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Selection: with tag open-science [119 articles] 


Software simplified

Nature, Vol. 546, No. 7656. (29 May 2017), pp. 173-174,


Containerization technology takes the hassle out of setting up software and can boost the reproducibility of data-driven research. [Excerpt] [...] Containers are essentially lightweight, configurable virtual machines — simulated versions of an operating system and its hardware, which allow software developers to share their computational environments. Researchers use them to distribute complicated scientific software systems, thereby allowing others to execute the software under the same conditions that its original developers used. In doing so, containers can remove one source of variability in ...


Do not publish

Science, Vol. 356, No. 6340. (25 May 2017), pp. 800-801,


Biologists have long valued publishing detailed information on rare and endangered species. Until relatively recently, much of this information was accessible only through accessing specialized scientific journals in university libraries. However, much of these data have been transferred online with the advent of digital platforms and a rapid push to open-access publication. Information is increasingly also available online in public reports and wildlife atlases, and research published behind paywalls can often be found in the public domain. Increased data and information ...


Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical results

PLOS ONE, Vol. 6, No. 11. (2 November 2011), e26828,


The widespread reluctance to share published research data is often hypothesized to be due to the authors' fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically. We related the reluctance to share research data for reanalysis to 1148 statistically significant results reported in 49 papers published in two major psychology journals. We found the reluctance to share data to be associated with weaker evidence ...


The importance of free and open source software and open standards in modern scientific publishing

Publications, Vol. 1, No. 2. (26 June 2013), pp. 49-55,


In this paper we outline the reasons why we believe a reliance on the use of proprietary computer software and proprietary file formats in scientific publication have negative implications for the conduct and reporting of science. There is increasing awareness and interest in the scientific community about the benefits offered by free and open source software. We discuss the present state of scientific publishing and the merits of advocating for a wider adoption of open standards in science, particularly where it ...


A data citation roadmap for scientific publishers

bioRxiv (19 January 2017), 100784,


This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP) [1], a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of and the NIH BioCADDIE program. The structure of the roadmap presented here follows the “life of a paper” workflow and includes the categories Pre-submission, Submission, Production, ...


A manifesto for reproducible science

Nature Human Behaviour, Vol. 1, No. 1. (10 January 2017), 0021,


Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals ...


Position paper for the endorsement of Free Software and Open Standards in Horizon 2020 and all publicly-funded research

In Free Software Foundation Europe (January 2017)


The Free Software Foundation Europe (FSFE) is a charity that empowers users to control technology by advocating for Free Software. In a digital world, Free Software is the fundament of Open Knowledge, Open Innovation and Open Science. [\n] Software is an integral part of today’s society. Our daily interactions, transactions, education, communication channels, work and life environments rely heavily on software. "Free Software" refers to all programs distributed under terms and licences that allow users to run the software for any purpose, ...


Running an open experiment: transparency and reproducibility in soil and ecosystem science

Environmental Research Letters, Vol. 11, No. 8. (01 August 2016), 084004,


Researchers in soil and ecosystem science, and almost every other field, are being pushed—by funders, journals, governments, and their peers—to increase transparency and reproducibility of their work. A key part of this effort is a move towards open data as a way to fight post-publication data loss, improve data and code quality, enable powerful meta- and cross-disciplinary analyses, and increase trust in, and the efficiency of, publicly-funded research. Many scientists however lack experience in, and may be unsure of the benefits ...


Five selfish reasons to work reproducibly

Genome Biology, Vol. 16, No. 1. (8 December 2015), 274,


And so, my fellow scientists: ask not what you can do for reproducibility; ask what reproducibility can do for you! Here, I present five reasons why working reproducibly pays off in the long run and is in the self-interest of every ambitious, career-oriented scientist. [Excerpt] [::Reproducibility: what's in it for me?] In this article, I present five reasons why working reproducibly pays off in the long run and is in the self-interest of every ambitious, career-oriented scientist. [::] Reason number 1: reproducibility helps to avoid ...


Enhancing reproducibility for computational methods

Science, Vol. 354, No. 6317. (09 December 2016), pp. 1240-1241,


Over the past two decades, computational methods have radically changed the ability of researchers from all areas of scholarship to process and analyze data and to simulate complex systems. But with these advances come challenges that are contributing to broader concerns over irreproducibility in the scholarly literature, among them the lack of transparency in disclosure of computational methods. Current reporting methods are often uneven, incomplete, and still evolving. We present a novel set of Reproducibility Enhancement Principles (REP) targeting disclosure challenges ...


Social software

Nature Methods, Vol. 4, No. 3. (01 March 2007), pp. 189-189,


Software that is custom-developed as part of novel methods is as important for the method's implementation as reagents and protocols. Such software, or the underlying algorithms, must be made available to readers upon publication. [Excerpt] "An inherent principle of publication is that others should be able to replicate and build upon the authors' published claims. Therefore, a condition of publication in a Nature journal is that authors are required to make materials, data and associated protocols available to readers promptly on request." ...


Why linked data is not enough for scientists

Future Generation Computer Systems, Vol. 29, No. 2. (February 2013), pp. 599-611,


[Abstract] Scientific data represents a significant portion of the linked open data cloud and scientists stand to benefit from the data fusion capability this will afford. Publishing linked data into the cloud, however, does not ensure the required reusability. Publishing has requirements of provenance, quality, credit, attribution and methods to provide the reproducibility that enables validation of results. In this paper we make the case for a scientific data publication model on top of linked data and introduce the notion of Research ...


Why policy needs philosophers as much as it needs science

The Guardian, Vol. 2016, No. October, 13. (2016), 57b3q


[Excerpt] In a widely-discussed recent essay for the New Atlantis, the policy scholar Daniel Sarewitz argues that science is in deep trouble. While modern research remains wondrously productive, its results are more ambiguous, contestable and dubious than ever before. This problem isn’t caused by a lack of funding or of scientific rigour. Rather, Sarewitz argues that we need to let go of a longstanding and cherished cultural belief – that science consists of uniquely objective knowledge that can put an end to ...


ePiX tutorial and reference manual



[Excerpt: Introduction] ePiX, a collection of batch utilities, creates mathematically accurate figures, plots, and animations containing LATEX typography. The input syntax is easy to learn, and the user interface resembles that of LATEX itself: You prepare a scene description in a text editor, then “compile” the input file into a picture. LATEX- and web-compatible output types include a LATEX picture-like environment written with PSTricks, tikz, or eepic macros; vector images (eps, ps, and pdf); and bitmapped images and movies (png, mng, and gif). [\n] ePiX’s strengths include: [::] Quality of ...


The FAIR Guiding Principles for scientific data management and stewardship

Scientific Data, Vol. 3 (15 March 2016), 160018,


There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, ...


Enabling open science: Wikidata for Research (Wiki4R)

Research Ideas and Outcomes, Vol. 1 (22 December 2015), e7573,


Wiki4R will create an innovative virtual research environment (VRE) for Open Science at scale, engaging both professional researchers and citizen data scientists in new and potentially transformative forms of collaboration. It is based on the realizations that (1) the structured parts of the Web itself can be regarded as a VRE, (2) such environments depend on communities, (3) closed environments are limited in their capacity to nurture thriving communities. Wiki4R will therefore integrate Wikidata, the multilingual semantic backbone behind Wikipedia, into ...


The hard road to reproducibility

Science, Vol. 354, No. 6308. (07 October 2016), pp. 142-142,


[Excerpt] [...] A couple years ago, we published a paper applying computational fluid dynamics to the aerodynamics of flying snakes. More recently, I asked a new student to replicate the findings of that paper, both as a training opportunity and to help us choose which code to use in future research. Replicating a published study is always difficult—there are just so many conditions that need to be matched and details that can't be overlooked—but I thought this case was relatively straightforward. ...


JRC data policy

Vol. 27163 EN (2015),


[Executive summary] The work on the JRC Data Policy followed the task identified in the JRC Management Plan 2014 to develop a dedicated data policy to complement the JRC Policy on Open Access to Scientific Publications and Supporting Guidance, and to promote open access to research data in the context of Horizon 2020. [\n] Important policy commitments and the relevant regulatory basis within the European Union and the European Commission include: the Commission Decision on the reuse of Commission documents, Commission ...


Open data: curation is under-resourced

Nature, Vol. 538, No. 7623. (05 October 2016), pp. 41-41,


[Excerpt] Science funders and researchers need to recognize the time, resources and effort required to curate open data [...]. There is no reliable business model to finance the curation and maintenance of data repositories. [...] Curation is not fully automated for most data types. This means that — in the life sciences, for example — many popular databases must resort to time-consuming manual curation to check data quality, reliability, provenance, format and metadata [...]. To make open data effective as a ...


More accountability for big-data algorithms

Nature, Vol. 537, No. 7621. (21 September 2016), pp. 449-449,


To avoid bias and improve transparency, algorithm designers must make data sources and profiles public. [Excerpt] [...] Algorithms, from the simplest to the most complex, follow sets of instructions or learn to accomplish a goal. In principle, they could help to make impartial analyses and decisions by reducing human biases and prejudices. But there is growing concern that they risk doing the opposite, and will replicate and exacerbate human failings [...]. And in an era of powerful computers, machine learning and big data, ...


Why scientists must share their research code

Nature (13 September 2016),


'Reproducibility editor' Victoria Stodden explains the growing movement to make code and data available to others. [Excerpt] [...] [::What does computational reproducibility mean?] It means that all details of computation — code and data — are made routinely available to others. If I can run your code on your data, then I can understand what you did. We need to expose all the steps that went into any discovery that relies on a computer. [::What’s the scientific value of running the same data with the ...


Transparency in ecology and evolution: real problems, real solutions

Trends in Ecology & Evolution, Vol. 31, No. 9. (September 2016), pp. 711-719,


To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there ...


Fast computing for distance covariance

Technometrics (25 June 2015), pp. 0-0,


Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O(n2) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be implemented by an O(n log n) algorithm and ...


Disciplinary action

Nature, Vol. 495, No. 7442. (27 March 2013), pp. 409-410,


How scientists share and reuse information is driven by technology but shaped by discipline. [Excerpt] [\n] [...] The transformation of research publishing is less a revolution and more a war of attrition. Battle lines were drawn long ago and all sides are well dug-in. In 2001, this journal published a series of viewpoints on the future of ‘e-access to the primary literature’ (see Those attitudes seem strikingly familiar today. At the time, the founders of the Public Library of Science initiative (then PLS, ...


1,500 scientists lift the lid on reproducibility

Nature, Vol. 533, No. 7604. (25 May 2016), pp. 452-454,


Survey sheds light on the ‘crisis’ rocking research. [Excerpt] More than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments. Those are some of the telling figures that emerged from Nature's survey of 1,576 researchers who took a brief online questionnaire on reproducibility in research. [\n] The data reveal sometimes-contradictory attitudes towards reproducibility. Although 52% of those surveyed agree that there is a significant 'crisis' of reproducibility, less than ...


Reality check on reproducibility

Nature, Vol. 533, No. 7604. (25 May 2016), pp. 437-437,


A survey of Nature readers revealed a high level of concern about the problem of irreproducible results. Researchers, funders and journals need to work together to make research more reliable. [Excerpt] Is there a reproducibility crisis in science? Yes, according to the readers of Nature. Two-thirds of researchers who responded to a survey by this journal said that current levels of reproducibility are a major problem. [\n] [...] [\n] What does ‘reproducibility’ mean? Those who study the science of science joke that the definition ...


Badges to acknowledge open practices: a simple, low-cost, effective method for increasing transparency

PLoS Biology, Vol. 14, No. 5. (12 May 2016), e1002456,


Beginning January 2014, Psychological Science gave authors the opportunity to signal open data and materials if they qualified for badges that accompanied published articles. Before badges, less than 3% of Psychological Science articles reported open data. After badges, 23% reported open data, with an accelerating trend; 39% reported open data in the first half of 2015, an increase of more than an order of magnitude from baseline. There was no change over time in the low rates of data sharing among ...


Promoting research resource identification at JCN

Journal of Comparative Neurology, Vol. 522, No. 8. (01 June 2014), pp. 1707-1707,


[Excerpt] [\n] [...] [\n] The attention of scientists, editors, and policymakers alike have all turned recently to the issue of reproducibility in scientific research, focusing on research spanning from the pharmaceutical industry (Begley and Ellis, 2012) to the highest levels of government (Collins and Tabak, 2014; see also McNutt, 2014). While these commentaries point out that scientific misconduct is quite rare, they do point to a confluence of factors that hinder the reproducibility of scientific findings, including the identification of key reagents, such ...


Updated source code for calculating fire danger indices in the Canadian Forest Fire Weather Index System

Vol. NOR-X-424 (2015)


This report presents updated versions of the FORTRAN 77 program originally published by the Canadian Forest Service in 1985 and used to calculate the Canadian forest fire weather indices from daily weather observations. The updated program is presented here in FORTRAN 95, C, C++, Python, Java and SAS/IML programming languages to meet the needs of various users. The updated versions are easier to understand and use than the original source code. The updated source codes were written in a modular programming style, consisting of a main program and ...


  1. Canadian Forestry Service. 1984. Tables for the Canadian Forest Fire Weather Index System. (4th ed.) Environ. Can., Can. For. Serv., Ottawa, ON. For. Tech. Rep. 25. Also available at .
  2. Chapman, S. J. 2004. FORTRAN 90/95 for scientists and engineers. McGraw Hill Higher Education, Toronto, ON. Also available at .
  3. De Groot, W.J.; Field, R.D.; Brady, M.A.; Roswintiarti, O.; Mohamad, M. 2006. Development of the

The Resource Identification Initiative: a cultural shift in publishing

Neuroinformatics, Vol. 14, No. 2. (2016), pp. 169-182,


A central tenet in support of research reproducibility is the ability to uniquely identify research resources, i.e., reagents, tools, and materials that are used to perform experiments. However, current reporting practices for research resources are insufficient to identify the exact resources that are reported or to answer basic questions such as “How did other studies use resource X?” To address this issue, the Resource Identification Initiative was launched as a pilot project to improve the reporting standards for research resources in ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 23

(February 2014)
Keywords: inrmm-list-of-tags   nolina-recurvata   non-array-oriented   non-equilibrium   non-linearity   non-semantic-software-errors   non-stationarity   non-wood-products   nonadditive-measures   nonideal-neurons   nonlinear-correlation   nonlinear-response-to-bioclimatic-predictors   nonmarket-impacts   nonsteady-flame-convection   north-africa   north-america   northern-europe   northern-hemisphere   norway   not-automatic-workflow   notation   notation-as-a-tool-of-thought   nothofagus-cunninghamii   nothofagus-glauca   nothofagus-nervosa   nothofagus-procera   nothofagus-pumilio   nothofagus-spp   notholithocarpus-densiflorus   nothotsuga-spp   nreap-2020   nuclear-disasters   numerical-analysis   numpy   nurse-species   nut-producing-plants   nutrient-gradient   nutrient-recommendations   nutrient-rich-soil   nutrients   nutritional-composition   nyssa-spp   nyssa-sylvatica   oak-decline   oak-hornbeam-forest   oak-shake   object-oriented-programming   occam-razor   ocean-acidification   ocean-circulation   oceans   ochroma-pyramidale   oenothera-spp   off-site-effects   ogc   olea-europaea   olea-spp   oleoresin   olive-decline   olive-oil   ombrotrophic   on-site-effects   ononis-fruticosa   ontologies   open-access   open-access-embargo   open-data   open-field   open-loop-control   open-science   open-source   opengis   openlayers   openstreetmap   operational-research   operophtera-antiqua   operophtera-brumata   ophiostoma-novo-ulmi   ophiostoma-spp   ophiostoma-ulmi   opportunistic-plant-pests   optimization   opuntia-amyclaea   opuntia-ficus-indica   oregon   organic-carbon   organic-material   ornamental-plant   ornamental-trees   orthotomicus-laricis   ostrya-carpinifolia   ostrya-spp   ostryopsis-spp   otiorhynchus-scaber   outbreak   outdated-yield-tables   outputs-vs-outcomes   overexploited-fish-stocks   overfitting  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


Research integrity: don't let transparency damage science

Nature, Vol. 529, No. 7587. (25 January 2016), pp. 459-461,


Stephan Lewandowsky and Dorothy Bishop explain how the research community should protect its members from harassment, while encouraging the openness that has become essential to science. [Excerpt] Transparency has hit the headlines. In the wake of evidence that many research findings are not reproducible1, the scientific community has launched initiatives to increase data sharing, transparency and open critique. As with any new development, there are unintended consequences. Many measures that can improve science2 — shared data, post-publication peer review and public engagement ...


Changes in data sharing and data reuse practices and perceptions among scientists worldwide

PLoS ONE, Vol. 10, No. 8. (26 August 2015), e0134826,


The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers ...


Author sequence and credit for contributions in multiauthored publications

PLoS Biology, Vol. 5, No. 1. (16 January 2007), e18,


A transparent, simple, and straightforward approach that is free from any arbitrary rank valuation is required to estimate the credit associated with the sequence of authors' names on multiauthored papers. [Excerpt] The increasing tendency across scientific disciplines to write multiauthored papers [1,2] makes the issue of the sequence of contributors' names a major topic both in terms of reflecting actual contributions and in a posteriori assessments by evaluation committees. Traditionally, the first author contributes most and also receives most of the credit, ...


The integration of land change modeling framework FUTURES into GRASS GIS 7

In Free and Open Source Software for Geospatial - Open innovation for Europe, Vol. 12 (2015), pp. 21-24


Many valuable models and tools developed by scientists are often inaccessible to their potential users because of non-existent sharing infrastructure or lack of documentation. Case in point is the FUTure Urban-Regional Environment Simulation (FUTURES), a patch-based land change model for generating scenario-based regional forecasts of urban growth pattern. Despite a high- impact publication, few scientists, planners, or policy makers have adopted FUTURES due to complexity in use and lack of direct access. We seek to address these issues by integrating FUTURES into GRASS GIS, a free and open source ...


  1. Bivand, R. (2007). Using the R–Grass interface. OSGeo Journal, 1, 36-38.
  2. Chemin, Y Petras, V., Petrasova, A., Landa, M., Gebbert, S., Zambelli, P., Neteler, M., Löwe, P., Di Leo, M. (2015). GRASS GIS: a peer-reviewed scientific platform and future research repository. Geophysical Research Abstracts 17, 8314+. INRMM-MiD:13544126
  3. Di Leo, M., de Rigo, D., Rodriguez-Aseretto, D., Bosco, C., Petroliagkis, T., Camia, A., San-Miguel-Ayanz, J. (2013). Dynamic data driven ensemble for wildfire behaviour

The future of science will soon be upon us

Nature, Vol. 524, No. 7564. (12 August 2015), pp. 137-137,


The European Commission has abandoned consideration of 'Science 2.0', finding it too ambitious. That was the wrong call, says Colin Macilwain. [Excerpt] As the staff of the European Commission head for the beaches this August, they have been asked to ponder the future of science. Research commissioner Carlos Moedas has announced his priorities as being “open science” and “open innovation”, and invited his team to report back with its ideas on how to achieve that. [\n] These goals sound laudable enough, but they're ...


The case for open preprints in biology

PLoS Biology, Vol. 11, No. 5. (14 May 2013), e1001563,


Biologists should submit their preprints to open servers, a practice common in mathematics and physics, to open and accelerate the scientific process. [Excerpt: Introduction] Public preprint servers allow authors to make manuscripts publicly available before, or in parallel to, submitting them to journals for traditional peer review. The rationale for preprint servers is fundamentally simple: to make the results of research available to the scientific community as soon as possible, instead of waiting until the peer-review process is fully completed. Sharing manuscripts using ...


An open investigation of the reproducibility of cancer biology research

eLife, Vol. 3 (10 dec 2014), e04333,
edited by Peter Rodgers


It is widely believed that research that builds upon previously published findings has reproduced the original work. However, it is rare for researchers to perform or publish direct replications of existing results. The Reproducibility Project: Cancer Biology is an open investigation of reproducibility in preclinical cancer biology research. We have identified 50 high impact cancer biology articles published in the period 2010-2012, and plan to replicate a subset of experimental results from each article. A Registered Report detailing the proposed experimental ...


Time to do something about reproducibility

eLife, Vol. 3 (10 December 2014), e03981,


Individual scientists, scientific communities and scientific journals can do more to assess the publication of irreproducible results, to promote good science, and to increase the efficiency with which the scientific community self-corrects. ...


Reproducible research can still be wrong: adopting a prevention approach

Proceedings of the National Academy of Sciences, Vol. 112, No. 6. (11 February 2015), pp. 1645-1646,


[Excerpt] Reproducibility—the ability to recompute results—and replicability—the chances other experimenters will achieve a consistent result—are two foundational characteristics of successful scientific research. Consistent findings from independent investigators are the primary means by which scientific evidence accumulates for or against a hypothesis. Yet, of late, there has been a crisis of confidence among researchers worried about the rate at which studies are either reproducible or replicable. To maintain the integrity of science research and the public’s trust in science, the scientific community ...

Visual summary


Open code for open science?

Nature Geoscience, Vol. 7, No. 11. (30 October 2014), pp. 779-781,


Open source software is often seen as a path to reproducibility in computational science. In practice there are many obstacles, even when the code is freely available, but open source policies should at least lead to better quality code. ...


Knowledge Freedom in computational science: a two stage peer-review process with KF eligibility access review



Wide scale transdisciplinary modelling (WSTM) growingly demands a focus on reproducible research and scientific knowledge freedom. Data and software freedom are essential aspects of knowledge freedom in computational science. Therefore, ideally published articles should also provide the readers with the data and source code of the described mathematical modelling. To maximise transparency, replicability, reproducibility and reusability, published data should be made available as open data while source code should be made available as free software. Here, a two-stage peer review process ...

Visual summary


The Open Science Peer Review Oath

F1000Research (12 November 2014),


One of the foundations of the scientific method is to be able to reproduce experiments and corroborate the results of research that has been done before. However, with the increasing complexities of new technologies and techniques, coupled with the specialisation of experiments, reproducing research findings has become a growing challenge. Clearly, scientific methods must be conveyed succinctly, and with clarity and rigour, in order for research to be reproducible. Here, we propose steps to help increase the transparency of the scientific ...


  1. Ioannidis JP: Why most published research findings are false. PLoS Med. 2005; 2(8): e124.
  2. Ioannidis JP, Allison DB, Ball CA, et al.: Repeatability of published microarray gene expression analyses. Nat Genet. 2009; 41(2): 149–55.
  3. Prinz F, Schlange T, Asadullah K: Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov. 2011; 10(9): 712.
  4. Hines WC,

Openness in science is key to keeping public trust

Nature, Vol. 515, No. 7527. (19 November 2014), pp. 313-313,


Silence stifles progress, says Mark Yarborough. The scientific enterprise needs a transparent culture that actively finds and fixes problems. [Excerpt] The Ebola crisis demonstrates once again that, despite all the posturing of politicians, it is scientists who the public looks to in times of crisis and concern. The public still trusts scientists. A UK survey this year found that they trust scientists even if they do not always trust scientific information itself. Still, the public’s trust is fragile. Given how much scientists ...


Code share

Nature, Vol. 514, No. 7524. (29 October 2014), pp. 536-536,


Papers in Nature journals should make computer code accessible where possible. [Excerpt] A theme in Nature’s ongoing campaign for the replicability and reproducibility of our research papers is that key components of publications should be available to peers who wish to validate the techniques and results. A core element of many papers is the computercode used by authors in models, simulations and data analysis. In an ideal world, this code would always be transportable and easily used by others. In such a ...


Supporting environmental and energy decisions through an open software structure

In Proceedings of the iEMSs Third Biennial Meeting: "Summit on Environmental Modelling and Software" (July 2006)


Public participation to environmental planning and management decisions, as suggested by local Agenda 21 processes, can be supported by software tools developed with a cyclic interaction with all the stakeholders and simple enough to be quickly operated by a large set of heterogeneous users. This also helps preventing their rapid aging and their excessive dependence on changing technologies. We experimented the development of such software tools using an Office type environment to store data, analyse, and geographically represent the effects of ...


Online collaboration: scientists and the social network

Nature, Vol. 512, No. 7513. (13 August 2014), pp. 126-129,


Giant academic social networks have taken off to a degree that no one expected even a few years ago. A Nature survey explores why. ...


Interactive comment on "Perturbation experiments to investigate the impact of ocean acidification: approaches and software tools" by J.-P. Gattuso and H. Lavigne

Biogeosciences Discussions, Vol. 6 (2009), pp. C1071-C1073


[Excerpt] The referee wonders whether this manuscript should be published as a technical note rather than as a scientific article […][and] feels that the functions described are “black boxes”. We cannot disagree more with this statement as [the software tool] is free software, the source code of which is available to anyone (one just needs to download the package). Further, [the software tool] can be redistributed and/or modified under the terms of the GNU General Public License as published by the ...


Open sourcing ecological data

BioScience, Vol. 57, No. 4. (01 April 2007), pp. 309-310,


In a thought-provoking Viewpoint, Cassey and Blackburn (2006) suggest that reproducibility should not be required of ecological studies. Thus, ecological journals should not require authors to publish data as a requirement of publication, nor should reviewers insist on it. Cassey and Blackburn make three cautionary points: First, the goal of reproducibility should not be applied piecemeal. Second, journals are not ready for custodianship of data. Third, publishing data places the intellectual rights of authors at risk under the current reward system. ...


Open access: sharing your data is easier than you think

Nature, Vol. 510, No. 7505. (18 June 2014), pp. 340-340,


[excerpt] [...] Storing large volumes of raw data is costly, but many items destined for sharing are highly processed and relatively small. [...] Neither is there a shortage of repositories: many institutional databases are freely available and well supported [...], sharing computer code does not necessarily demand much time investment (see, for example, D. C. Ince et al. Nature 482, 485–488; 2012). Code is a valuable part of a paper, so everyone benefits if its authors assume from the start that it ...

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Integrated Natural Resources Modelling and Management - Meta-information Database.

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Publication metadata

Bibtex, RIS, RSS/XML feed, Json, Dublin Core

Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.