Article

In praise of open research measures

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... Regarding human activities, data from the National Institute for Space Research (INPE, 2018) reveals that 45 % of the Caatinga biome is degraded and that 7.2 % of its soil is already exposed. In addition, the Caatinga has been exposed to continuous land cover changes, and less than 1 % of the region is a strictly protected area (Leal et al., 2005;Kolker, 2013). Thus, our results (a) provide insights into identifying geographical areas that could be preserved due to their capacity for providing blue and green water and (b) could be part of a monitoring system for optimizing the limited water inputs and supply in this semiarid ecosystem (i.e., for agricultural planning). ...
Article
Full-text available
Over the past decade, Brazil has experienced severe droughts across its territory, with important implications for soil moisture dynamics. Soil moisture variability has a direct impact on agriculture, water security and ecosystem services. Nevertheless, there is currently little information on how soil moisture across different biomes responds to drought. In this study, we used satellite soil moisture data from the European Space Agency, from 2009 to 2015, to analyze differences in soil moisture responses to drought for each biome of Brazil: Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa and Pantanal. We found an overall soil moisture decline of −0.5 % yr−1 (p
... This is often underestimated by biologists during the result interpretation [4]. Thus, both the standardization and the evaluation of the reproducibility of data analysis workflows between method modifications, mass spectrometers employed, different laboratories, and biological replicates are required [5]. Speaking of the reproducibility we look for the workflows, in which the proteomes of similar biological samples characterized in different studies may be properly compared and then integrated into a common knowledge base. ...
Article
Genomic and proteomic data were integrated into the proteogenomic workflow to identify coding genomic variants of Human Embryonic Kidney 293 (HEK-293) cell line at the proteome level. Shotgun proteome data published by Geiger et al. (2012), Chick et al. (2015), and obtained in this work for HEK-293 were searched against the customized genomic database generated using exome data published by Lin et al. (2014). Overall, 112 unique variants were identified at the proteome level out of ∼1,200 coding variants annotated in the exome. 7 identified variants were shared between all three considered proteomic data sets, and 27 variants were found in any two data sets. Some of the found variants belong to widely known genomic polymorphisms originated from the germline, while the others are more likely resulting from somatic mutations. At least, 8 of the proteins bearing amino acid variants were annotated as cancer-related ones, including p53 tumor suppressor. In all considered shotgun data sets, the variant peptides were at the ratio of 1:2.5 less likely being identified than the wild-type ones compared with the corresponding theoretical peptides. This can be explained by the presence of the so-called 'passenger' mutations in the genes which were never expressed in HEK-293 cells. This article is protected by copyright. All rights reserved.
... Metadata is important for at least three reasons. First, metadata is a conditio sine qua non for transparent, reproducible, and thus, accountable omics data provenance (Kolker et al., 2013). In the age of Big Data (Higdon et al., 2013), the open source movement that has stemmed from the advancement of newly developed and available softwares and technologies, integrated Personal Omics Profiling (iPOP) and personal genomics (Prainsack and Vayena, 2013;Vayena and Tasioulas, 2013a), metadata are crucial for robust open science (Snyder et al., 2014). ...
Article
Full-text available
Abstract Metadata refer to descriptions about data or as some put it, "data about data." Metadata capture what happens on the backstage of science, on the trajectory from study conception, design, funding, implementation, and analysis to reporting. Definitions of metadata vary, but they can include the context information surrounding the practice of science, or data generated as one uses a technology, including transactional information about the user. As the pursuit of knowledge broadens in the 21(st) century from traditional "science of whats" (data) to include "science of hows" (metadata), we analyze the ways in which metadata serve as a catalyst for responsible and open innovation, and by extension, science diplomacy. In 2015, the United Nations Millennium Development Goals (MDGs) will formally come to an end. Therefore, we propose that metadata, as an ingredient of responsible innovation, can help achieve the Sustainable Development Goals (SDGs) on the post-2015 agenda. Such responsible innovation, as a collective learning process, has become a key component, for example, of the European Union's 80 billion Euro Horizon 2020 R&D Program from 2014-2020. Looking ahead, OMICS: A Journal of Integrative Biology, is launching an initiative for a multi-omics metadata checklist that is flexible yet comprehensive, and will enable more complete utilization of single and multi-omics data sets through data harmonization and greater visibility and accessibility. The generation of metadata that shed light on how omics research is carried out, by whom and under what circumstances, will create an "intervention space" for integration of science with its socio-technical context. This will go a long way to addressing responsible innovation for a fairer and more transparent society. If we believe in science, then such reflexive qualities and commitments attained by availability of omics metadata are preconditions for a robust and socially attuned science, which can then remain broadly respected, independent, and responsibly innovative. "In Sierra Leone, we have not too much electricity. The lights will come on once in a week, and the rest of the month, dark[ness]. So I made my own battery to power light in people's houses." Kelvin Doe (Global Minimum, 2012 ) MIT Visiting Young Innovator Cambridge, USA, and Sierra Leone "An important function of the (Global) R&D Observatory will be to provide support and training to build capacity in the collection and analysis of R&D flows, and how to link them to the product pipeline." World Health Organization ( 2013 ) Draft Working Paper on a Global Health R&D Observatory.
Article
Full-text available
Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org ) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org ) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding.
ResearchGate has not been able to resolve any references for this publication.