Open Science Resources Research Articles

Corrigendum to ‘RadLab: An open science resource for radiation studies relevant to human spaceflight’ Life Sciences in Space Research Volume 43, November 2024, Pages 29-34

Corrigendum to ‘RadLab: An open science resource for radiation studies relevant to human spaceflight’ Life Sciences in Space Research Volume 43, November 2024, Pages 29-34

A Case for the Use of Open Data as a Tool to Incorporate Socioscientific Topics into Neuroscience Education.

Education scholars have called for an increased focus on developing curricula based on culturally relevant pedagogy (Ladson-Billings, 1995). A key tenet of Ladson-Billings' (1995; 2014) theory of culturally relevant pedagogy is the development of students' sociopolitical consciousness, whereby students feel empowered and encouraged to evaluate and solve real-world interdisciplinary problems. Here, we propose that open science datasets could serve as a valuable tool for neuroscience educators to foster their students' sociopolitical consciousness. Using the open data available through the Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) as a case study, this article will explore how open science can be leveraged as a tool to encourage socioscientific thinking amongst neuroscience students. We overview a collection of lessons created by the Allen Institute's Education & Engagement team that provides a scaffolded exploration of an open science resource through a socioscientific lens. We supplement our discussion of the lessons with feedback from students who completed the lessons during a day-long workshop hosted at the Allen Institute in Seattle, WA. We conclude by reflecting on the future role this type of interdisciplinary, open science-based approach to curricula could have across neuroscience education more broadly.

Метадані наукових документів як складова системи інформаційних ресурсів «відкритої науки»

Open science is a movement that aims to make research results more accessible, including code, data, and scientific papers. It covers many different but often related aspects affecting the entire research life cycle, including open access to publications, open data of research, open source software, open workflows, public science, open educational resources and alternative methods of the research evaluation, including open peer review, expert reviews, etc. The key to effective application and integration of open science resources is their structured description based on the principles of completeness and necessity of meta-information, ease of use and interoperability. The units of such description are metadata. In fact, the quality of open resources begins with the quality of its metadata. This study does not cover the entire wide spectrum of open science resources. Its purposes are to define the system of characteristics that describe general and specific features of various types of scientific documents as a significant part of scientific knowledge of Open Science. To achieve the goal of the research it is defined a taxonomy of resources of open scientific documents and proposes an integrated system of their metadata. Proposed system of metadata is based on several classifier sets. It includes three major groups: internal characteristics – description of explicit features of the object of open knowledge (for example, the size or the type of the file), administrative characteristics – information about the object (authors, executers, etc.) and descriptive characteristics - information about the object’s content, its special features, links to other objects related to this. The metadata system is built based on the analysis of the existing metadata schemas and standards, search engines and digital libraries, and it takes into account similarity and specificity of each type of open documents.

INaturalist is an open science resource for ecological genomics by enabling rapid and tractable records of initial observations of sequenced biological samples.

The rapidly growing body of publicly available sequencing data for rare species and/or wild-caught samples is accelerating the need for detailed records of the samples used to generate datasets. Many already published datasets are unlikely to ever be reused, not due to problems with the data themselves, but due to their questionable or unverifiable origins. In this paper, I present iNaturalist-a pre-existing citizen science platform that allows people to post photo observations of organisms in nature-as a tool that allows genomics researchers to rapidly publish observations of samples used to generate sequencing datasets. This practice aligns with the values of the open science movement, and I also discuss how iNaturalist, along with other online resources, can be used to create an open genomics pipeline that enables future replication studies and ensures the value of genomics datasets to future research.

Teaching and Training with Open Science: From Classroom Teaching Tool to Professional Development

In order for open science to reach its full potential to reduce barriers in science and increase access to the field, data and tools need to be accompanied by training and other supporting resources to make them truly accessible to prospective and new users. Further, these educational resources must be tailored to meet the needs of many different user profiles, such as neuroscientists of many specialties, computational scientists, and educators. In this article, we will describe some of the approaches the Allen Institute has taken to support working scientists, students, and educators at multiple career stages and paths to use our open science resources.

Phospholipid Removal for Enhanced Chemical Exposomics in Human Plasma.

The challenge of chemical exposomics in human plasma is the 1000-fold concentration gap between endogenous substances and environmental pollutants. Phospholipids are the major endogenous small molecules in plasma, thus we validated a chemical exposomics protocol with an optimized phospholipid-removal step prior to targeted and non-targeted liquid chromatography high-resolution mass spectrometry. Increased injection volume with negligible matrix effect permitted sensitive multiclass targeted analysis of 77 priority analytes; median MLOQ = 0.05 ng/mL for 200 μL plasma. In non-targeted acquisition, mean total signal intensities of non-phospholipids were enhanced 6-fold in positive (max 28-fold) and 4-fold in negative mode (max 58-fold) compared to a control method without phospholipid removal. Moreover, 109 and 28% more non-phospholipid molecular features were detected by exposomics in positive and negative mode, respectively, allowing new substances to be annotated that were non-detectable without phospholipid removal. In individual adult plasma (100 μL, n = 34), 28 analytes were detected and quantified among 10 chemical classes, and quantitation of per- and polyfluoroalkyl substances (PFAS) was externally validated by independent targeted analysis. Retrospective discovery and semi-quantification of PFAS-precursors was demonstrated, and widespread fenuron exposure is reported in plasma for the first time. The new exposomics method is complementary to metabolomics protocols, relies on open science resources, and can be scaled to support large studies of the exposome.

Open science resources from the Tara Pacific expedition across coral reef and surface ocean ecosystems

The Tara Pacific expedition (2016–2018) sampled coral ecosystems around 32 islands in the Pacific Ocean and the ocean surface waters at 249 locations, resulting in the collection of nearly 58 000 samples. The expedition was designed to systematically study warm-water coral reefs and included the collection of corals, fish, plankton, and seawater samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide a complete description of the sampling methodology, and we explain how to explore and access the different datasets generated by the expedition. Environmental context data were obtained from taxonomic registries, gazetteers, almanacs, climatologies, operational biogeochemical models, and satellite observations. The quality of the different environmental measures has been validated not only by various quality control steps, but also through a global analysis allowing the comparison with known environmental large-scale structures. Such publicly released datasets open the perspective to address a wide range of scientific questions.

Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach.

Magnetic resonance imaging (MRI)-based brain segmentation has recently been revolutionized by deep learning methods. These methods use large numbers of annotated segmentations to train algorithms that have the potential to perform brain segmentations reliably and quickly. However, training data for these algorithms are frequently obtained from automated brain segmentation systems, which may contain inaccurate neuroanatomy. Thus, the neuroimaging community would benefit from an open source database of high quality, neuroanatomically curated and manually edited MRI brain images, as well as the publicly available tools and detailed procedures for generating these curated data. Manual segmentation approaches are regarded as the gold standard for brain segmentation and parcellation. These approaches underpin the construction of neuroanatomically accurate human brain atlases. In addition, neuroanatomically precise definitions of MRI-based regions of interest (ROIs) derived from manual brain segmentation are essential for accuracy in structural connectivity studies and in surgical planning for procedures such as deep brain stimulation. However, manual segmentation procedures are time and labor intensive, and not practical in studies utilizing very large datasets, large cohorts, or multimodal imaging. Automated segmentation methods were developed to overcome these issues, and provide high data throughput, increased reliability, and multimodal imaging capability. These methods utilize manually labeled brain atlases to automatically parcellate the brain into different ROIs, but do not have the anatomical accuracy of skilled manual segmentation approaches. In the present study, we developed a custom software module for manual editing of brain structures in the freely available 3D Slicer software platform that employs principles and tools based on pioneering work from the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. We used these novel 3D Slicer segmentation tools and techniques in conjunction with well-established neuroanatomical definitions of subcortical brain structures to manually segment 50 high resolution T1w MRI brains from the Human Connectome Project (HCP) Young Adult database. The structural definitions used herein are associated with specific neuroanatomical ontologies to systematically interrelate histological and MRI-based morphometric definitions. The resulting brain datasets are publicly available and will provide the basis for a larger database of anatomically curated brains as an open science resource.

Dynamic causal modelling of COVID-19 and its mitigations

This technical report describes the dynamic causal modelling of mitigated epidemiological outcomes during the COVID-9 coronavirus outbreak in 2020. Dynamic causal modelling is a form of complex system modelling, which uses ‘real world’ timeseries to estimate the parameters of an underlying state space model using variational Bayesian procedures. Its key contribution—in an epidemiological setting—is to embed conventional models within a larger model of sociobehavioural responses—in a way that allows for (relatively assumption-free) forecasting. One advantage of using variational Bayes is that one can progressively optimise the model via Bayesian model selection: generally, the most likely models become more expressive as more data becomes available. This report summarises the model (on 6-Nov-20), eight months after the inception of dynamic causal modelling for COVID-19. This model—and its subsequent updates—is used to provide nowcasts and forecasts of latent behavioural and epidemiological variables as an open science resource. The current report describes the underlying model structure and the rationale for the variational procedures that underwrite Bayesian model selection.

The Developing Human Connectome Project Neonatal Data Release.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Open science as a path to education of new psychophysiologists

There is a pressing need for resources to train the next generation of psychophysiologists. Psychophysiology, and especially the subfield of cognitive electrophysiology, poses challenges for educators because it requires an understanding of complex concepts and experimental design, advanced analysis and programming skills, and access to specialized software and equipment. These challenges are common to other STEM fields as well. We present PURSUE (Preparing Undergraduates for Research in STEM Using Electrophysiology – www.PursueERP.com) as an example initiative that engages open educational practices to create and share freely available electrophysiology training materials. This model uses evidence-based pedagogy to create accessible and flexible materials, an open database with supporting lab-based training resources, and also provides instructor support during implementation. This model can be used for other areas within STEM. We review benefits and challenges of using open science research and publishing practices for training. Open science resources have benefits for both course-based undergraduate research experiences and other types of training by increasing access to publications, software, and code for conducting experiments and analyses, as well as access to data for those who do not have access to research equipment. Further, we argue that coordinated open educational practices are necessary to take full advantage of open science resources for training students. Open educational practices such as open educational resources, collaborative course building, and implementation support greatly enhance the ability to incorporate these open science resources into a curriculum.

Open science resources for the mass spectrometry-based analysis of SARS-CoV-2

Open science resources for the mass spectrometry-based analysis of SARS-CoV-2

The Kinase Chemogenomic Set (KCGS): An Open Science Resource for Kinase Vulnerability Identification.

We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS), current Version 1.0, is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.

Access to data from clinical trials in the COVID-19 crisis: open, flexible, and time-sensitive

- There is a great need to swiftly develop vaccines and treatments against COVID-19 in the current pandemic. Yet, the time pressure and difficult circumstances to conduct clinical trials increases the risk of incomplete data sets, suboptimal study designs, and thus spurious results and reversals of decisions. - Open access to clinical trial and other patient-relevant data is necessary in order to provide transparency, and the possibility for validating clinical-trial analyses, and fully exploiting the information emerging from clinical trials. Thus, open access is critical in order to enable the successful and swift development of an effective intervention.

Information technologies and resources of open science: bibliometric, scientometric vision

Problem setting. Today our country joins the European Research Area, in particular, taking into account the experience and successful practices of the European Union in open science, cooperation in digital projects, ensuring access of Ukrainian scientists to international databases, electronic journals, scientific and educational networks and scientometric systems and platforms. Some analysis issues of the state and prospects of the national system of open science development, the application of information technologies and open science resources for scientometric and bibliometric analysis of modern trends in scientific communication, don`t lose their relevance, were and remain in the center of attention of foreign and national scientists, specialists, practitioners, such as: S. Glibko, Y. Pasmor, A. Strizhkova. The target of this article is to define tasks and directions concerning scientometric and bibliometric definition of modern problems of scientific activity on the basis of the analysis. Article`s main body. In the context of Ukraine’s solution of tasks and implementation of long-term plans for integration of achievements and obtainings of scientists into the European information space, EU development strategy until 2020 is aimed at «Innovation Union» and at building open innovation. It seems convincing that the concept of open access has become the basis for the emergence of a number of projects, which were realised in the paradigm of open science through the joint use and dissemination of research results, ideas, innovations for global progress, development and presence of Ukraine in the world scientific community. Conclusions and prospects for the development. 44.8 % of respondents said that scientometrics is very important. 89.6 % support scientometrics as a new but necessary way to measure scientific achievements. Therefore, in the current trends of global technologies of open science, natural transformations of society, the evolution of forms and research methodologies are obvious. In the paradigm of open innovations, which are also based on scientometric, bibliometric indicators and resources of open science, the following issues are relevant: 1) providing grant support for the best projects of Ukrainian scientists within the competition of the National Research Foundation; 2) implementation of measures for Ukraine accession to the grant program «Horizon Europe»; 3) continuation of work on the creation of the National Scientific Information System «URIS»; 4) stimulation of activities in the field of technology transfer to provide more transparency and accessibility to national science; 5) implementation of a pilot project of the creation a network of startup-school-incubator-accelerator on the basis of higher education institutions and research institutions.

ACS launches open science resource center

ACS Publications has launched an open science resource center to help researchers find and navigate open access resources. The new resource center will, for example, let researchers find step-by-st...

One- and two-year visual outcomes from the Moorfields age-related macular degeneration database: a retrospective cohort study and an open science resource

ObjectivesTo analyse treatment outcomes and share clinical data from a large, single-centre, well-curated database (8174 eyes/6664 patients with 120 756 single entries) of patients with neovascular age-related macular degeneration (AMD)...

Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition

A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009–2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world’s planktonic ecosystems.

Collaborating on open science: The journey of the Biodiversity Heritage Library

The Biodiversity Heritage Library, BHL,1 is an established and successful digital library, formed by a global consortium of natural history libraries, with engaged and enthusiastic users. The extensive partnerships, curated content, innovative tools and services, the ease of mining the data all combine to establish an open science resource that advances scientific progress through linking, use and reuse. The aim of BHL as stated on the web page is: “Inspiring discovery through free access to biodiversity knowledge. The Biodiversity Heritage Library works collaboratively to make biodiversity literature openly available to the world as part of a global biodiversity community. BHL also serves as the foundational literature component of the Encyclopedia of Life (EOL)”. BHL and EOL are linked via taxonomic names and bibliographies. BHL is linked in a similar way to the Global Biodiversity Information Facility (GBIF) and thus has broad exposure to scientists across the globe as well as a global public.

WikiHyperGlossary (WHG): an information literacy technology for chemistry documents.

BackgroundThe WikiHyperGlossary is an information literacy technology that was created to enhance reading comprehension of documents by connecting them to socially generated multimedia definitions as well as semantically relevant data. The WikiHyperGlossary enhances reading comprehension by using the lexicon of a discipline to generate dynamic links in a document to external resources that can provide implicit information the document did not explicitly provide. Currently, the most common method to acquire additional information when reading a document is to access a search engine and browse the web. This may lead to skimming of multiple documents with the novice actually never returning to the original document of interest. The WikiHyperGlossary automatically brings information to the user within the current document they are reading, enhancing the potential for deeper document understanding.ResultsThe WikiHyperGlossary allows users to submit a web URL or text to be processed against a chosen lexicon, returning the document with tagged terms. The selection of a tagged term results in the appearance of the WikiHyperGlossary Portlet containing a definition, and depending on the type of word, tabs to additional information and resources. Current types of content include multimedia enhanced definitions, ChemSpider query results, 3D molecular structures, and 2D editable structures connected to ChemSpider queries. Existing glossaries can be bulk uploaded, locked for editing and associated with multiple social generated definitions.ConclusionThe WikiHyperGlossary leverages both social and semantic web technologies to bring relevant information to a document. This can not only aid reading comprehension, but increases the users’ ability to obtain additional information within the document. We have demonstrated a molecular editor enabled knowledge framework that can result in a semantic web inductive reasoning process, and integration of the WikiHyperGlossary into other software technologies, like the Jikitou Biomedical Question and Answer system. Although this work was developed in the chemical sciences and took advantage of open science resources and initiatives, the technology is extensible to other knowledge domains. Through the DeepLit (Deeper Literacy: Connecting Documents to Data and Discourse) startup, we seek to extend WikiHyperGlossary technologies to other knowledge domains, and integrate them into other knowledge acquisition workflows.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0073-7) contains supplementary material, which is available to authorized users.