Information sharing across institutions: Practices and barriers during public health emergencies in Ethiopia.

BACKGROUND: Rapid, integrated information exchange between stakeholders is critical for effective emergency preparedness and response. However, many low- and middle-income countries face barriers to seamless data sharing. While information accessibility is recognized as important for evidence-based decision-making and resource allocation in Ethiopia, factors influencing current health information sharing practices among stakeholders involved in public health emergency management programs are unclear. This study aims to examine multi-sectoral stakeholders' perspectives and experiences with health data sharing during emergencies in Ethiopia, to identify opportunities and challenges influencing practices to strengthen the national public health emergency response system. METHODS: A mixed-methods study was conducted between June and August 2023, involving a survey of 169 stakeholders actively involved in PHEM programs in Ethiopia as well as 23 in-depth interviews with key informants in senior leadership or advisory roles. The data was analyzed using descriptive statistics in SPSS and thematic analysis of qualitative transcripts. RESULTS: During emergencies, it was observed that data sharing between different entities occurred. Quantitative findings showed the predominant types of health data shared between stakeholders during emergencies included hospital data (109, 64.5 %), clinical case information, and laboratory results. Challenges limiting effective coordination included issues like limited functionality of digital health systems (75, 44 %), incompatible data formats (13, 34 %), and financial constraints (83, 49 %) and and socio-cultural barriers constrain current practices in Ethiopia. Qualitative interviews identified five themes around risk communication and inclusive alert systems. Experts emphasized tailored, multichannel outreach but noted infrastructure gaps and digital divides currently limit poorer communities' engagement. CONCLUSION: While collaborative health information exchange during emergencies is recognized as important, systemic, financial, and socio-cultural barriers constrain current practices in Ethiopia. Targeted strategies including capacity building, investment in integrated data infrastructure, economic optimization through innovative financing models, trust-based relationship development, and locally relevant communication channels informed by stakeholder perspectives can optimize information accessibility, coordination, quality, and equity of healthcare services during public health emergencies.

From code to care: Clinician and researcher perspectives on an optimal therapeutic web portal for acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML), a rapidly progressing cancer of the blood and bone marrow, is the most common and fatal type of adult leukemia. Therapeutic web portals have great potential to facilitate AML research advances and improve health outcomes by increasing the availability of data, the speed and reach of new knowledge, and the communication between researchers and clinicians in the field. However, there is a need for stakeholder research regarding their optimal features, utility, and implementation. METHODS: To better understand stakeholder perspectives regarding an ideal pan-Canadian web portal for AML research, semi-structured qualitative interviews were conducted with 17 clinicians, researchers, and clinician-researchers. Interview guides were inspired by De Laat's "fictive scripting", a method where experts are presented with scenarios about a future technology and asked questions about its implementation. Content analysis relied on an iterative process using themes extracted from both existing scientific literature and the data. RESULTS: Participants described potential benefits of an AML therapeutic portal including facilitating data-sharing, communication, and collaboration, and enhancing clinical trial matchmaking for patients, potentially based on their specific genomic profiles. There was enthusiasm about researcher, clinician, and clinician-researcher access, but some disagreement about the nature of potential patient access to the portal. Interviewees also discussed two key elements they believed to be vital to the uptake and thus success of a therapeutic AML web portal: credibility and user friendliness. Finally, sustainability, security and privacy concerns were also documented. CONCLUSIONS: This research adds to existing calls for digital platforms for researchers and clinicians to supplement extant modes of communication to streamline research and its dissemination, advance precision medicine, and ultimately improve patient prognosis and care. Findings are applicable to therapeutic web portals more generally, particularly in genomic and translational medicine, and will be of interest to portal end-users, developers, researchers, and policymakers.

Assessment of transparency indicators in space medicine.

Space medicine is a vital discipline with often time-intensive and costly projects and constrained opportunities for studying various elements such as space missions, astronauts, and simulated environments. Moreover, private interests gain increasing influence in this discipline. In scientific disciplines with these features, transparent and rigorous methods are essential. Here, we undertook an evaluation of transparency indicators in publications within the field of space medicine. A meta-epidemiological assessment of PubMed Central Open Access (PMC OA) eligible articles within the field of space medicine was performed for prevalence of code sharing, data sharing, pre-registration, conflicts of interest, and funding. Text mining was performed with the rtransparent text mining algorithms with manual validation of 200 random articles to obtain corrected estimates. Across 1215 included articles, 39 (3%) shared code, 258 (21%) shared data, 10 (1%) were registered, 110 (90%) contained a conflict-of-interest statement, and 1141 (93%) included a funding statement. After manual validation, the corrected estimates for code sharing, data sharing, and registration were 5%, 27%, and 1%, respectively. Data sharing was 32% when limited to original articles and highest in space/parabolic flights (46%). Overall, across space medicine we observed modest rates of data sharing, rare sharing of code and almost non-existent protocol registration. Enhancing transparency in space medicine research is imperative for safeguarding its scientific rigor and reproducibility.

Contents analysis of thyroid cancer-related information uploaded to YouTube by physicians in Korea: endorsing thyroid cancer screening, potentially leading to overdiagnosis.

BACKGROUND: Thyroid cancer overdiagnosis is a major public health issue in South Korea, which has the highest incidence rate. The accessibility of information through the Internet, particularly on YouTube, could potentially impact excessive screening. This study aimed to analyze the content of thyroid cancer-related YouTube videos, particularly those from 2016 onwards, to evaluate the potential spread of misinformation. METHODS: A total of 326 videos for analysis were collected using a video search protocol with the keyword "thyroid cancer" on YouTube. This study classified the selected YouTube videos as either provided by medical professionals or not and used topic clustering with LDA (latent dirichlet allocation), sentiment analysis with KoBERT (Korean bidirectional encoder representations from transformers), and reliability evaluation to analyze the content. The proportion of mentions of poor prognosis for thyroid cancer and the categorization of advertising content was also analyzed. RESULTS: Videos by medical professionals were categorized into 7 topics, with "Thyroid cancer is not a 'Good cancer'" being the most common. The number of videos opposing excessive thyroid cancer screening decreased gradually yearly. Videos advocating screening received more favorable comments from viewers than videos opposing excessive thyroid cancer screening. Patient experience videos were categorized into 6 topics, with the "Treatment process and after-treatment" being the most common. CONCLUSION: This study found that a significant proportion of videos uploaded by medical professionals on thyroid cancer endorse the practice, potentially leading to excessive treatments. The study highlights the need for medical professionals to provide high-quality and unbiased information on social media platforms to prevent the spread of medical misinformation and the need for criteria to judge the content and quality of online health information.

User Information Sharing and Hospital Website Privacy Policies.

Importance: Hospital websites frequently use tracking technologies that transfer user information to third parties. It is not known whether hospital websites include privacy policies that disclose relevant details regarding tracking. Objective: To determine whether hospital websites have accessible privacy policies and whether those policies contain key information related to third-party tracking. Design, Setting, and Participants: In this cross-sectional content analysis of website privacy policies of a nationally representative sample of nonfederal acute care hospitals, hospital websites were first measured to determine whether they included tracking technologies that transferred user information to third parties. Hospital website privacy policies were then identified using standardized searches. Policies were assessed for length and readability. Policy content was analyzed using a data abstraction form. Tracking measurement and privacy policy retrieval and analysis took place from November 2023 to January 2024. The prevalence of privacy policy characteristics was analyzed using standard descriptive statistics. Main Outcomes and Measures: The primary study outcome was the availability of a website privacy policy. Secondary outcomes were the length and readability of privacy policies and the inclusion of privacy policy content addressing user information collected by the website, potential uses of user information, third-party recipients of user information, and user rights regarding tracking and information collection. Results: Of 100 hospital websites, 96 (96.0%; 95% CI, 90.1%-98.9%) transferred user information to third parties. Privacy policies were found on 71 websites (71.0%; 95% CI, 61.6%-79.4%). Policies were a mean length of 2527 words (95% CI, 2058-2997 words) and were written at a mean grade level of 13.7 (95% CI, 13.4-14.1). Among 71 privacy policies, 69 (97.2%; 95% CI, 91.4%-99.5%) addressed types of user information automatically collected by the website, 70 (98.6%; 95% CI, 93.8%-99.9%) addressed how collected information would be used, 66 (93.0%; 95% CI, 85.3%-97.5%) addressed categories of third-party recipients of user information, and 40 (56.3%; 95% CI, 44.5%-67.7%) named specific third-party companies or services receiving user information. Conclusions and Relevance: In this cross-sectional study of hospital website privacy policies, a substantial number of hospital websites did not present users with adequate information about the privacy implications of website use, either because they lacked a privacy policy or had a privacy policy that contained limited content about third-party recipients of user information.

How Indigenous communities in New Zealand are protecting their data.

Concerns about the ethical use of data, privacy, and data harms are front of mind in many jurisdictions as regulators move to impose tighter controls on data privacy and protection, and the use of artificial intelligence (AI). Although efforts to hold corporations to account for their deployment of data and data-driven technologies have been largely welcomed by academics and civil society, there is a growing recognition of the limits to individual data rights, given the capacity of tech giants to link, surveil, target, and make inferences about groups. Questions about whether collective data rights exist, and how they can be recognized and protected, have provided fertile ground for researchers but have yet to penetrate the broader discourse on data rights and regulation.

What are the bottlenecks to health data sharing in Switzerland? An interview study.

BACKGROUND: While health data sharing for research purposes is strongly supported in principle, it can be challenging to implement in practice. Little is known about the actual bottlenecks to health data sharing in Switzerland. AIMS OF THE STUDY: This study aimed to assess the obstacles to Swiss health data sharing, including legal, ethical and logistical bottlenecks. METHODS: We identified 37 key stakeholders in data sharing via the Swiss Personalised Health Network ecosystem, defined as being an expert on sharing sensitive health data for research purposes at a Swiss university hospital (or a Swiss disease cohort) or being a stakeholder in data sharing at a public or private institution that uses such data. We conducted semi-structured interviews, which were transcribed, translated when necessary, and de-identified. The entire research team discussed the transcripts and notes taken during each interview before an inductive coding process occurred. RESULTS: Eleven semi-structured interviews were conducted (primarily in English) with 17 individuals representing lawyers, data protection officers, ethics committee members, scientists, project managers, bioinformaticians, clinical trials unit members, and biobank stakeholders. Most respondents felt that it was not the actual data transfer that was the bottleneck but rather the processes and systems around it, which were considered time-intensive and confusing. The templates developed by the Swiss Personalised Health Network and the Swiss General Consent process were generally felt to have streamlined processes significantly. However, these logistics and data quality issues remain practical bottlenecks in Swiss health data sharing. Areas of legal uncertainty include privacy laws when sharing data internationally, questions of "who owns the data", inconsistencies created because the Swiss general consent is perceived as being implemented differently across different institutions, and definitions and operationalisation of anonymisation and pseudo-anonymisation. Many participants desired to create a "culture of data sharing" and to recognise that data sharing is a process with many steps, not an event, that requires sustainability efforts and personnel. Some participants also stressed a desire to move away from data sharing and the current privacy focus towards processes that facilitate data access. CONCLUSIONS: Facilitating a data access culture in Switzerland may require legal clarifications, further education about the process and resources to support data sharing, and further investment in sustainable infrastructureby funders and institutions.

Agricultural education in Africa using YouTube multilingual animations: A retrospective feasibility study assessing costs to reach language-diverse populations.

There is a critical need for widespread information dissemination of agricultural best practices in Africa. Literacy, language and resource barriers often impede such information dissemination. Culturally and linguistically localized, computer-animated training videos placed on YouTube and promoted through paid advertising is a potential tool to help overcome these barriers. The goal of this study is to assess the feasibility of reaching language-diverse populations in Africa using this new type of information dissemination channel. As a case study, cost estimates were obtained for YouTube ad campaigns of a video to prevent post-harvest loss through safe food storage using sanitized jerrycan containers. Seventy-three video variants were created for the most common 16 languages in Ghana, 35 languages in Kenya, and 22 languages in Nigeria. Using these videos, campaigns were deployed country wide or focused on zones of influence that represent economically underdeveloped regions known to produce beans suitable for jerrycan storage. Using data collected from YouTube ad campaigns, language-specific models were created for each country to estimate how many viewers could be reached per US dollar spent. Separate models were created to estimate the number of viewers who watched 25% and 75% of the video (most of video without end credits), reflecting different levels of engagement. For language campaigns with both country wide and zone of influence areas of deployment, separate region-specific models were created. Models showed that the estimated number of viewers per dollar spent varied considerably amongst countries and languages. On average, the expected number of viewers per dollar spent were 1.8 (Range = 0.2-7.3) for 25% watched and 0.8 (Range = 0.1-3.2) for 75% watched in Ghana, 1.2 (0.2-4.8) for 25% watched and 0.5 (Range = 0.1-2.0) for 75% watched in Kenya, and 0.4 (Range = 0.2-1.3) for 25% watched and 0.2 (Range = 0.1-0.5) for 75% watched in Nigeria. English versions of the video were the most cost-effective in reaching viewers in Ghana and Nigeria. In Kenya, English language campaigns ranked 28 (country wide) and 36 (zones of influence) out of 37 analyzed campaigns. Results also showed that many local language campaigns performed well, opening the possibility that targeted knowledge dissemination on topics of importance to local populations, is potentially cost effective. In addition, such targeted information dissemination appears feasible, even during regional and global crises when in-person training may not be possible. In summary, leveraging multilingual computer-animations and digital platforms such as YouTube shows promise for conducting large-scale agricultural education campaigns. The findings of the current study provides the justification to pursue a more rigorous prospective study to verify the efficacy of knowledge exchange and societal impact through this form of information dissemination channel.

Now Is the Time to Strengthen Government-Academic Data Infrastructures to Jump-Start Future Public Health Crisis Response.

During public health crises, the significance of rapid data sharing cannot be overstated. In attempts to accelerate COVID-19 pandemic responses, discussions within society and scholarly research have focused on data sharing among health care providers, across government departments at different levels, and on an international scale. A lesser-addressed yet equally important approach to sharing data during the COVID-19 pandemic and other crises involves cross-sector collaboration between government entities and academic researchers. Specifically, this refers to dedicated projects in which a government entity shares public health data with an academic research team for data analysis to receive data insights to inform policy. In this viewpoint, we identify and outline documented data sharing challenges in the context of COVID-19 and other public health crises, as well as broader crisis scenarios encompassing natural disasters and humanitarian emergencies. We then argue that government-academic data collaborations have the potential to alleviate these challenges, which should place them at the forefront of future research attention. In particular, for researchers, data collaborations with government entities should be considered part of the social infrastructure that bolsters their research efforts toward public health crisis response. Looking ahead, we propose a shift from ad hoc, intermittent collaborations to cultivating robust and enduring partnerships. Thus, we need to move beyond viewing government-academic data interactions as 1-time sharing events. Additionally, given the scarcity of scholarly exploration in this domain, we advocate for further investigation into the real-world practices and experiences related to sharing data from government sources with researchers during public health crises.

The Costs of Anonymization: Case Study Using Clinical Data.

BACKGROUND: Sharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as reidentification risk, can be addressed through the application of anonymization algorithms, whereby data are altered so that it is no longer reasonably related to a person. Yet, such alterations have the potential to influence the data set's statistical properties, such that the privacy-utility trade-off must be considered. This has been studied in theory, but evidence based on real-world individual-level clinical data is rare, and anonymization has not broadly been adopted in clinical practice. OBJECTIVE: The goal of this study is to contribute to a better understanding of anonymization in the real world by comprehensively evaluating the privacy-utility trade-off of differently anonymized data using data and scientific results from the German Chronic Kidney Disease (GCKD) study. METHODS: The GCKD data set extracted for this study consists of 5217 records and 70 variables. A 2-step procedure was followed to determine which variables constituted reidentification risks. To capture a large portion of the risk-utility space, we decided on risk thresholds ranging from 0.02 to 1. The data were then transformed via generalization and suppression, and the anonymization process was varied using a generic and a use case-specific configuration. To assess the utility of the anonymized GCKD data, general-purpose metrics (ie, data granularity and entropy), as well as use case-specific metrics (ie, reproducibility), were applied. Reproducibility was assessed by measuring the overlap of the 95% CI lengths between anonymized and original results. RESULTS: Reproducibility measured by 95% CI overlap was higher than utility obtained from general-purpose metrics. For example, granularity varied between 68.2% and 87.6%, and entropy varied between 25.5% and 46.2%, whereas the average 95% CI overlap was above 90% for all risk thresholds applied. A nonoverlapping 95% CI was detected in 6 estimates across all analyses, but the overwhelming majority of estimates exhibited an overlap over 50%. The use case-specific configuration outperformed the generic one in terms of actual utility (ie, reproducibility) at the same level of privacy. CONCLUSIONS: Our results illustrate the challenges that anonymization faces when aiming to support multiple likely and possibly competing uses, while use case-specific anonymization can provide greater utility. This aspect should be taken into account when evaluating the associated costs of anonymized data and attempting to maintain sufficiently high levels of privacy for anonymized data. TRIAL REGISTRATION: German Clinical Trials Register DRKS00003971; https://drks.de/search/en/trial/DRKS00003971. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1093/ndt/gfr456.

The role of the (in)accessibility of social media data for infodemic management: a public health perspective on the situation in the European Union in March 2024.

Public health institutions rely on the access to social media data to better understand the dynamics and impact of infodemics - an overabundance of information during a disease outbreak, potentially including mis-and disinformation. The scope of the COVID-19 infodemic has led to growing concern in the public health community. The spread of harmful information or information voids may negatively impact public health. In this context, social media are of particular relevance as an integral part of our society, where much information is consumed. In this perspective paper, we discuss the current state of (in)accessibility of social media data of the main platforms in the European Union. The European Union's relatively new Digital Services Act introduces the obligation for platforms to provide data access to a wide range of researchers, likely including researchers at public health institutions without formal academic affiliation. We examined eight platforms (Facebook, Instagram, LinkedIn, Pinterest, Snapchat, TikTok, X, YouTube) affected by the new legislation in regard to data accessibility. We found that all platforms apart from TikTok offer data access through the Digital Services Act. Potentially, this presents a fundamentally new situation for research, as before the Digital Services Act, few platforms granted data access or only to very selective groups of researchers. The access regime under the Digital Services Act is, however, still evolving. Specifics such as the application procedure for researcher access are still being worked out and results can be expected in spring 2024. The impact of the Digital Services Act on research will therefore only become fully apparent in the future.

Dacryocystorhinostomy videos on YouTube as a source of patient education.

BACKGROUND: To determine the quality and reliability of DCR YouTube videos as patient education resources and identify any associated factors predictive of video quality. METHODS: A YouTube search was conducted using the terms "Dacryocystorhinostomy, DCR, surgery" on 12th of January 2022, with the first 50 relevant videos selected for inclusion. For each video, the following was collected: video hyperlink, title, total views, months since the video was posted, video length, total likes/dislikes, authorship (i.e. surgeon, patient experience or media companies) and number of comments. The videos were graded independently by a resident, a registrar and an oculoplastic surgeon using three validated scoring systems: the Journal of the American Medical Association (JAMA), DISCERN, and Health on the Net (HON). RESULTS: The average number of video views was 22,992, with the mean length being 488.12 s and an average of 18 comments per video. The consensus JAMA, DISCERN and HON scores were 2.1 ± 0.6, 29.1 ± 8.8 and 2.7 ± 1.0, respectively. This indicated that the included videos were of a low quality, however, only DISCERN scores had good interobserver similarity. Videos posted by surgeons were superior to non-surgeons when considering mean JAMA and HON scores. No other factors were associated with the quality of educational content. CONCLUSION: The quality and reliability of DCR related content for patient education is relatively low. Based on this study's findings, patients should be encouraged to view videos created by surgeons or specialists in preference to other sources on YouTube.

Streamlining remote nanopore data access with slow5curl.

BACKGROUND: As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility, and reanalysis. RESULTS: Slow5curl allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. Slow5curl uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelized data access requests to maximize download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (>22 TB), we demonstrate how slow5curl can be used to quickly fetch and reanalyze raw signal reads corresponding to a set of target genes from each individual in large cohort dataset (n = 91), minimizing the time, egress costs, and local storage requirements for their reanalysis. CONCLUSIONS: We provide slow5curl as a free, open-source package that will reduce frictions in data sharing for the nanopore community: https://github.com/BonsonW/slow5curl.

Influencing factors and countermeasures on intelligent transformation and upgrading of logistics firms: A case study in China.

This study explores the influencing factors on intelligent transformation and upgrading of China's logistics firms under smart logistics, and designs the corresponding framework to guide the practice of firms. By analyzing the characteristics of smart logistics and the transformation and upgrading needs of traditional logistics, from the micro perspective of logistics firms, this paper constructs influencing factor index system of smart transformation and development from four dimensions: logistics technology innovation, logistics big data sharing, logistics management upgrading and logistics decision-making transformation. Logistics firms are divided into firms with medium scale and above and small and medium-sized firms according to their scale. Then EWIF-AHP model is proposed to measure the weight of index system and score the decision-making, so as to evaluate the impact of various influencing factors on transformation and development of logistics firms. The results show that, for logistics firms above medium scale, logistics technology innovation and logistics big data sharing have the most significant impact on transformation and development, followed by logistics management upgrading and logistics decision-making transformation. For small and medium-sized logistics firms, the biggest factor is the upgrading of logistics management, followed by the upgrading of logistics technology, which is almost as important as the influencing factors of the upgrading of logistics management, and followed by the sharing of logistics big data and the transformation of logistics decision-making. Therefore, corresponding countermeasures and suggestions for intelligent transformation of logistics firms have been put forward.

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways.

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

PLUME: Record, Replay, Analyze and Share User Behavior in 6DoF XR Experiences.

From education to medicine to entertainment, a wide range of industrial and academic fields now utilize eXtended Reality (XR) technologies. This diversity and growing use are boosting research and leading to an increasing number of XR experiments involving human subjects. The main aim of these studies is to understand the user experience in the broadest sense, such as the user cognitive and emotional states. Behavioral data collected during XR experiments, such as user movements, gaze, actions, and physiological signals constitute precious assets for analyzing and understanding the user experience. While they contribute to overcome the intrinsic flaws of explicit data such as post-experiment questionnaires, the required acquisition and analysis tools are costly and challenging to develop, especially for 6DoF (Degrees of Freedom) XR experiments. Moreover, there is no common format for XR behavioral data, which restrains data-sharing, and thus hinders wide usages across the community, replicability of studies, and the constitution of large datasets or meta-analysis. In this context, we present PLUME, an open-source software toolbox (PLUME Recorder, PLUME Viewer, PLUME Python) that allows for the exhaustive record of XR behavioral data (including synchronous physiological signals), their offline interactive replay and analysis (with a standalone application), and their easy sharing due to our compact and interoperable data format. We believe that PLUME can greatly benefit the scientific community by making the use of behavioral and physiological data available for the greatest, contributing to the reproducibility and replicability of XR user studies, enabling the creation of large datasets, and contributing to a deeper understanding of user experience.

A data-driven approach to choosing privacy parameters for clinical trial data sharing under differential privacy.

OBJECTIVES: Clinical trial data sharing is crucial for promoting transparency and collaborative efforts in medical research. Differential privacy (DP) is a formal statistical technique for anonymizing shared data that balances privacy of individual records and accuracy of replicated results through a "privacy budget" parameter, ε. DP is considered the state of the art in privacy-protected data publication and is underutilized in clinical trial data sharing. This study is focused on identifying ε values for the sharing of clinical trial data. MATERIALS AND METHODS: We analyzed 2 clinical trial datasets with privacy budget ε ranging from 0.01 to 10. Smaller values of ε entail adding greater amounts of random noise, with better privacy as a result. Comparison of rates, odds ratios, means, and mean differences between the original clinical trial datasets and the empirical distribution of the DP estimator was performed. RESULTS: The DP rate closely approximated the original rate of 6.5% when ε > 1. The DP odds ratio closely aligned with the original odds ratio of 0.689 when ε ≥ 3. The DP mean closely approximated the original mean of 164.64 when ε ≥ 1. As ε increased to 5, both the minimum and maximum DP means converged toward the original mean. DISCUSSION: There is no consensus on how to choose the privacy budget ε. The definition of DP does not specify the required level of privacy, and there is no established formula for determining ε. CONCLUSION: Our findings suggest that the application of DP holds promise in the context of sharing clinical trial data.

FAIR Header Reference genome: a TRUSTworthy standard.

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability and Technology. The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.