scholarly journals FAIR Science for Social Machines: Let's Share Metadata Knowlets in the Internet of FAIR Data and Services

2019 ◽  
Vol 1 (1) ◽  
pp. 22-42 ◽  
Author(s):  
Barend Mons
Keyword(s):  
Scientific Practice ◽  
Critical Role ◽  
Public Funding ◽  
Open Science ◽  
Central Feature ◽  
Relative Role ◽  
Patient Privacy ◽  
Science Data ◽  
Social Machines ◽  
Data Stewardship

In a world awash with fragmented data and tools, the notion of Open Science has been gaining a lot of momentum, but simultaneously, it caused a great deal of anxiety. Some of the anxiety may be related to crumbling kingdoms, but there are also very legitimate concerns, especially about the relative role of machines and algorithms as compared to humans and the combination of both (i.e., social machines). There are also grave concerns about the connotations of the term “open”, but also regarding the unwanted side effects as well as the scalability of the approaches advocated by early adopters of new methodological developments. Many of these concerns are associated with mind-machine interaction and the critical role that computers are now playing in our day to day scientific practice. Here we address a number of these concerns and provide some possible solutions. FAIR (machine-actionable) data and services are obviously at the core of Open Science (or rather FAIR science). The scalable and transparent routing of data, tools and compute (to run the tools on) is a key central feature of the envisioned Internet of FAIR Data and Services (IFDS). Both the European Commission in its Declaration on the European Open Science Cloud, the G7, and the USA data commons have identified the need to ensure a solid and sustainable infrastructure for Open Science. Here we first define the term FAIR science as opposed to Open Science. In FAIR science, data and the associated tools are all Findable, Accessible under well defined conditions, Interoperable and Reusable, but not necessarily “open”; without restrictions and certainly not always “gratis”. The ambiguous term “open” has already caused considerable confusion and also opt-out reactions from researchers and other data-intensive professionals who cannot make their data open for very good reasons, such as patient privacy or national security. Although Open Science is a definition for a way of working rather than explicitly requesting for all data to be available in full Open Access, the connotation of openness of the data involved in Open Science is very strong. In FAIR science, data and the associated services to run all processes in the data stewardship cycle from design of experiment to capture to curation, processing, linking and analytics all have minimally FAIR metadata, which specify the conditions under which the actual underlying research objects are reusable, first for machines and then also for humans. This effectively means that—properly conducted—Open Science is part of FAIR science. However, FAIR science can also be done with partly closed, sensitive and proprietary data. As has been emphasized before, FAIR is not identical to “open”. In FAIR/Open Science, data should be as open as possible and as closed as necessary. Where data are generated using public funding, the default will usually be that for the FAIR data resulting from the study the accessibility will be as high as possible, and that more restrictive access and licensing policies on these data will have to be explicitly justified and described. In all cases, however, even if the reuse is restricted, data and related services should be findable for their major uses, machines, which will make them also much better findable for human users. With a tendency to make good data stewardship the norm, a very significant new market for distributed data analytics and learning is opening and a plethora of tools and reusable data objects are being developed and released. These all need FAIR metadata to be routed to each other and to be effective.

scholarly journals Methods for Open and Reproducible Materials Science

2019 ◽  
Author(s):  
Sara L Wilson ◽  
Micah Altman ◽  
Rafael Jaramillo
Keyword(s):  
Data Management ◽  
Data Science ◽  
Management Practices ◽  
Materials Science ◽  
Critical Role ◽  
Structured Interview ◽  
Open Science ◽  
Manuscript Submission ◽  
Attitudes And Practices ◽  
Data Stewardship

Data stewardship in experimental materials science is increasingly complex and important. Progress in data science and inverse-design of materials give reason for optimism that advances can be made if appropriate data resources are made available. Data stewardship also plays a critical role in maintaining broad support for research in the face of well-publicized replication failures (in different fields) and frequently changing attitudes, norms, and sponsor requirements for open science. The present-day data management practices and attitudes in materials science are not well understood. In this article, we collect information on the practices of a selection of materials scientists at two leading universities, using a semi-structured interview instrument. An analysis of these interviews reveals that although data management is universally seen as important, data management practices vary widely. Based on this analysis, we conjecture that broad adoption of basic file-level data sharing at the time of manuscript submission would benefit the field without imposing substantial burdens on researchers. More comprehensive solutions for lifecycle open research in materials science will have to overcome substantial differences in attitudes and practices.

Planetary Science Virtual Observatory: VESPA/Europlanet outcome and prospects

2020 ◽  
Author(s):  
Stéphane Erard ◽  
Baptiste Cecconi ◽  
Pierre Le Sidaner ◽  
Angelo Pio Rossi ◽  
Hanna Rothkaehl ◽  
...  
Keyword(s):  
Open Science ◽  
Planetary Science ◽  
Geological Mapping ◽  
Virtual Observatory ◽  
Science Data ◽  
Small Bodies ◽  
Horizon 2020 ◽  
Data Services ◽  
Research And Innovation ◽  
Data Stewardship

<p>The Europlanet-2020 programme, which ended Aug 2019, included an activity called VESPA (Virtual European Solar and Planetary Access) which focused on adapting Virtual Observatory (VO) techniques to handle Planetary Science data. We will present some aspects of VESPA at the end of this 4-years development phase and at the onset of the newly selected Europlanet-2024 programme in Feb 2020. VESPA currently distributes 54 data services which are searchable according to observing conditions and encompass a wide scope including surfaces, atmospheres, magnetospheres and planetary plasmas, small bodies, heliophysics, exoplanets, and lab spectroscopy. Versatile online visualization tools have been adapted for Planetary Science, and efforts were made to connect the Astronomy VO with related environments, e.g., GIS for planetary surfaces. The new programme will broaden and secure the former “data stewardship” concept, providing a handy solution to Open Science challenges in our community. It will also move towards a new concept of “enabling data analysis”: a run-on-demand platform will be adapted from another H2020 programme in Astronomy (ESCAPE); VESPA services will be made ready to use for Machine Learning and geological mapping activities, and will also host selected results from such analyses. More tutorials and practical use cases will be made available to facilitate access to the VESPA infrastructure.</p><p>VESPA portal: http://vespa.obspm.fr</p><p>The Europlanet 2020/2024 Research Infrastructure projects have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 654208 and No 871149</p>

scholarly journals The Effect of Octapeptide Repeats on Prion Folding and Misfolding

2021 ◽  
Vol 22 (4) ◽  
pp. 1800
Author(s):  
Kun-Hua Yu ◽  
Mei-Yu Huang ◽  
Yi-Ru Lee ◽  
Yu-Kie Lin ◽  
Hau-Ren Chen ◽  
...  
Keyword(s):  
Amyloid Fibrils ◽  
Age Of Onset ◽  
Prion Diseases ◽  
Critical Role ◽  
Threshold Effect ◽  
Central Feature ◽  
Terminal Domain ◽  
Amyloid Aggregates

Misfolding of prion protein (PrP) into amyloid aggregates is the central feature of prion diseases. PrP has an amyloidogenic C-terminal domain with three α-helices and a flexible tail in the N-terminal domain in which multiple octapeptide repeats are present in most mammals. The role of the octapeptides in prion diseases has previously been underestimated because the octapeptides are not located in the amyloidogenic domain. Correlation between the number of octapeptide repeats and age of onset suggests the critical role of octapeptide repeats in prion diseases. In this study, we have investigated four PrP variants without any octapeptides and with 1, 5 and 8 octapeptide repeats. From the comparison of the protein structure and the thermal stability of these proteins, as well as the characterization of amyloids converted from these PrP variants, we found that octapeptide repeats affect both folding and misfolding of PrP creating amyloid fibrils with distinct structures. Deletion of octapeptides forms fewer twisted fibrils and weakens the cytotoxicity. Insertion of octapeptides enhances the formation of typical silk-like fibrils but it does not increase the cytotoxicity. There might be some threshold effect and increasing the number of peptides beyond a certain limit has no further effect on the cell viability, though the reasons are unclear at this stage. Overall, the results of this study elucidate the molecular mechanism of octapeptides at the onset of prion diseases.

scholarly journals Data Papers as a New Form of Knowledge Organization in the Field of Research Data

2019 ◽  
Vol 46 (8) ◽  
pp. 622-638
Author(s):  
Joachim Schöpfel ◽  
Dominic Farace ◽  
Hélène Prost ◽  
Antonella Zane
Keyword(s):  
Business Models ◽  
Open Science ◽  
Research Data ◽  
Data Driven ◽  
Academic Publishing ◽  
Science Data ◽  
Research Data Management ◽  
Fair Principles ◽  
New Form ◽  
Machine Readable

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.

scholarly journals Integrating open science in the teaching of cognitive research methods

2020 ◽  
Author(s):  
Ralph S. Redden ◽  
Colin R McCormick
Keyword(s):  
Research Methods ◽  
Undergraduate Research ◽  
Scientific Practice ◽  
A Priori ◽  
Daily Practice ◽  
Open Science ◽  
Methods Course ◽  
Replication Experiment ◽  
Successful Replication ◽  
Oral Presentations

Openness, transparency, and reproducibility are widely accepted as fundamental aspects of scientific practice. However, a growing body of evidence suggests that these features are not readily adopted in the daily practice of most scientists. The Centre for Open Science has been championing efforts for systemic change in the scientific process, with newly adopted practices such as preregistration and open sharing of data and experimental materials. In an effort to inculcate these practices early in training, we have integrated several key components of open science practice into an undergraduate research methods course in the cognitive sciences. Students were divided into four research teams, each with the goal of carrying out a replication experiment related to the study of attention; specifically, temporal orienting, alertness, prior entry, and the attentional blink. Teams completed a preregistration exercise, and importantly, were encouraged to consider a priori the criteria for a successful replication. They were also required to collect and analyze data, prepare manuscripts, and disseminate their findings in poster symposia and oral presentations. All project materials can be found at https://osf.io/gxkfq/. Critical appraisal of the goals and implementation of the course are discussed.

scholarly journals TrIAS, leveraging citizen science data to monitor invasive species in Belgium

2018 ◽  
Vol 2 ◽  
pp. e24749
Author(s):  
Quentin Groom ◽  
Tim Adriaens ◽  
Damiano Oldoni ◽  
Lien Reyserhove ◽  
Diederik Strubbe ◽  
...  
Keyword(s):  
Invasive Species ◽  
Alien Species ◽  
Citizen Science ◽  
Invasive Alien Species ◽  
Science Research ◽  
Open Science ◽  
Policy Support ◽  
Science Data ◽  
Common View ◽  
Indispensable Tool

Reducing the damage caused by invasive species requires a community approach informed by rapidly mobilized data. Even if local stakeholders work together, invasive species do not respect borders, and national, continental and global policies are required. Yet, in general, data on invasive species are slow to be mobilized, often of insufficient quality for their intended application and distributed among many stakeholders and their organizations, including scientists, land managers, and citizen scientists. The Belgian situation is typical. We struggle with the fragmentation of data sources and restrictions to data mobility. Nevertheless, there is a common view that the issue of invasive alien species needs to be addressed. In 2017 we launched the Tracking Invasive Alien Species (TrIAS) project, which envisages a future where alien species data are rapidly mobilized, the spread of exotic species is regularly monitored, and potential impacts and risks are rapidly evaluated in support of policy decisions (Vanderhoeven et al. 2017). TrIAS is building a seamless, data-driven workflow, from raw data to policy support documentation. TrIAS brings together 21 different stakeholder organizations that covering all organisms in the terrestrial, freshwater and marine environments. These organizations also include those involved in citizen science, research and wildlife management. TrIAS is an Open Science project and all the software, data and documentation are being shared openly (Groom et al. 2018). This means that the workflow can be reused as a whole or in part, either after the project or in different countries. We hope to prove that rapid data workflows are not only an indispensable tool in the control of invasive species, but also for integrating and motivating the citizens and organizations involved.

scholarly journals Analyzing academic mobility of U.S. professors based on ORCID data and the Carnegie Classification

2020 ◽  
Vol 1 (4) ◽  
pp. 1451-1467
Author(s):  
Erija Yan ◽  
Yongjun Zhu ◽  
Jiangen He
Keyword(s):  
United States ◽  
The United States ◽  
Open Science ◽  
Geographic Region ◽  
Science Data ◽  
Academic Mobility ◽  
Carnegie Classification ◽  
Research Intensity ◽  
Rural Institutions ◽  
Urban Institutions

This paper uses two open science data sources—ORCID and the Carnegie Classification of Institutions of Higher Education (CCIHE)—to identify tenure-track and tenured professors in the United States who have changed academic affiliations. Through a series of data cleaning and processing actions, 5,938 professors met the selection criteria of professorship and mobility. Using ORCID professor profiles and the Carnegie Classification, this paper reveals patterns of academic mobility in the United States from the aspects of institution types, locations, regions, funding mechanisms of institutions, and professors’ genders. We find that professors tended to move to institutions with higher research intensity, such as those with an R1 or R2 designation in the Carnegie Classification. They also tend to move from rural institutions to urban institutions. Additionally, this paper finds that female professors are more likely to move within the same geographic region than male professors and that when they move from a less research-intensive institution to a more research-intensive one, female professors are less likely to retain their rank or attain promotion.

scholarly journals Inhibition of the histone demethylase, KDM5B, directly induces re-expression of tumor suppressor protein HEXIM1 in cancer cells

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Monica M. Montano ◽  
I-Ju Yeh ◽  
Yinghua Chen ◽  
Chris Hernandez ◽  
Janna G. Kiselar ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Suppressor ◽  
Cancer Cells ◽  
Cancer Metastasis ◽  
Critical Role ◽  
Cell Phenotype ◽  
Relative Role ◽  
Western Blots ◽  
Inhibition Of Proliferation ◽  
Proliferation Assays

Abstract Background The tumor suppressor actions of hexamethylene bis-acetamide (HMBA)-inducible protein 1 (HEXIM1) in the breast, prostate, melanomas, and AML have been reported by our group and others. Increased HEXIM1 expression caused differentiation and inhibited proliferation and metastasis of cancer cells. Historically, HEXIM1 has been experimentally induced with the hybrid polar compound HMBA, but HMBA is a poor clinical candidate due to lack of a known target, poor pharmacological properties, and unfavorable ADMETox characteristics. Thus, HEXIM1 induction is an intriguing therapeutic approach to cancer treatment, but requires better chemical tools than HMBA. Methods We identified and verified KDM5B as a target of HEXIM1 inducers using a chemical proteomics approach, biotin–NeutrAvidin pull-down assays, surface plasmon resonance, and molecular docking. The regulation of HEXIM1 by KDM5B and KDM5B inhibitors was assessed using chromatin immunoprecipitation assays, RT-PCR, western blotting, and depletion of KDM5B with shRNAs. The regulation of breast cancer cell phenotype by KDM5B inhibitors was assessed using western blots, differentiation assays, proliferation assays, and a mouse model of breast cancer metastasis. The relative role of HEXIM1 in the action of KDM5B inhibitors was determined by depleting HEXIM1 using shRNAs followed by western blots, differentiation assays, and proliferation assays. Results We have identified a highly druggable target, KDM5B, which is inhibited by small molecule inducers of HEXIM1. RNAi knockdown of KDM5B induced HEXIM1 expression, thus validating the specific negative regulation of tumor suppressor HEXIM1 by the H3K4me3/2 demethylase KDM5B. Known inhibitors of KDM5B were also able to induce HEXIM1 expression, inhibit cell proliferation, induce differentiation, potentiate sensitivity to cancer chemotherapy, and inhibit breast tumor metastasis. Conclusion HMBA and 4a1 induce HEXIM1 expression by inhibiting KDM5B. Upregulation of HEXIM1 expression levels plays a critical role in the inhibition of proliferation of breast cancer cells using KDM5B inhibitors. Based on the novel molecular scaffolds that we identified which more potently induced HEXIM1 expression and data in support that KDM5B is a target of these compounds, we have opened up new lead discovery and optimization directions.

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