A survey of biodiversity informatics: Concepts, practices, and challenges
暂无分享,去创建一个
Luiz M. R. Gadelha | Eduardo Krempser | Maria Luiza Mondelli | Marcia Chame | Artur Ziviani | Luís Alexandre Estevão da Silva | Pedro C. de Siracusa | Luiz M. R. Gadelha | Pedro C. Siracusa | Eduardo Couto Dalcin | Luís Alexandre Estevão Silva | Douglas A. Augusto | Helen Michelle Affe | Raquel Lopes Costa | Maria Luiza Mondelli | Pedro Milet Meirelles | Fabiano Thompson | Marinez Ferreira Siqueira | Helen Michelle Affe | M. F. Siqueira | A. Ziviani | F. Thompson | R. L. Costa | Eduardo Krempser | D. A. Augusto | E. Dalcin | P. Meirelles | M. Chame
[1] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[2] Craig Moritz,et al. Biodiversity analysis in the digital era , 2016, Philosophical Transactions of the Royal Society B: Biological Sciences.
[3] Lionel Guy,et al. Deep mitochondrial origin outside the sampled alphaproteobacteria , 2018, Nature.
[4] David O. Holmes,et al. Improving precision and recall for Soundex retrieval , 2002, Proceedings. International Conference on Information Technology: Coding and Computing.
[5] M. Schatz,et al. Big Data: Astronomical or Genomical? , 2015, PLoS biology.
[6] Jesse Cleary,et al. Data integration for conservation: Leveraging multiple data types to advance ecological assessments and habitat modeling for marine megavertebrates using OBIS-SEAMAP , 2014, Ecol. Informatics.
[7] Nicholas Chrisman,et al. Part 2: Issues and Problems Relating to Cartographic Data Use, Exchange and Transfer: The Role Of Quality Information In The Long-Term Functioning Of A Geographic Information System , 1984 .
[8] D. R. Cutler,et al. Utah State University From the SelectedWorks of , 2017 .
[9] F. Frentiu. Ecological Niches: Linking Classical and Contemporary Approaches , 2004 .
[10] R. Guralnick,et al. Biodiversity informatics: automated approaches for documenting global biodiversity patterns and processes , 2009, Bioinform..
[11] Javier Otegui,et al. The GBIF Integrated Publishing Toolkit: Facilitating the Efficient Publishing of Biodiversity Data on the Internet , 2014, PloS one.
[12] A. Peterson,et al. Ecologic niche modeling and differentiation of populations of Triatoma brasiliensis neiva, 1911, the most important Chagas' disease vector in northeastern Brazil (hemiptera, reduviidae, triatominae). , 2002, The American journal of tropical medicine and hygiene.
[13] Fred W. Glover,et al. Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..
[14] A. Townsend Peterson,et al. Rethinking receiver operating characteristic analysis applications in ecological niche modeling , 2008 .
[15] Ulrik Brandes,et al. What is network science? , 2013, Network Science.
[16] A. Peterson,et al. Biodiversity informatics: managing and applying primary biodiversity data. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[17] Bertram Ludäscher,et al. Kurator: Tools for Improving Fitness for Use of Biodiversity Data. , 2018 .
[18] Philip S. Yu,et al. Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.
[19] Albert Y. Zomaya,et al. A Survey of Mobile Device Virtualization , 2016, ACM Comput. Surv..
[20] John C. Wooley,et al. A Primer on Metagenomics , 2010, PLoS Comput. Biol..
[21] R. Lourenço-de-Oliveira,et al. Potential risk of re-emergence of urban transmission of Yellow Fever virus in Brazil facilitated by competent Aedes populations , 2017, Scientific Reports.
[22] F. Bisby. The quiet revolution: biodiversity informatics and the internet. , 2000, Science.
[23] J L Edwards,et al. Interoperability of biodiversity databases: biodiversity information on every desktop. , 2000, Science.
[24] Néstor Fernández,et al. Essential Biodiversity Variables: Integrating In-Situ Observations and Remote Sensing Through Modeling , 2020, Remote Sensing of Plant Biodiversity.
[25] Roderic D. M. Page,et al. Biodiversity informatics: the challenge of linking data and the role of shared identifiers , 2008, Briefings Bioinform..
[26] F. Chapin,et al. Consequences of changing biodiversity , 2000, Nature.
[27] Sergey I. Nikolenko,et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing , 2012, J. Comput. Biol..
[28] M. Cadotte. Ecological Niches: Linking Classical and Contemporary Approaches , 2004, Biodiversity & Conservation.
[29] David B. Lindenmayer,et al. DYNAMIC SPECIES CO–OCCURRENCE NETWORKS REQUIRE DYNAMIC BIODIVERSITY SURROGATES , 2016 .
[30] Carlos Peña,et al. VoSeq: A Voucher and DNA Sequence Web Application , 2012, PloS one.
[31] Edward C Holmes,et al. Evolutionary history and phylogeography of human viruses. , 2008, Annual review of microbiology.
[32] Elisa Thébault,et al. Identifying compartments in presence–absence matrices and bipartite networks: insights into modularity measures , 2013 .
[33] F. Grassle. The Ocean Biogeographic Information System (OBIS): An On-line, Worldwide Atlas for Accessing, Modeling and Mapping Marine Biological Data in a Multidimensional Geographic Context , 2000 .
[34] Lindsay P. Campbell,et al. NicheA: creating virtual species and ecological niches in multivariate environmental scenarios , 2016 .
[35] Seth Kaufman,et al. MorphoBank: phylophenomics in the “cloud” , 2011, Cladistics : the international journal of the Willi Hennig Society.
[36] A. Townsend Peterson,et al. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas , 2012 .
[37] R. G. Davies,et al. Methods to account for spatial autocorrelation in the analysis of species distributional data : a review , 2007 .
[38] J Elith,et al. A working guide to boosted regression trees. , 2008, The Journal of animal ecology.
[39] Walter G. Berendsohn,et al. The concept of "potential taxa" in databases , 1995 .
[40] Arthur Korte,et al. Arabidopsis thaliana AUCSIA-1 Regulates Auxin Biology and Physically Interacts with a Kinesin-Related Protein , 2012, PloS one.
[41] A. Peterson. Uses and requirements of ecological niche models and related distributional models , 2006 .
[42] Steven J. Phillips,et al. WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS? , 2007 .
[43] Renzo Kottmann,et al. Meeting Report: Hackathon-Workshop on Darwin Core and MIxS Standards Alignment (February 2012) , 2012, Standards in genomic sciences.
[44] M. Rounsevell,et al. Exposure of European biodiversity to changes in human-induced pressures , 2008 .
[45] Taylor H. Ricketts,et al. The Convention on Biological Diversity's 2010 Target , 2005, Science.
[46] R. Peng. Reproducible Research in Computational Science , 2011, Science.
[47] Robert A. Wagner,et al. An Extension of the String-to-String Correction Problem , 1975, JACM.
[48] Michael Hofreiter,et al. New life for ancient DNA. , 2012, Scientific American.
[49] R. Pearson,et al. Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar , 2006 .
[50] Stuart R. Borrett,et al. The rise of Network Ecology: Maps of the topic diversity and scientific collaboration , 2013, 1311.1785.
[51] Heather A. Piwowar,et al. Data reuse and the open data citation advantage , 2013, PeerJ.
[52] Alban Gaignard,et al. Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities , 2017, Future Gener. Comput. Syst..
[53] Emily S. Charlson,et al. Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications , 2011, Nature Biotechnology.
[54] T. Dawson,et al. Model‐based uncertainty in species range prediction , 2006 .
[55] Birgitta König-Ries,et al. Towards an Ecological Trait-data Standard , 2018, bioRxiv.
[56] Thomas G. Dietterich,et al. The eBird enterprise: An integrated approach to development and application of citizen science , 2014 .
[57] Ramakrishnan Srikant,et al. Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.
[58] G. Rambold,et al. FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results , 2020, Database J. Biol. Databases Curation.
[59] Matthew E. Aiello-Lammens,et al. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models , 2015 .
[60] R. Guralnick,et al. BioGeomancer: Automated Georeferencing to Map the World's Biodiversity Data , 2006, PLoS biology.
[61] Brendan A. Wintle,et al. Imperfect detection impacts the performance of species distribution models , 2014 .
[62] R. Real,et al. AUC: a misleading measure of the performance of predictive distribution models , 2008 .
[63] Gabriele Dröge,et al. The Global Genome Biodiversity Network (GGBN) Data Portal , 2013, Nucleic Acids Res..
[64] Wisdom M. Dlamini,et al. A data mining approach to predictive vegetation mapping using probabilistic graphical models , 2011, Ecol. Informatics.
[65] Mark Tranmer. Animal social networks Jens Krause Richard James , 2015, Animal Behaviour.
[66] Jeff Weber,et al. Workflow Management in Condor , 2007, Workflows for e-Science, Scientific Workflows for Grids.
[67] Stephen Abrams,et al. DMPTool 2: Expanding Functionality for Better Data Management Planning , 2014, Int. J. Digit. Curation.
[68] Christina M. Bergey,et al. The use of museum specimens with high-throughput DNA sequencers. , 2015, Journal of human evolution.
[69] Hervé Goëau,et al. Automated Identification of Herbarium Specimens at Different Taxonomic Levels , 2018, Multimedia Tools and Applications for Environmental & Biodiversity Informatics.
[70] Luiz M. R. Gadelha,et al. Exploring Reproducibility and FAIR Principles in Data Science Using Ecological Niche Modeling as a Case Study , 2019, ER Workshops.
[71] P. Soltis. Digitization of herbaria enables novel research. , 2017, American journal of botany.
[72] Youhua Chen. Conservation biogeography of the snake family Colubridae of China , 2009 .
[73] David Koop,et al. VisTrails SAHM: visualization and workflow management for species habitat modeling , 2013 .
[74] Mark New,et al. Ensemble forecasting of species distributions. , 2007, Trends in ecology & evolution.
[75] Mark A. Burgman,et al. Scientific Foundations for an IUCN Red List of Ecosystems , 2013, PloS one.
[76] Tony Hey,et al. The Fourth Paradigm: Data-Intensive Scientific Discovery , 2009 .
[77] Matthew Jones,et al. Maximizing the Value of Ecological Data with Structured Metadata: An Introduction to Ecological Metadata Language (EML) and Principles for Metadata Creation , 2005 .
[78] A. Peterson,et al. No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation , 2015 .
[79] Cristina Boeres,et al. EasyGrid: towards a framework for the automatic Grid enabling of legacy MPI applications , 2004, Concurr. Pract. Exp..
[80] Carsten F. Dormann,et al. Ecological networks - foodwebs and beyond , 2009 .
[81] Siang Thye Hang,et al. Plant Identification: Experts vs. Machines in the Era of Deep Learning - Deep Learning Techniques Challenge Flora Experts , 2018, Multimedia Tools and Applications for Environmental & Biodiversity Informatics.
[82] Tony X. Han,et al. Deep convolutional neural network based species recognition for wild animal monitoring , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[83] Paul T. Groth,et al. The rationale of PROV , 2015, J. Web Semant..
[84] N. Jürgens,et al. A complete digitization of German herbaria is possible, sensible and should be started now , 2020 .
[85] SchmidhuberJürgen. Deep learning in neural networks , 2015 .
[86] Renée J. Miller,et al. Open Data Integration , 2018, Proc. VLDB Endow..
[87] Shawn Bowers,et al. The New Bioinformatics: Integrating Ecological Data from the Gene to the Biosphere , 2006 .
[88] P. Kirk,et al. International Code of Nomenclature for algae, fungi, and plants (Melbourne Code) , 2012 .
[89] Jano Moreira de Souza,et al. Analysis and visualization of the geographical distribution of atlantic forest bromeliads species , 2009, 2009 IEEE Symposium on Computational Intelligence and Data Mining.
[90] Constance A. Rinaldo,et al. The Biodiversity Heritage Library: sharing biodiversity literature with the world , 2009 .
[91] Karen I. Stocks,et al. Information Management Strategies for Deep‐Sea Biology , 2016 .
[92] L. Sack,et al. Digital data collection in forest dynamics plots , 2010 .
[93] CandelaLeonardo,et al. Species distribution modeling in the cloud , 2016 .
[94] Ari Karppinen,et al. Multimedia Tools and Applications for Environmental & Biodiversity Informatics , 2018, Multimedia Systems and Applications.
[95] Raymond L. Lindeman. The trophic-dynamic aspect of ecology , 1942 .
[96] Anne E. Trefethen,et al. Cyberinfrastructure for e-Science , 2005, Science.
[97] Robert A. Morris,et al. Kurator: A Kepler Package for Data Curation Workflows , 2012, ICCS.
[98] H. Odum. Primary Production in Flowing Waters1 , 1956 .
[99] Siddeswara Guru,et al. Development of a cloud-based platform for reproducible science: A case study of an IUCN Red List of Ecosystems Assessment , 2016, Ecol. Informatics.
[100] Eduardo Dalcin,et al. SiBBr: Uma Infraestrutura para Coleta, Integração e Análise de Dados sobre a Biodiversidade Brasileira , 2014 .
[101] Michael J. Lutz,et al. Undergraduate software engineering , 2014, CACM.
[102] J. M. Heberling,et al. iNaturalist as a tool to expand the research value of museum specimens , 2018, Applications in plant sciences.
[103] Margo I. Seltzer,et al. A primer on provenance , 2014, CACM.
[104] Douglas Thain,et al. An invariant framework for conducting reproducible computational science , 2015, J. Comput. Sci..
[105] Luiz M. R. Gadelha,et al. New perspectives on analysing data from biological collections based on social network analytics , 2020, Scientific Reports.
[106] Ian J. Taylor,et al. Workflows and e-Science: An overview of workflow system features and capabilities , 2009, Future Gener. Comput. Syst..
[107] Erik Schultes,et al. The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.
[108] Anton Nekrutenko,et al. Ten Simple Rules for Reproducible Computational Research , 2013, PLoS Comput. Biol..
[109] Eli Dart,et al. The Modern Research Data Portal: a design pattern for networked, data-intensive science , 2018, PeerJ Comput. Sci..
[110] David Koop,et al. Data Management Challenges in Species Distribution Modeling , 2013, IEEE Data Eng. Bull..
[111] David Abramson,et al. A Computational Pipeline for the IUCN Risk Assessment for Meso-American Reef Ecosystem , 2017, 2017 IEEE 13th International Conference on e-Science (e-Science).
[112] John Wieczorek,et al. Connecting data and expertise: a new alliance for biodiversity knowledge , 2019, Biodiversity data journal.
[113] Robert P. Anderson,et al. Maximum entropy modeling of species geographic distributions , 2006 .
[114] P. Hebert,et al. bold: The Barcode of Life Data System (http://www.barcodinglife.org) , 2007, Molecular ecology notes.
[115] Rakesh Agarwal,et al. Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.
[116] Paul T. Groth,et al. Provenance-based validation of e-science experiments , 2005, J. Web Semant..
[117] Jaideep Srivastava,et al. Selecting the right interestingness measure for association patterns , 2002, KDD.
[118] Andreas Wilke,et al. The MG-RAST metagenomics database and portal in 2015 , 2015, Nucleic Acids Res..
[119] Ian Foster,et al. Parsl: Pervasive Parallel Programming in Python , 2019, HPDC.
[120] Robert P. Anderson,et al. Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models , 2014 .
[121] A. Neves,et al. New Brazilian Floristic List Highlights Conservation Challenges , 2018 .
[122] Renzo Kottmann,et al. RCN4GSC Workshop Report: Managing Data at the Interface of Biodiversity and (Meta)Genomics, March 2011 , 2012, Standards in genomic sciences.
[123] Gregor Hagedorn,et al. Discovery and publishing of primary biodiversity data associated with multimedia resources: The Audubon Core strategies and approaches , 2013 .
[124] N. Pettorelli,et al. Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions , 2016 .
[125] Eduardo Siegle,et al. Perspectives on the Great Amazon Reef: Extension, Biodiversity, and Threats , 2018, Front. Mar. Sci..
[126] Thijs J. G. Ettema,et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity , 2017, Nature.
[127] J. Elith,et al. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .
[128] Timothy J. S. Whitfeld,et al. Widespread sampling biases in herbaria revealed from large-scale digitization , 2017, bioRxiv.
[129] Jesús Francisco Vargas-Bonilla,et al. Towards automatic wild animal monitoring: Identification of animal species in camera-trap images using very deep convolutional neural networks , 2016, Ecol. Informatics.
[130] Eric H Lyons,et al. The iPlant Collaborative , 2012 .
[131] J. Wesley Barnes,et al. ConsNet: new software for the selection of conservation area networks with spatial and multi‐criteria analyses , 2009 .
[132] Sofia C. Olhede,et al. A method to detect subcommunities from multivariate spatial associations , 2014 .
[133] Diana Rizzolio. Text of the Convention , 2008 .
[134] Robin Freeman,et al. Emerging Network-Based Tools in Movement Ecology. , 2016, Trends in ecology & evolution.
[135] A. Peterson,et al. Using Ecological‐Niche Modeling to Predict Barred Owl Invasions with Implications for Spotted Owl Conservation , 2003 .
[136] Xin Zhou,et al. The Global Genome Biodiversity Network (GGBN) Data Standard specification , 2016, Database J. Biol. Databases Curation.
[137] Luiz M. R. Gadelha,et al. Baseline Assessment of Mesophotic Reefs of the Vitória-Trindade Seamount Chain Based on Water Quality, Microbial Diversity, Benthic Cover and Fish Biomass Data , 2015, PloS one.
[138] A. Peterson,et al. The crucial role of the accessible area in ecological niche modeling and species distribution modeling , 2011 .
[139] Cláudio T. Silva,et al. Provenance for Computational Tasks: A Survey , 2008, Computing in Science & Engineering.
[140] Miguel B. Araújo,et al. Using species co-occurrence networks to assess the impacts of climate change , 2011 .
[141] P. Hebert,et al. bold: The Barcode of Life Data System (http://www.barcodinglife.org) , 2007, Molecular ecology notes.
[142] Margaret Kosmala,et al. Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning , 2017, Proceedings of the National Academy of Sciences.
[143] Zahid Anwar,et al. Data mining techniques and applications — A decade review , 2017, 2017 23rd International Conference on Automation and Computing (ICAC).
[144] Quentin Groom,et al. Herbarium specimens reveal the exchange network of British and Irish botanists, 1856–1932 , 2014 .
[145] A. Guisan,et al. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data , 2004 .
[146] Matthew E. Aiello-Lammens,et al. Wallace: A flexible platform for reproducible modeling of species niches and distributions built for community expansion , 2017 .
[147] J. Drexler,et al. Evidence for multiple sylvatic transmission cycles during the 2016-2017 yellow fever virus outbreak, Brazil. , 2018, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.
[148] Winston A Hide,et al. Big data: The future of biocuration , 2008, Nature.
[149] A. Townsend Peterson,et al. Novel methods improve prediction of species' distributions from occurrence data , 2006 .
[150] Jano Moreira de Souza,et al. Applying data mining techniques for spatial distribution analysis of plant species co-occurrences , 2016, Expert Syst. Appl..
[151] Eduardo Couto Dalcin,et al. Data quality concepts and techniques applied to taxonomic databases , 2005 .
[152] Ilene Karsch-Mizrachi,et al. The NCBI BioCollections Database , 2018, Database J. Biol. Databases Curation.
[153] P. Hebert,et al. Barcode of life. , 2008, Scientific American.
[154] Garth N. Wells,et al. Containers for Portable, Productive, and Performant Scientific Computing , 2016, Computing in Science & Engineering.
[155] Aakrosh Ratan,et al. Galaxy tools to study genome diversity , 2013, GigaScience.
[156] Edward Baker,et al. Scratchpads 2.0: a Virtual Research Environment supporting scholarly collaboration, communication and data publication in biodiversity science , 2011, ZooKeys.
[157] M. Fladeland,et al. Remote sensing for biodiversity science and conservation , 2003 .
[158] Matthew J. Turk,et al. Computing Environments for Reproducibility: Capturing the "Whole Tale" , 2018, Future Gener. Comput. Syst..
[159] Rafael Pino-Mejías,et al. Predicting the potential habitat of oaks with data mining models and the R system , 2010, Environ. Model. Softw..
[160] Douglas Thain,et al. Reproducibility in Scientific Computing , 2018, ACM Comput. Surv..
[161] A. Townsend Peterson,et al. The Importance of Biodiversity E-infrastructures for Megadiverse Countries , 2015, PLoS biology.
[162] Edmund Hart,et al. Towards a more reproducible ecology , 2016 .
[163] Rodolfo Paranhos,et al. Abrolhos Bank Reef Health Evaluated by Means of Water Quality, Microbial Diversity, Benthic Cover, and Fish Biomass Data , 2012, PloS one.
[164] Theodoros Rekatsinas,et al. Deep Learning for Entity Matching: A Design Space Exploration , 2018, SIGMOD Conference.
[165] Matthew B. Jones,et al. Managing heterogeneous ecological data using Morpho , 2002, Proceedings 14th International Conference on Scientific and Statistical Database Management.
[166] J. L. Parra,et al. Very high resolution interpolated climate surfaces for global land areas , 2005 .
[167] Steve Kelling,et al. Participatory design of DataONE - Enabling cyberinfrastructure for the biological and environmental sciences , 2012, Ecol. Informatics.
[168] Bas E. Dutilh,et al. FOCUS: an alignment-free model to identify organisms in metagenomes using non-negative least squares , 2014, PeerJ.
[169] R. Forzza,et al. Herbarium collection of the Rio de Janeiro Botanical Garden (RB), Brazil , 2018, Biodiversity data journal.
[170] Ashley Shade,et al. Computing Workflows for Biologists: A Roadmap , 2015, PLoS biology.
[171] Jens Kattge,et al. Biodiversity data integration—the significance of data resolution and domain , 2019, PLoS biology.
[172] Matthew B Jones,et al. Ecoinformatics: supporting ecology as a data-intensive science. , 2012, Trends in ecology & evolution.
[173] Vladimir I. Levenshtein,et al. Binary codes capable of correcting deletions, insertions, and reversals , 1965 .
[174] Marta Mattoso,et al. Provenance and Annotation of Data and Processes , 2016, Lecture Notes in Computer Science.
[175] Damaris Zurell,et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .
[176] Charles Troupin,et al. Bio‐ORACLE: a global environmental dataset for marine species distribution modelling , 2012 .
[177] Daniel Sabatier,et al. Species Distribution Modelling: Contrasting presence-only models with plot abundance data , 2018, Scientific Reports.
[178] A. Townsend Peterson,et al. Ecological Niche Modeling Using the Kepler Workflow System , 2007, Workflows for e-Science, Scientific Workflows for Grids.
[179] Gerald L. Kooyman,et al. An Emperor Penguin Population Estimate: The First Global, Synoptic Survey of a Species from Space , 2012, PloS one.
[180] Rommie E. Amaro,et al. Exascale Computing: A New Dawn for Computational Biology , 2018, Computing in Science & Engineering.
[181] Jitendra Kumar,et al. Cluster Analysis-Based Approaches for Geospatiotemporal Data Mining of Massive Data Sets for Identification of Forest Threats , 2011, ICCS.
[182] Matthew B. Jones,et al. Metacat: a schema-independent XML database system , 2001, Proceedings Thirteenth International Conference on Scientific and Statistical Database Management. SSDBM 2001.
[183] Tim Sutton,et al. How Global Is the Global Biodiversity Information Facility? , 2007, PloS one.
[184] Edward A. Lee,et al. Scientific workflow management and the Kepler system , 2006, Concurr. Comput. Pract. Exp..
[185] R. Henrik Nilsson,et al. Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi , 2014, Database J. Biol. Databases Curation.
[186] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[187] Lee Belbin,et al. Towards a national bio-environmental data facility: experiences from the Atlas of Living Australia , 2016, Int. J. Geogr. Inf. Sci..
[188] Marko Debeljak,et al. Modelling forest growing stock from inventory data: A data mining approach , 2014 .
[189] Michael Nee,et al. An integrated assessment of the vascular plant species of the Americas , 2017, Science.
[190] Graziano Pesole,et al. The BioVel Project: Robust phylogenetic workflows running on the GRID , 2012 .
[191] Peter Brewer,et al. openModeller: a generic approach to species’ potential distribution modelling , 2011, GeoInformatica.
[192] M. White,et al. Measuring and comparing the accuracy of species distribution models with presence–absence data , 2011 .
[193] Omri Allouche,et al. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) , 2006 .
[194] Renée J. Miller,et al. Table Union Search on Open Data , 2018, Proc. VLDB Endow..
[195] Andreas Wilke,et al. phylogenetic and functional analysis of metagenomes , 2022 .
[196] O. Phillips,et al. Extinction risk from climate change , 2004, Nature.
[197] Vincent S. Smith,et al. Actionable, long-term stable and semantic web compatible identifiers for access to biological collection objects , 2017, Database J. Biol. Databases Curation.
[198] Anna Lysyanskaya,et al. How to keep secrets safe. , 2008, Scientific American.
[199] Verena Kantere,et al. Managing scientific data , 2010, Commun. ACM.
[200] Alex Hardisty,et al. UvA-DARE ( Digital Academic Repository ) A decadal view of biodiversity informatics : challenges and priorities , 2013 .
[201] Clara Baringo Fonseca,et al. SiBBr: Envisioning the spatial distribution of Brazilian biodiversity records , 2017 .
[202] David E. Golan,et al. Protein therapeutics: a summary and pharmacological classification , 2008, Nature Reviews Drug Discovery.
[203] Andreas Thor,et al. Evaluation of entity resolution approaches on real-world match problems , 2010, Proc. VLDB Endow..
[204] Marinez Ferreira de Siqueira,et al. Consequences of global climate change for geographic distributions of cerrado tree species , 2003 .
[205] Zhenyuan Lu,et al. The taxonomic name resolution service: an online tool for automated standardization of plant names , 2013, BMC Bioinformatics.
[206] M. Luoto,et al. Biotic interactions improve prediction of boreal bird distributions at macro‐scales , 2007 .
[207] Eli Dart,et al. The Modern Research Data Portal: a design pattern for networked, data-intensive science , 2018, PeerJ Comput. Sci..
[208] Walter G. Berendsohn,et al. A taxonomic information model for botanical databases: the IOPI Model , 1997 .
[209] Carl Boettiger,et al. An introduction to Docker for reproducible research , 2014, OPSR.
[210] T. Groen,et al. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling , 2011 .
[211] Tony X. Han,et al. Ensemble Video Object Cut in Highly Dynamic Scenes , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[212] N. Baeshen,et al. Biological Identifications Through DNA Barcodes , 2012 .
[213] André Carlos Ponce de Leon Ferreira de Carvalho,et al. Comparing machine learning classifiers in potential distribution modelling , 2011, Expert Syst. Appl..
[214] T. Rangel,et al. Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change , 2009 .
[215] Ben Collen,et al. Global effects of land use on local terrestrial biodiversity , 2015, Nature.
[216] J. Edwards. Research and Societal Benefits of the Global Biodiversity Information Facility , 2004 .
[217] Laura Eme,et al. Archaea and the origin of eukaryotes , 2017, Nature Reviews Microbiology.
[218] WESLEY M. HOCHACHKA,et al. Data-Mining Discovery of Pattern and Process in Ecological Systems , 2007 .
[219] John Wieczorek,et al. Darwin Core: An Evolving Community-Developed Biodiversity Data Standard , 2012, PloS one.
[220] A. Townsend Peterson,et al. Essential biodiversity variables are not global , 2018, Biodiversity and Conservation.
[221] C. A. Howell,et al. Niches, models, and climate change: Assessing the assumptions and uncertainties , 2009, Proceedings of the National Academy of Sciences.
[222] Louisa Flintoft,et al. A barcode for life? , 2004, Nature Reviews Genetics.
[223] Marta Mattoso,et al. A Survey of Data-Intensive Scientific Workflow Management , 2015, Journal of Grid Computing.
[224] V. Stodden,et al. Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals , 2013, PloS one.
[225] Fabiano L. Thompson,et al. Metagenomic Analysis of Healthy and White Plague-Affected Mussismilia braziliensis Corals , 2013, Microbial Ecology.
[226] B. S. Manjunath,et al. The iPlant Collaborative: Cyberinfrastructure for Plant Biology , 2011, Front. Plant Sci..
[227] Ruben Vicente-Saez,et al. Open Science now: A systematic literature review for an integrated definition , 2018, Journal of Business Research.
[228] W. G. Berendsohn,et al. Biodiversity information platforms: From standards to interoperability , 2011, ZooKeys.
[229] R. C. Forzza,et al. Jabot - Sistema de Gerenciamento de Coleções Botânicas: a experiência de uma década de desenvolvimento e avanços , 2017 .
[230] Joseph A Cook,et al. The next generation of natural history collections , 2018, PLoS biology.
[231] Graziano Pesole,et al. UvA-DARE ( Digital Academic Repository ) BioVeL : a virtual laboratory for data analysis and modelling in biodiversity science and ecology , 2016 .
[232] Robert A. Boria,et al. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models , 2014 .
[233] Pasquale Pagano,et al. Species distribution modeling in the cloud , 2016, Concurr. Comput. Pract. Exp..
[234] Gregory Piatetsky-Shapiro,et al. Knowledge Discovery in Real Databases: A Report on the IJCAI-89 Workshop , 1991, AI Mag..
[235] P. Bonnet,et al. Going deeper in the automated identification of Herbarium specimens , 2017, BMC Evolutionary Biology.
[236] G. Daily,et al. Biodiversity loss and its impact on humanity , 2012, Nature.
[237] Zhi Zhang,et al. Visual Informatics Tools for Supporting Large-Scale Collaborative Wildlife Monitoring with Citizen Scientists , 2016, IEEE Circuits and Systems Magazine.
[238] J. Calabrese,et al. Stacking species distribution models and adjusting bias by linking them to macroecological models , 2014 .
[239] D. Tautz,et al. A plea for DNA taxonomy , 2003 .
[240] Ulf Leser,et al. Similarity Search for Scientific Workflows , 2014, Proc. VLDB Endow..
[241] David J. Gavaghan,et al. The zoon r package for reproducible and shareable species distribution modelling , 2017 .
[242] Jennifer Preece,et al. Understanding Data Providers in a Global Scientific Data Hub , 2015, CSCW Companion.
[243] R. Ostfeld,et al. Effects of environmental change on zoonotic disease risk: an ecological primer. , 2014, Trends in parasitology.
[244] David Abramson,et al. High performance parametric modeling with Nimrod/G: killer application for the global grid? , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.
[245] Marta Mattoso,et al. Towards supporting the life cycle of large scale scientific experiments , 2010, Int. J. Bus. Process. Integr. Manag..
[246] K. Schmidt. Conceptual Framework for , 2002 .
[247] Javier Otegui,et al. The geospatial data quality REST API for primary biodiversity data , 2016, Bioinform..
[248] Heather Holden,et al. Hyperspectral identification of coral reef features , 1999 .
[249] Jitendra Kumar,et al. Parallel k-Means Clustering for Quantitative Ecoregion Delineation Using Large Data Sets , 2011, ICCS.
[250] A. Townsend Peterson,et al. kuenm: an R package for detailed development of ecological niche models using Maxent , 2019, PeerJ.
[251] Cláudio T. Silva,et al. Managing Rapidly-Evolving Scientific Workflows , 2006, IPAW.
[252] Helio J. C. Barbosa,et al. SISS-Geo: Leveraging Citizen Science to Monitor Wildlife Health Risks in Brazil , 2018, Journal of Healthcare Informatics Research.
[253] Miguel B. Araújo,et al. Selecting areas for species persistence using occurrence data , 2000 .
[254] Alberto Apostolico,et al. Global Biodiversity Informatics Outlook: Delivering biodiversity knowledge in the information age , 2013 .
[255] Robert P. Anderson,et al. Evaluating predictive models of species’ distributions: criteria for selecting optimal models , 2003 .
[256] J. Bascompte. Networks in ecology , 2007 .
[257] Robert Pergl,et al. "Data Stewardship Wizard": A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning , 2019, Data Sci. J..
[258] Jorge Soberón. Niche and area of distribution modeling: a population ecology perspective , 2010 .
[259] J. Bascompte,et al. Ecological networks : beyond food webs Ecological networks – beyond food webs , 2008 .
[260] Shu-Hsien Liao,et al. Data mining techniques and applications - A decade review from 2000 to 2011 , 2012, Expert Syst. Appl..
[261] Mark Newman,et al. Networks: An Introduction , 2010 .
[262] Albert-László Barabási,et al. Statistical mechanics of complex networks , 2001, ArXiv.
[263] Anton Güntsch,et al. The Biodiversity Informatics Landscape: Elements, Connections and Opportunities , 2017 .
[264] Jarrett E. K. Byrnes,et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change , 2012, Nature.
[265] Pasquale Pagano,et al. Supporting Biodiversity Studies by the EUBrazilOpenBio Hybrid Data Infrastructure , 2013 .
[266] Tony Rees,et al. Taxamatch, an Algorithm for Near (‘Fuzzy’) Matching of Scientific Names in Taxonomic Databases , 2014, PloS one.
[267] Lisa Drew,et al. Are We Losing the Science of Taxonomy? , 2011 .
[268] Christopher R. Stephens,et al. Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases , 2008, PloS one.
[269] Santiago José Elías Velazco,et al. ENMTML: An R package for a straightforward construction of complex ecological niche models , 2020, Environ. Model. Softw..
[270] T. Dawson,et al. Selecting thresholds of occurrence in the prediction of species distributions , 2005 .
[271] D. Roberts,et al. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales , 2005 .
[272] N. Pettorelli,et al. Essential Biodiversity Variables , 2013, Science.
[273] Marie-Stéphanie Samain,et al. Data Mining for Global Trends in Mountain Biodiversity , 2011 .
[274] Bas E. Dutilh,et al. SUPER-FOCUS: a tool for agile functional analysis of shotgun metagenomic data , 2015, Bioinform..
[275] Robert P. Anderson,et al. Ecological Niches and Geographic Distributions , 2011 .
[276] Ian M. Mitchell,et al. Best Practices for Scientific Computing , 2012, PLoS biology.
[277] M. Araújo,et al. Uses and misuses of bioclimatic envelope modeling. , 2012, Ecology.
[278] Anne Bowser,et al. The Bari Manifesto: An interoperability framework for essential biodiversity variables , 2019, Ecol. Informatics.
[279] Indra Neil Sarkar,et al. Taxongrab: Extracting Taxonomic Names from Text , 2005 .
[280] José Laurindo Campos dos Santos,et al. Biodiversity and Integrated Environmental Monitoring , 2013 .
[281] Matthew B. Jones,et al. Challenges and Opportunities of Open Data in Ecology , 2011, Science.
[282] Louise McRae,et al. Global biodiversity monitoring: From data sources to Essential Biodiversity Variables , 2017 .
[283] Luiz M. R. Gadelha,et al. Model-R: A Framework for Scalable and Reproducible Ecological Niche Modeling , 2017, CARLA.
[284] Kristin Vanderbilt,et al. Long term ecological research and information management , 2011, Ecol. Informatics.
[285] Antonio Mauro Saraiva,et al. A conceptual framework for quality assessment and management of biodiversity data , 2017, PloS one.
[286] Robert Cubey,et al. Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach , 2012, ZooKeys.
[287] Barry Smith,et al. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies , 2014, PloS one.
[288] Norman F Johnson,et al. Biodiversity informatics. , 2007, Annual review of entomology.
[289] P. Bryan Heidorn,et al. Shedding Light on the Dark Data in the Long Tail of Science , 2008, Libr. Trends.
[290] Daniel S. Park,et al. A checklist for maximizing reproducibility of ecological niche models , 2019, Nature Ecology & Evolution.