implemented in Svalbard (SIOS) since 2018 and aim to identify the scientific potential to further develop the observing system. The recommendations are bottom-up inputs for a continuous process that aims to accomplish the vision and mission of SIOS: optimizing, integrating and further developing the observing system in an Earth system science (ESS) perspective. The primary outcome of the synthesis work is the evidence that ESS in SIOS has, during the first 4 years of operation, naturally developed from individual scientists or smaller groups of scientists to larger disciplinary international groups of scientists working together within the different environments (the atmosphere, the cryosphere, and marine and terrestrial environments). It is clear that strategic efforts towards interdisciplinarity are necessary for operating fully at ESS scale in Svalbard. As Svalbard is experiencing the largest ongoing warming in the Arctic and worldwide, SIOS is in a unique position to perform a full-scale study of all processes impacting ESS dynamics and controlling the water cycle using all parts of the SIOS observation network, with a large potential for increasing the understanding of key mechanisms in the Earth system. We also identify the potential to upscale Svalbard-based observations collected in SIOS to pan-Arctic and global scales, contributing to full-scale ESS.

What drives public engagement by scientists? An Australian perspective

There is an increasing expectation for more scientists to engage with industry, government, and communities to solve climate change. A group for whom these calls are now prevalent are marine (natural and social) scientists working on environmental change, including climate change. Yet, there is limited empirical evidence of what drives them to embrace or avoid engaging distinct publics, including policymakers. Here, we examined via twenty-eight in-depth qualitative interviews factors affecting how Australian scientists engage the public about climate change. We found that nineteen contextual variables constrain and enable public engagement by scientists. These variables co-occur and interact at the individual, organizational, and systemic levels to affect how they prioritize, mobilize resources, and decide to engage the public. We found that while the scientists saw it rewarding to share their findings with others, they found it hard to deal with conflict, face skeptics, and navigate organizational politics and structures to engage others in a public-facing role. Also, a lack of institutional support and engagement culture, role ambiguity, unequal power relations, and a legacy of past encounters led many scientists to engage in tokenism. These findings and insights have implications for individual scientists, institutional policy, and the practice of engaging others about global environmental change. They reveal why scientists might not engage others in a public-facing role and what might be needed to transform engagement.

How an international research programme can contribute to improvements in the research environment: the perspective of doctoral students in sub-Saharan Africa

Background The Africa Capacity Building Initiative (ACBI) programme aimed to ‘strengthen the research and training capacity of higher education institutions and support the development of individual scientists in sub-Saharan Africa through UK-Africa research collaborations’ including by funding PhD studentships. We conducted research to understand students’ experiences and to see how consortia-based programmes such as ACBI and their own institutions can enhance PhD students’ research environment and progress. Methods In-depth interviews with 35 ACBI-funded PhD students explored their perspectives about how their research and personal development benefitted from belonging to a research consortium. Questionnaires were used to corroborate interview findings. Results Students recognised that membership of a research consortium provided many benefits compared to less well-resourced peers. By drawing on the programme and consortiums’ resources, they were often able to overcome some limitations in their own institution’s systems and facilities. Through their consortia they could access a wide range of international expertise and support from mentors and colleagues for their technical and psychosocial needs. Multiple consortia opportunities for engaging with the international scientific community and for networking, gave them confidence and motivation and enhanced their career prospects. Conclusion Our study and its recommendations highlight how the breadth and diversity of resources available to PhD students through research consortia can be harnessed to facilitate students’ progress and to create a supportive and conducive research environment. It also underlines how, through a multi-level approach, consortia can contribute to longer-term improvements in institutional research environments for PhD students.

Formation of Approaches to Determining the Social Effectiveness of Scientific Activity of Libraries

The problem of evaluating the effectiveness of scientific activity as applied to the humanitarian and library sphere is analyzed. Research conducted in libraries contributes to the development of libraries themselves, as well as to the study and disclosure of cultural heritage. The question of the effectiveness of the conducted research is of fundamental importance. An analysis of the evolution of approaches to the evaluation of effectiveness is presented. In the last quarter of the 20th century, the fundamental principle of scientific policy was the position “science is the direct productive force of society”, which focused on the implementation of the findings of research activities and the formation of ideas about the mandatory material form of the results. This attitude is not applicable in the social sciences and humanities. In the Soviet period, the task of practical connection of science with production for a long time established the position that any scientific result should be practically tangible and economically effective, and every research should end with a document containing certain conclusions and a list of measures, or with an act on the implementation of research results.Currently, to assess not only the performance of individual scientists and organizations, but also in the formation of public science policy, the use of scientometric methods — quantitative measurements of information characteristics of published results of scientific work — is widely used. However, the scientometric approach continues to be debated.In the last decade the theoretical problem of social effectiveness of science, which, unlike economic, is not direct and specific and difficult to measure, has been increasingly discussed. Research conducted in the field of scientific support of library development has been proven to have a pronounced impact on library work (e. g., in the form of developed concepts, strategies, programs, etc.). Research of historical and cultural character influences the formation of public and individual consciousness, value system and contributes to the solution of the most important strategic state tasks.Determining the social effectiveness of research activities of libraries is becoming increasingly important.

RADAR-Pipeline: Scalable Feature Generation for Mobile Health Data

Introduction & BackgroundRADAR-Pipeline is an open-source Python framework designed to simplify and enhance mobile health data analysis. It has been designed to efficiently read and process the large amount of data generated through the RADAR-Base platform. RADAR-base is a scalable, real-time streaming and analytics open-source platform to facilitate research access and customisation requirements. Studies using the Radar-base platform have collected fine-grained longitudinal data from wearables and phones. The data can potentially create multitudes of digital biomarkers, which can be used to inform us greatly about the disease condition. Due to the sheer size of the data, it can be difficult for researchers to read and process those data -- a common task is identifying useful features and common data processing/analysis steps previously used by the community. Up to now, these have been hand-crafted by individual data scientists, often lacking the capability to be easily reused by the community without author-specific knowledge. Furthermore, generating variables based on already established research on a larger scale can be challenging and could hinder replication. Hence, we have designed RADAR-Pipeline to help researchers overcome these challenges. It empowers them to create and share their data analysis and visualisation pipelines, fostering collaboration and knowledge sharing within the research community. Objectives & ApproachThe primary objective of RADAR-Pipeline is to offer researchers a user-friendly and powerful platform to develop and share their research. Researchers can build reusable analysis and visualisation pipelines to ensure consistent and reliable results. It simplifies big data analysis by leveraging Apache Spark to handle large and complex mobile health datasets efficiently. Researchers can also save time and effort by reusing and extending existing pipelines built by others. Finally, the RADAR-Pipeline promotes collaboration and recognition by allowing researchers to share their work through the RADAR-base Analytics Catalogue, making their pipelines citable and accessible to the wider research community. Whilst Radar-pipeline has been designed to read data from Radar-base, it can also be used to read data from any dataset which uses Hadoop Distributed File System (HDFS) file system namespace. Relevance to Digital FootprintsMobile health data is rich and valuable for understanding human behaviour and health. RADAR-Pipeline addresses the challenges associated with analysing large and complex mobile health datasets, enabling researchers to extract valuable insights that can be used to (1) Improve public health: By enabling efficient analysis of large-scale mobile health data, RADAR-Pipeline can contribute to research efforts aimed at improving population health outcomes and developing effective interventions; (2) Personalised healthcare: By facilitating the extraction of individual-level features from mobile health data, RADAR-Pipeline can seamlessly be integrated with Kafka data streams and machine learning pipelines to process the data in real-time, which can then be utilised to create more effective and targeted real-time interventions. (3) Promote reproducible research: The framework's emphasis on transparency and reproducibility in research aligns with the conference's focus on the responsible use of digital mobile health data. Conclusions & ImplicationsRADAR-Pipeline is a valuable tool for researchers, offering them the means to harness the potential of mobile health data. By adopting this framework, researchers can achieve efficient and scalable data analysis, thereby streamlining the extracting insights from digital footprints. This efficiency enables researchers to delve deeper into the data and uncover valuable patterns and trends. Furthermore, RADAR-Pipeline promotes collaboration and knowledge sharing within the research community. By providing a standardised framework for data analysis, RADAR-Pipeline facilitates collaboration among researchers, leading to the sharing of best practices and the dissemination of knowledge.

Reassessment of the Shirley and model functions within X-ray photoelectron spectroscopy analysis utilizing comprehensive search methodologies of Bayesian inference

The analysis of X-ray photoelectron spectra often faces challenges due to the lack of standardization in modeling approaches, background subtraction methods, and computational algorithms within the field of computer science. The interpretation of XPS data significantly relies on the unique expertise and judgment of individual researchers. Therefore, the objective of this study is to highlight the difficulties associated with analytical methods that depend heavily on the discretion of individual scientists, to elucidate the prevailing models and background subtraction techniques, and to suggest improvements to these methodologies. This endeavor aims to enhance the reliability and reproducibility of XPS analysis, thereby contributing to the advancement of research in this area. By utilizing the information criterion as part of a thorough search methodology in Bayesian inference, we show that our sophisticated analytical techniques significantly outperform others in the analysis of actual X-ray photoelectron spectroscopy (XPS) spectra. This improvement is evidenced through enhanced accuracy and reliability in spectral interpretation, underscoring the efficacy of our methods in practical applications of XPS.

Data-enhanced revealing of trends in Geoscience

Abstract Purpose This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences①. Design/methodology/approach The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists. Findings Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology. Research limitations The analyzed data of this study only contain those were included in the Web of Science. Practical implications This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study. Originality/value This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.

Input and Verification of Scientometric Data in Large, Complex Information Systems

For effective stimulation of the activities of organizations, collectives, and individual scientists in the field of scientific, research, experimental, design, and technological work, it is necessary to rely on up-to-date, comprehensive, and verified data on the results obtained from these activities. The article describes an approach to the organization of processes for input and multi-level verification of data into information-analytical scientometric systems used to support decision-making in scientific organizations.

Business Innovations and Digital Transformation: Trend, Comparative and Bibliometric Analysis

The rapid development of digital technologies, digital transformation, business innovation, and the emergence of such technologies as artificial intelligence, blockchain, the Internet of Things provides significant potential for transforming business processes and creating new innovative models. The trend analysis conducted in this article (using the Google Trends tool) around the world for 2009-2023 showed that public interest in “business innovation” was almost constant until 2021 (according to the GT Scale, it ranged from 0.25 to 0.5). After 2021, it increased (according to the GT Scale, it was more than 0.5). At the same time, public interest in “digital transformation” has significantly increased since 2014, reaching almost maximum values in 2020-2023 (0.75 – 1.00 on the GT Scale). This confirms a growing need in society to acquire new knowledge related to the ability of businesses to adapt to digital transformation, including through creating innovative developments. Unlike trend analysis, bibliometric and comparative analyses identify trends in developing interest in this topic not among ordinary citizens – users of the Google search platform ‒ but among scientists who publish the results of their research either in monographs or in authoritative peer-reviewed scientific journals indexed by leading scientometric databases. The comparative analysis conducted in the article using the Google Books Ngram Viewer (Google) tool, which displays the frequency of references to relevant terms in English-language books for 2009-2019 worldwide, showed similar trends: the persistence of scholars’ attention to business innovation, while their interest in digital transformation is growing: in 2009-2013 – a slight increase, in 2013-2019 ‒ a significant increase. In the bibliometric analysis, a five-level mechanism for limiting the research sample was applied: only English-language and most recent (for 2018-2022) scientific articles indexed by the Scopus database in the subject area of Business, Management and Accounting were subject to analysis. Based on these limitations, the research sample for the keyword “digital transformation” was reduced from 12131 to 1700 papers, and for “business innovation” from 865 to 70. The analysis of the published articles, their views and citations, carried out using the SciVal tool, fully confirmed the conclusions drawn from the trend and comparative analysis results. In terms of digital transformation, the leaders in terms of the number of papers and the number of views are Germany, Italy, the UK and the US; in terms of citations – the UK, Germany, the US, and in terms of individual scientists – Brazil and Germany. As for the topic of business innovation, the United States is the undisputed leader in all these parameters, followed by China and the United Kingdom. Some scientists from Germany and Spain also attract the attention of the academic community (in terms of views and citations). Changes in trends and research priorities in each of the studied topics were identified and described using SciVal (analysis of the reference dynamics to the top 50 keywords in articles for 2018-2023). For example, in 2023, compared to 2022, scientific interest in issues related to “value creation” (+61.5%), “incumbents” (+66.7%), “service economy” (+83.3%), “digital marketing” (+75.0%), and “design thinking” (+150.0%) increased the most. VOSviewer software made it possible to cluster the scientific work by thematic areas. The largest cluster on digital transformation relates this concept to small and medium-sized businesses and technologies, and the largest cluster on business innovation relates it to the development of small and medium-sized enterprises and the protection of property rights.

Cultural competence-based framework: A multilevel and multidimensional perspective on contemporary science culture

This article presents a cultural competence-based (CCB) framework to analyse contemporary science culture. Starting from the observation that two separate views of culture-as-context and culture-as-practice cannot address the ongoing transitions in the contemporary sciences towards esoteric–exoteric trans-sphere governance and multicultural science, we introduce key ideas from ‘older’ varieties of competence-based culture theories. We argue that a spectrum of cultural and sociocultural systems shapes contemporary science culture by being (un)supportive of individual scientists acquiring cultural competence and guiding scientists’ research practices. In contrast, individual scientists’ cultural competence shapes the fabrication of cultural and sociocultural systems through their scientific practices, thereby shaping contemporary science cultures. We also synthesize different concepts of science culture, reflect the transitions in contemporary sciences and construct three dimensions of the cultural system, sociocultural system and cultural competence from various elements. By providing a conceptual framework that contributes to a better understanding and management of contemporary science culture, we hope to enhance effective work ethics and fit-for-purpose science knowledge to address emerging ‘wicked’ societal challenges.

Citizen scientists—practices, observations, and experience

Citizen science has been studied intensively in recent years. Nonetheless, the voice of citizen scientists is often lost despite their altruistic and indispensable role. To remedy this deficiency, a survey on the overall experiences of citizen scientists was undertaken. Dimensions investigated include activities, open science concepts, and data practices. However, the study prioritizes knowledge and practices of data and data management. When a broad understanding of data is lacking, the ability to make informed decisions about consent and data sharing, for example, is compromised. Furthermore, the potential and impact of individual endeavors and collaborative projects are reduced. Findings indicate that understanding of data management principles is limited. Furthermore, an unawareness of common data and open science concepts was observed. It is concluded that appropriate training and a raised awareness of Responsible Research and Innovation concepts would benefit individual citizen scientists, their projects, and society.