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Selection: with tag data-collection-bias [8 articles] 

 

Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

  
Ecography, Vol. 40, No. 8. (1 August 2017), pp. 913-929, https://doi.org/10.1111/ecog.02881

Abstract

Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also ...

 

Integrating biodiversity distribution knowledge: toward a global map of life

  
Trends in Ecology & Evolution, Vol. 27, No. 3. (March 2012), pp. 151-159, https://doi.org/10.1016/j.tree.2011.09.007

Abstract

Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses. The ultimate ...

 

Using citizen science data to estimate climatic niches and species distributions

  
Basic and Applied Ecology, Vol. 20 (May 2017), pp. 75-85, https://doi.org/10.1016/j.baae.2017.04.001

Abstract

Opportunistic citizen data documenting species observations – i.e. observations collected by citizens in a non-standardized way – is becoming increasingly available. In the absence of scientific observations, this data may be a viable alternative for a number of research questions. Here we test the ability of opportunistic species records to provide predictions of the realized distribution of species and if species attributes can act as indicators of the reliability and completeness of these data. We use data for 39 reptile and ...

 

Spatial distribution of citizen science casuistic observations for different taxonomic groups

  
Scientific Reports, Vol. 7, No. 1. (16 October 2017), https://doi.org/10.1038/s41598-017-13130-8

Abstract

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution ...

 

The uncertain nature of absences and their importance in species distribution modelling

  
Ecography, Vol. 33, No. 1. (1 February 2010), pp. 103-114, https://doi.org/10.1111/j.1600-0587.2009.06039.x

Abstract

Species distribution models (SDM) are commonly used to obtain hypotheses on either the realized or the potential distribution of species. The reliability and meaning of these hypotheses depends on the kind of absences included in the training data, the variables used as predictors and the methods employed to parameterize the models. Information about the absence of species from certain localities is usually lacking, so pseudo-absences are often incorporated to the training data. We explore the effect of using different kinds of ...

 

Reproducibility: a tragedy of errors

  
Nature, Vol. 530, No. 7588. (3 February 2016), pp. 27-29, https://doi.org/10.1038/530027a

Abstract

Mistakes in peer-reviewed papers are easy to find but hard to fix, report David B. Allison and colleagues. [Excerpt: Three common errors] As the influential twentieth-century statistician Ronald Fisher (pictured) said: “To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.” [\n] [...] Frequent errors, once recognized, can be kept out of the literature with targeted education and policies. Three of the most common are ...

 

Rise of the citizen scientist

  
Nature, Vol. 524, No. 7565. (18 August 2015), pp. 265-265, https://doi.org/10.1038/524265a

Abstract

From the oceans to the soil, technology is changing the part that amateurs can play in research. But this greater involvement raises concerns that must be addressed. [Excerpt] [...] Citizen science has come a long way from the first distributed-computing projects that hoovered up spare processing power on home computers to perform calculations or search for alien signals. And it has progressed further still since the earliest public surveys of wildlife: it was way back in 1900 that the Audubon Society persuaded ...

 

(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 11

  
(February 2014)
Keywords: 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   database   dataset   dating   davidsoniella-virescens   dbh   dddas   de-facto-standard   dead-wood   debris   debris-floods   debris-flows   deciduous   deciduous-forest   decision-making   decision-making-procedure   decision-support-system   decline   decline-effect   decline-symptomology   deep-learning   deep-machine-learning   deep-reproducible-research   deep-uncertainty   defensible-space   definition   defoliation   deforestation   degenerated-soil   deglaciation   degradation   degradation-velocity   dehesas   delay   delonix-regia   democracy   demographic-indicators   dendrochronology   dendroctonus-frontalis   dendroctonus-micans   dendroctonus-ponderosae   dendroctonus-pseudotsugae   dendroctonus-rufipennis   dendroctonus-spp   dendroecology   dendrology   denmark   density-related-behaviour   deposition   derived-data   desalinisation   description   desertification   deserts   design-diversity   development   devil-in-details   diabetes   diabetes-mellitus   diagram-data   diameter-differentiation   dictionary   dictyophara-europea   die-off   dieback   diesel   difference   differentiation   digital-preservation   digital-society   dimensional-analysis   dimensionality-reduction   dimensionless   dioryctria-splendidella   dioscorea-caucasica   diospyros-kaki   diospyros-lotus   diospyros-spp   diospyros-virginiana   diplodia-pinea   inrmm-list-of-tags  

Abstract

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 ( http://mfkp.org/INRMM/tag/inrmm-list-of-tags ). ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database. http://mfkp.org/INRMM/tag/data-collection-bias

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.