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Selection: with tag data-sharing [47 articles] 


SoilGrids250m: Global gridded soil information based on machine learning

PLOS ONE, Vol. 12, No. 2. (16 February 2017), e0169748,


This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference ...


SoilGrids1km - Global soil information based on automated mapping

PLOS ONE, Vol. 9, No. 8. (29 August 2014), e105992,


Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. We present SoilGrids1km â a global 3D soil information system at 1 km resolution â containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kgâ1), soil pH, sand, silt and ...


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 ...


Core trustworthy data repositories requirements



The Core Trustworthy Data Repository Requirements were developed by the DSA–WDS Partnership Working Group on Repository Audit and Certification, a Working Group (WG) of the Research Data Alliance . The goal of the effort was to create a set of harmonized common requirements for certification of repositories at the core level, drawing from criteria already put in place by the Data Seal of Approval (DSA: and the ICSU World Data System (ICSU-WDS: An additional goal of the project was ...


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 ...


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, ...


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 ...


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 ...


Brain and Behavior: we want you to share your data

Brain and Behavior, Vol. 4, No. 1. (January 2014), pp. 1-3,


We at Brain and Behavior are happy, for one, that data sharing is now here. [Excerpt] [...] Many reasons are given as to why we cannot, do not, or should not make data available (e.g., Strasser 2013; Wallis et al. 2013), but I think that the main reason we do not routinely share data is that, until recently, we could not. And because we could not, a system of scholarly communication grew where data were disposable. Literally. Eventually, the boxes piled upon ...


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 ...


Funders must encourage scientists to share

Nature, Vol. 522, No. 7555. (11 June 2015), pp. 129-129,


To realize the full potential of large data sets, researchers must agree on better ways to pass data around, says Martin Bobrow. [Excerpt] How can we make best use of the vast amounts of data on genomics, epidemiology and population-level health being collected by researchers? Maximizing the benefits depends on how well we as a scientific community share information. [...] [\n] Both those who generate data and those who want to use them expressed frustration at the way that data-access processes are ...


Data reuse and the open data citation advantage

PeerJ, Vol. 1 (01 October 2013), e175,


[Background] Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the “citation benefit”. Furthermore, ...


Nine simple ways to make it easier to (re)use your data

Ideas in Ecology and Evolution, Vol. 6, No. 2. (2013),


Sharing data is increasingly considered to be an important part of the scientific process. Making your data publicly available allows original results to be reproduced and new analyses to be conducted. While sharing your data is the first step in allowing reuse, it is also important that the data be easy to understand and use. We describe nine simple ways to make it easy to reuse the data that you share and also make it easier to work with it yourself. ...


Data archiving

The American Naturalist, Vol. 175, No. 2. (February 2010), pp. 145-146,


[Excerpt] Science depends on good data. Data are central to our understanding of the natural world, yet most data in ecology and evolution are lost to science—except perhaps in summary form—very quickly after they are collected. Once the results of a study are published, the data on which those results are based are often stored unreliably, subject to loss by hard drive failure and (even more likely) by the researcher forgetting the specific details required to use the data (Michener et ...


Observational articles: a tool to reconstruct ecological history based on chronicling unusual events

F1000Research, Vol. 2 (9 August 2013), 168,


Natural history is based on observations, whereas modern ecology is mostly based on experiments aimed at testing hypotheses, either in the field or in a computer. Furthermore, experiments often reveal generalities that are taken as norms. Ecology, however, is a historical discipline and history is driven by both regularities (deriving from norms) and irregularities, or contingencies, which occur when norms are broken. If only norms occured, there would be no history. The current disregard for the importance of contingencies and anecdotes ...


Data, eternal

Science, Vol. 347, No. 6217. (02 January 2015), pp. 7-7,


[Excerpt] During 2014, Science worked with members of the research community, other publishers, and representatives of funding agencies on many initiatives to increase transparency and promote reproducibility in the published research literature. Those efforts will continue in 2015. Connected to that progress, and an essential element to its success, an additional focus will be on making data more open, easier to access, more discoverable, and more thoroughly documented. My own commitment to these goals is deeply held, for I learned early in ...


microclim: Global estimates of hourly microclimate based on long-term monthly climate averages

Scientific Data, Vol. 1 (27 May 2014),


The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic ...

Visual summary


EPPO Global Database



EPPO Global Database is maintained by the Secretariat of the European and Mediterranean Plant Protection Organization (EPPO). This database is still under development but its ultimate goal is to include all pest-specific information that has been produced by EPPO. ...


Give, and it will be given to you



[Excerpt] In 2007, quantitative ecologist Karthik Ram sought to find out why certain insect parasites appeared in some sand dunes but not others. Ram, who was a graduate student at the time, thought that asking scientists for field data used in the papers they published was no big deal. But the scientists he e-mailed ignored his requests, so Ram, then at the University of California (UC), Davis, had to collect extra insect samples. Later, as he studied how climate change was impacting ...


The conundrum of sharing research data

J Am Soc Inf Sci Tec, Vol. 63, No. 6. (1 June 2012), pp. 1059-1078,


We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts, ) Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data ...


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 ...


Biodiversity data should be published, cited, and peer reviewed

Trends in Ecology & Evolution, Vol. 28, No. 8. (August 2013), pp. 454-461,


Knowledge depends on data and thus data quality. Data publication needs quality assurance standards like conventional publications. Peer review is the highest standard in scientific publications. Indicators for biodiversity data quality, including peer review, are proposed. Concerns over data quality impede the use of public biodiversity databases and subsequent benefits to society. Data publication could follow the well-established publication process: with automated quality checks, peer review, and editorial decisions. This would improve data accuracy, reduce the need for users to ‘clean’ ...


Data publication consensus and controversies

F1000Research (16 May 2014),


The movement to bring datasets into the scholarly record as first class research products (validated, preserved, cited, and credited) has been inching forward for some time, but now the pace is quickening. As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention. Data publication implementations differ in a variety of factors, including the kind of ...


Implementing reproducible research

by Alexander A. Aarts, Anita Alexander, Peter Attridge, Štěpán Bahník, Michael Barnett-Cowan, Elizabeth Bartmess, Frank A. Bosco, Mikio Braun, Benjamin Brown, C. Titus Brown, Kristina Brown, Jesse J. Chandler, Russ Clay, Hayley Cleary, Michael Cohn, Giulio Costantini, Jan Crusius, Andrew Davison, Jamie DeCoster, Michelle DeGaetano, Ryan Donohue, Elizabeth Dunn, Scott Edmunds, Casey Eggleston, Vivien Estel, Frank J. Farach, Susann Fiedler, James G. Field, Stanka Fitneva, Ian Foster, Joshua D. Foster, Rebecca S. Frazier, Juliana Freire, Elisa M. Galliani, Roger Giner-Sorolla, Lars Goellner, R. Justin Goss, Jesse Graham, James A. Grange, Philip Guo, Joshua Hartshorne, Timothy B. Hayes, Grace Hicks, Holger Hoefling, Bill Howe, Iain Hrynaszkiewicz, Denise Humphries, Christophe Hurlin, Luis Ibanez, Georg Jahn, Kate Johnson, Jennifer A. Joy-Gaba, Heather B. Kappes, Calvin K. Lai, Daniel Lakens, Kristin A. Lane, Etienne P. LeBel, Minha Lee, Kristi Lemm, Melissa Lewis, Stephanie C. Lin, Peter Li, Sean Mackinnon, Heather Mainard, Tanu Malik, Nathaniel Mann, Michael May, Jarrod Millman, Katherine Moore, Matt Motyl, Stephanie M. Müller, Dave Murray-Rust, Peter Murray-Rust, Brian A. Nosek, Catherine Olsson, Cheng S. Ong, Fernando Perez, Christophe Perignon, Marco Perugini, Quan Pham, Michael Pitts, Kate Ratliff, Frank Renkewitz, Anthony Rossini, Abraham M. Rutchick, Gillian Sandstrom, Dylan Selterman, William Simpson, Colin T. Smith, Jeffrey R. Spies, Victoria Stodden, Thomas Talhelm, Anna Veer, Michelangelo Vianello, Yihui Xie


In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal ...


Share alike

Nature, Vol. 507, No. 7491. (12 March 2014), pp. 140-140,


Research communities need to agree on standard etiquette for data-sharing. [Excerpt] In many fields, making research data available online for all is a step beyond making research papers open-access. This might puzzle communities that have already agreed to share. [...] Communities need to debate the ethics of data-sharing and agree on etiquette. When a researcher relies on another’s data, for example, it should be standard practice to invite the data-providers to be co-authors. Ecologists Clifford Duke and John Porter have suggested guidelines ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 9

(February 2014)
Keywords: crataegus-azarolus   crataegus-laevigata   crataegus-monogyna   crataegus-nigra   crataegus-spp   creative-commons   crescentia-cujete   crimean-mountains   crisis   croatia   crocidura-suaveolens   cronartium-ribicola   crop-yield   crops   cross-disciplinary-perspective   crowd-sourcing   crowdfunding   crowdsourcing   crown-copyright   crown-diameter   cryphalus-piceae   cryphonectria-parasitica   crypmmeria-japonica   cryptomeria-fortunei   cryptomeria-japonica   cryptomeria-spp   cryptorhynchus-lapathi   cultivars   cultivated   cultivated-plants   cultural-services   cunninghamia-lanceolata   cupressaceae   cupressus-abramsiana   cupressus-arizonica   cupressus-atlantica   cupressus-bakeri   cupressus-cashmeriana   cupressus-dupreziana   cupressus-funebris   cupressus-goveniana   cupressus-guadalupensis   cupressus-lusitanica   cupressus-macnabiana   cupressus-macrocarpa   cupressus-pygmaea   cupressus-sargentii   cupressus-sempervirens   cupressus-torulosa   curculio-elephas   curiosity   curse-of-dimensionality   cut-timber   cyanobacteria   cyathea-arborea   cyber-security   cybernetics   cyc   cycadopsida   cyclocarya-paliurus   cyclomatic-complexity   cyclone   cyclostationarity   cydonia-oblonga   cylindrocladium-quinqueseptatum   cyprus   cystopteris-spp   cytisus-scoparius   czech-republic   daboecia-cantabrica   dacryodes-excelsa   danube-basin   daphne-blagayana   daphne-cneorum   daphne-laureola   daphne-mezereum   daphne-pontica   daphniphyllum-oldhamii   dasineura-salicis   data   data-acquisition   data-based-mechanistic-modelling   data-breach   data-collection-bias   data-errors   data-fusion   data-heterogeneity   data-integration   data-lineage   data-model-comparison   data-provenance   data-quality   data-scarcity   data-sharing   data-transformation-codelets   data-transformation-modelling   data-transformation-modelling-dynamic   data-uncertainty   inrmm-list-of-tags  


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 ( ). ...


Ten simple rules for reproducible computational research

PLoS Computational Biology, Vol. 9, No. 10. (24 October 2013), e1003285,


[Excerpt] The importance of replication and reproducibility has recently been exemplified through studies showing that scientific papers commonly leave out experimental details essential for reproduction [5], studies showing difficulties with replicating published experimental results [6], an increase in retracted papers [7], and through a high number of failing clinical trials [8], [9]. This has led to discussions on how individual researchers, institutions, funding bodies, and journals can establish routines that increase transparency and reproducibility. In order to foster such aspects, it ...


On the reproducibility of science: unique identification of research resources in the biomedical literature

PeerJ, Vol. 1 (05 September 2013), e148,


Scientific reproducibility has been at the forefront of many news stories and there exist numerous initiatives to help address this problem. We posit that a contributor is simply a lack of specificity that is required to enable adequate research reproducibility. In particular, the inability to uniquely identify research resources, such as antibodies and model organisms, makes it difficult or impossible to reproduce experiments even where the science is otherwise sound. In order to better understand the magnitude of this problem, we ...


Delivering the goods: scaling out results of natural resource management research

Ecology and Society, Vol. 5, No. 2. (2001), 19+


To help integrated natural resource management (INRM) research "deliver the goods" for many of the world's poor over a large area and in a timely manner, the authors suggest a problem-solving approach that facilitates the scaling out of relevant agricultural practices. They propose seven ways to foster scaling out: (1) develop more attractive practices and technologies through participatory research (2) balance supply-driven approaches with resource user demands, (3) use feedback to redefine the research agenda, (4) encourage support groups and networks ...


Toward reproducible computational research: an empirical analysis of data and code policy adoption by journals

PLOS ONE, Vol. 8, No. 6. (21 June 2013), pp. e67111-e67111,


Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data ...


Who will pay for public access to research data?

Science (New York, N.Y.), Vol. 341, No. 6146. (9 August 2013), pp. 616-617,


On 22 February, the U.S. Office of Science and Technology Policy (OSTP) released a memo calling for public access for publications and data resulting from federally sponsored research grants (1). The memo directed federal agencies with more than $100 million R&D expenditures to “develop a plan to support increased public access to the results of research funded by the Federal Government.” Perhaps even more succinctly, a subsequent New York Times opinion page sported the headline “We Paid for the Research, So ...


Data-sharing: everything on display

Nature, Vol. 500, No. 7461. (7 August 2013), pp. 243-245,


Lizzie Wolkovich always felt she ought to make her research data freely available online. “The idea that data should be public has been in the background through my entire career,” she says. ...


If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology

PLoS ONE, Vol. 8, No. 7. (23 July 2013), pp. e67332-e67332,


Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but ...


Better living through transparency: improving the reproducibility of fMRI results through comprehensive methods reporting

In Cognitive, Affective, & Behavioral Neuroscience (2013), pp. 1-7,


Recent studies suggest that a greater proportion of published scientific findings than expected cannot be replicated. The field of functional neuroimaging research is no exception to this trend, with estimates of false positive results ranging from 10 % to 40 %. While false positive results in neuroimaging studies stem from a variety of causes, incomplete methodological reporting is perhaps the most obvious: Most published reports of neuroimaging studies provide ambiguous or incomplete descriptions of their methods and results. If neuroimaging researchers do not ...


Open your minds and share your results

Nature, Vol. 486, No. 7404. (27 June 2012), pp. 441-441,


An open approach is the best way to maximize the benefits of research for both scientists and the public, says Geoffrey Boulton ...


Open science is a research accelerator

Nature Chemistry, Vol. 3, No. 10. (23 September 2011), pp. 745-748,


An open-source approach to the problem of producing an off-patent drug in enantiopure form serves as an example of how academic and industrial researchers can join forces to make new scientific discoveries that could have a huge impact on human health. ...


Scientific communication is down at the moment, please check again later

Psychological Inquiry, Vol. 23, No. 3. (1 July 2012), pp. 267-270,


Brian A. Nosek and Yoav Bar-Anan (this issue) offer a futuristic utopia on how scientific communication might work to the maximal benefit of science. I am highly sympathetic and even enthusiastic about the hallmarks of the changes that they propose. Their road map revolves around the principles of improving efficiency, transparency, openness, and maximal participation in the dissemination of scientific information. Almost all of the components of their utopia are in fact already applied or piloted in different scientific fields, so ...


Open access to data: an ideal professed but not practised

Social Science Research Network Working Paper Series (26 February 2013)


We provide evidence for the status quo in economics with respect to data sharing using a unique data set with 488 hand-collected observations randomly taken from researchers' academic webpages. Out of the sample, 435 researchers (89.14%) neither have a data&code section nor indicate whether and where their data is available. We find that 8.81% of researchers share some of their data whereas only 2.05% fully share. We run an ordered probit regression to relate the decision of researchers to share to ...


Publishing frontiers: the library reboot

Nature, Vol. 495, No. 7442. (27 March 2013), pp. 430-432,


As scientific publishing moves to embrace open data, libraries and researchersare trying to keep up. ...


Advances in global change research require open science by individual researchers

Global Change Biology, Vol. 18, No. 7. (1 July 2012), pp. 2102-2110,


Understanding how species and ecosystems respond to climate change requires spatially and temporally rich data for a diverse set of species and habitats, combined with models that test and predict responses. Yet current study is hampered by the long-known problems of inadequate management of data and insufficient description of analytical procedures, especially in the field of ecology. Despite recent institutional incentives to share data and new data archiving infrastructure, many ecologists do not archive and publish their data and code. Given ...


Sharing Detailed Research Data Is Associated with Increased Citation Rate

PLOS ONE In PLoS ONE, Vol. 2, No. 3. (21 March 2007), pp. e308-e308,


Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of ...


Exploring the determinants of scientific data sharing: Understanding the motivation to publish research data

Government Information Quarterly, Vol. 30 (January 2013), pp. S19-S31,


The research community is working to create new capabilities to share data and to deal with issues of data quality, standards, and protection, and ethical and responsible use of shared data. These issues have been found to influence the willingness of researchers to publish data created during the course of their research. We use the results of a survey conducted by the working groups of the DataONE project to present a new understanding of challenges to the development of global data ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database.

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:
Search only within the INRMM-MiD publication records:
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.