cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20455284.v1
title: Efficacy and safety of phosphatidylinositol 3-kinase inhibitors in patients with chronic lymphocytic leukemia: a meta-analysis and systematic review

description: Phosphatidylinositol 3-kinase (PI3K) inhibitors demonstrate promising effects in the treatment of relapsed/refractory chronic lymphocytic leukemia (CLL). Emerging evidence of the therapeutic effects of the PI3K inhibitors in various aspects remains controversial. This meta-analysis was used to evaluate the efficacy and safety of PI3K inhibitors based on a synthesis of the data generated by randomized controlled trials (RCTs) of patients with CLL, by searching PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov registry. Five RCTs with 1593 patients were included. The PI3K inhibitors significantly improved progression-free survival (PFS), the chance of overall response, and partial response compared to the control arm. Regarding adverse events (AEs), the PI3K inhibitors increased the risk of pyrexia, chills, diarrhea, decreased appetite, vomiting, rash, pneumonia, and upper respiratory tract infection. Available evidence showed significant improvements over conventional therapy in PFS of the PI3K inhibitors in patients with CLL, with relatively manageable AEs.
DOI: 10.6084/m9.figshare.6823919.v1
title: Additional file 2: of Profiling of testis-specific long noncoding RNAs in mice

description: Table S2. Tissue-specific lncRNAs and mRNAs in the mouse brain, heart, kidney, liver and testis. (XLSX 4020 kb)
DOI: 10.6084/m9.figshare.6823934
title: Additional file 3: of Profiling of testis-specific long noncoding RNAs in mice

description: Table S3. The numbers and ratios of testicular lncRNAs and mRNAs on each mouse chromosome. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.13115088
title: Additional file 15 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 15. CircRNA/mRNA-miRNA co-expression relationships.
DOI: 10.6084/m9.figshare.13115115
title: Additional file 8 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 8. All the differentially expressed circRNAs in this study.
DOI: 10.6084/m9.figshare.13115082
title: Additional file 13 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 13. LncRNA-mRNA co-expression relationships.
DOI: 10.6084/m9.figshare.13115109.v1
title: Additional file 6 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 6. All the differentially expressed mRNAs in this study.
DOI: 10.6084/m9.figshare.13115103
title: Additional file 4 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 4. The information of all novel lncRNAs identified in this study.
DOI: 10.6084/m9.figshare.6823781
title: Additional file 1: of Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

description: Table S1. Cohort characteristics. Table S2. Single SNP meta-analyses. Table S3. Sex-stratified analyses. Table S4. SKAT analyses. Table S5. T1-burden analyses. Table S6. ADAMTS6 variant details. Table S7. Cardiac phenotype distribution in Adamts6 mutant mice. (XLSX 475 kb)
DOI: 10.6084/m9.figshare.13115103.v1
title: Additional file 4 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 4. The information of all novel lncRNAs identified in this study.
DOI: 10.6084/m9.figshare.6823781.v1
title: Additional file 1: of Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

description: Table S1. Cohort characteristics. Table S2. Single SNP meta-analyses. Table S3. Sex-stratified analyses. Table S4. SKAT analyses. Table S5. T1-burden analyses. Table S6. ADAMTS6 variant details. Table S7. Cardiac phenotype distribution in Adamts6 mutant mice. (XLSX 475 kb)
DOI: 10.5281/zenodo.8208245
title: Data Set: Promoting Open Science in Test-Driven Software Experiments

description: Data set for reproduction purposes (tabular data is stored using Apache's Parqet format).
DOI: 10.5281/zenodo.8208246
title: Data Set: Promoting Open Science in Test-Driven Software Experiments

description: Data set for reproduction purposes (tabular data is stored using Apache's Parqet format).
DOI: 10.6084/m9.figshare.13115106
title: Additional file 5 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 5. The information of all novel circRNAs identified in this study.
DOI: 10.6084/m9.figshare.13115112
title: Additional file 7 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 7. All the differentially expressed lncRNAs in this study.
DOI: 10.6084/m9.figshare.6823892.v1
title: Additional file 11: of Profiling of testis-specific long noncoding RNAs in mice

description: Table S11. Primers used for RT-PCR. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.6823991.v1
title: Additional file 8: of Profiling of testis-specific long noncoding RNAs in mice

description: Table S8. LncRNAs and mRNAs in three mouse germ cell-related cell lines (F9, GC-1 and GC-2). (XLSX 16402 kb)
DOI: 10.6084/m9.figshare.13115100.v1
title: Additional file 3 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 3. The information of all known lncRNAs identified in this study.
DOI: 10.6084/m9.figshare.13115106.v1
title: Additional file 5 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 5. The information of all novel circRNAs identified in this study.
DOI: 10.6084/m9.figshare.13115118.v1
title: Additional file 9 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 9. GO enrichment analysis of mRNAs.
DOI: 10.6084/m9.figshare.13115109
title: Additional file 6 of Genome-wide analysis of differentially expressed mRNAs, lncRNAs, and circRNAs in chicken bursae of Fabricius during infection with very virulent infectious bursal disease virus

description: Additional file 6. All the differentially expressed mRNAs in this study.
DOI: 10.34740/kaggle/ds/2306262
title: IIT Goa Pothole Detection & Classification Dataset
DOI: 10.6084/m9.figshare.13114961.v1
title: Additional file 4 of miR168 targets Argonaute1A mediated miRNAs regulation pathways in response to potassium deficiency stress in tomato

description: Additional file 4: Table S4. The expressed conserved miRNAs were classified into different miRNAs families.
DOI: 10.6084/m9.figshare.9956471.v1
title: Climate change contributes to widespread declines among bumble bees across continents - DATA REPOSITORY

description: Data and code repository for Soroye et al. 2020. (DOI: 10.1126/science.aax8591)Bumblebee observations, gridded environmental observations, and R scripts used to process data and generate all results from study.<br>The authors would like to thank all contributors to the bumble bee dataset, and the tireless hours of those who helped put it together, especially Alana Pindar, Paul Galpern, Laurence Packer, Simon G. Potts, Stuart M. Roberts, Pierre Rasmont, Oliver Schweiger, Sheila R. Colla, Leif L. Richardson, David L. Wagner, Lawrence F. Gall, Derek S. Sikes, and Alberto Pantoja. We are grateful to data contributors from North America: Bee Biology and Systematics Lab, USDA-ARS, Utah State University; John Ascher, National University of Singapore and American Museum of Natural History, New York, USA; Doug Yanega, University of California, Riverside (NSF-DBI #0956388 and #0956340), California, USA; Illinois Natural History Survey, Illinois, USA; Packer Lab Research Collection, York University, Canada; Canadian National Collection, Agriculture and Agri-Food Canada; Canada; Peabody Museum, Yale University; Sam Droege, USGS Patuxent Wildlife Research Center, USA; Boulder Museum of Natural History, University of Colorado, Colorado, USA. From Europe: Status and Trends of European Pollinators (STEP) Collaborative Project (grant 244090, www.STEP-project.net); Bees, Wasps and Ants Recording Society; BDFGM Banque de Données Fauniques (P. Rasmont & E. Haubruge); BWARS (UK, S.P.M. Roberts); SSIC (Sweden, B. Cederberg); Austria (J. Neumayer); EISN (Netherland, M. Reemer); CSCF (Suisse, Y. Gonseth); Poland (T. Pawlikowski); NBDC (Eire, U. FitzPatrick); FMNH (Finland, J. Paukkunen); Czech Republic (J. Straka, L. Dvorak); France (G. Mahé); NSIC (Norway, F. Odegaard); UK (S.P.M. Roberts); Italy (A. Manino); Spain (L. Castro) Global Biodiversity Information Facility (GBIF), http://gbif.org for records from North America and Europe. <br>
DOI: 10.17632/6crh35nc96.1
title: Data for: Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach

description: Inland transport in China by provinces, 2006-2015
DOI: 10.17632/6crh35nc96.2
title: Data for: Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach

description: Inland transport in China by provinces, 2006-2015
DOI: 10.5519/qd.86yxb00v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1046944 records)
DOI: 10.14457/cmu.res.2011.504
title: การพัฒนาระบบประเมินความถนัดทางการเรียน สำหรับนักเรียนโรงเรียนบุญวาทย์วิทยาลัย จังหวัดลำปาง
DOI: 10.14457/cmu.the.2011.456
title: การพัฒนาบทเรียนภาษาอังกฤษโดยใช้แหล่งเรียนรู้ท้องถิ่น สำหรับนักเรียนชั้นประถมศึกษาปีที่ 6 โรงเรียนชุมชนบ้านร้อง อำเภองาว จังหวัดลำปาง
DOI: 10.14457/cmu.the.2011.457
title: การพัฒนากรอบสมรรถนะของพยาบาลวิชาชีพห้องผ่าตัด ศูนย์มะเร็ง ลำปาง
DOI: 10.14457/cmu.the.2011.458
title: ความพึงพอใจของผู้รับบริการต่อคุณภาพการให้บริการของหน่วยงานบริการบำรุงรักษาระบบไฟฟ้าสาขาธนาคารกสิกรไทย จำกัด (มหาชน) ในกรุงเทพมหานคร
DOI: 10.14457/cmu.the.2011.459
title: การใช้ชุดกิจกรรมกระตุ้นระบบการรับความรู้สึกและการเคลื่อนไหว เพื่อลดพฤติกรรมการเล่นนิ้วมือในเด็กออทิสติก
DOI: 10.14457/cmu.the.2011.460
title: การสร้างแผนการจัดกิจกรรมชุมนุมคณิตศาสตร์โดยใช้แหล่งเรียนรู้ในชุมชน โรงเรียนชลประทานผาแตก จังหวัดเชียงใหม่
DOI: 10.14457/cmu.the.2011.461
title: การวัดระดับอุปนิสัยของนักศึกษาคณะอุตสาหกรรมเกษตร มหาวิทยาลัยเชียงใหม่โดยใช้หลักการเจ็ดอุปนิสัย สำหรับผู้ทรงประสิทธิผลยิ่ง
DOI: 10.5281/zenodo.3653339
title: Data for the publication "Extreme tensile strain states in La0.7Ca0.3MnO3 membranes"

description: Data sets and computational codes for the publication "Extreme tensile strain states in La0.7Ca0.3MnO3 membranes."
DOI: 10.5281/zenodo.3653340
title: Data for the publication "Extreme tensile strain states in La0.7Ca0.3MnO3 membranes"

description: Data sets and computational codes for the publication "Extreme tensile strain states in La0.7Ca0.3MnO3 membranes."
DOI: 10.14457/cmu.res.2011.505
title: การออกแบบหนังสืออิเล็กทรอนิกส์เพื่อเรียนรู้การออกแบบเชิงนิเวศเศรษฐกิจ ของผู้ผลิตผ้าฝ้ายทอมือย้อมสีธรรมชาติ
DOI: 10.14457/cmu.res.2011.506
title: ประสิทธิผลของการใช้แนวปฏิบัติการวางแผนการจำหน่ายในผู้สูงอายุโรคปอดอุดกั้นเรื้อรัง โรงพยาบาลพิชัย จังหวัดอุตรดิตถ์
DOI: 10.14457/cmu.res.2011.507
title: พฤติกรรมผู้บริโภคน้ำพริกสำเร็จรูปพร้อมรับประทาน ในอำเภอเมืองเชียงใหม่
DOI: 10.14457/cmu.res.2011.508
title: ปัจจัยที่มีผลต่อการใช้ระบบงานสารบรรณอิเล็กทรอนิกส์ ของบุคลากรมหาวิทยาลัยแม่โจ้
DOI: 10.14457/cmu.res.2011.509
title: การมีส่วนร่วมในการประกันคุณภาพการศึกษาของบุคลากร คณะพยาบาลศาสตร์ มหาวิทยาลัยเชียงใหม่
DOI: 10.14457/cmu.res.2011.510
title: ทัศนคติของผู้บริโภคในอำเภอเมืองเชียงใหม่ที่มีต่อผลิตภัณฑ์นมผงสำหรับเด็กทารกและเด็กเล็ก
DOI: 10.5281/zenodo.3653124
title: An evaluation of the accuracy and speed of metagenome analysis tools

description: Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity.
description: {"references": ["Lindgreen et al. 2016, An evaluation of the accuracy and speed of metagenome analysis tools"]}
DOI: 10.5281/zenodo.3653125
title: An evaluation of the accuracy and speed of metagenome analysis tools

description: Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity.
description: {"references": ["Lindgreen et al. 2016, An evaluation of the accuracy and speed of metagenome analysis tools"]}
DOI: 10.5281/zenodo.3653879
title: Road traffic prediction dataset.

description: <em>Public (anonymized) road traffic prediction datasets from Huawei Munich Research Center.</em> Datasets from a variety of traffic sensors (i.e. induction loops) for traffic prediction. The data is useful for forecasting traffic patterns and adjusting stop-light control parameters, i.e. cycle length, offset and split times. The dataset contains recorded data from 6 crosses in the urban area for the last 56 days, in the form of flow timeseries, depicted the number of vehicles passing every 5 minutes for a whole day (i.e. 12 readings/h, 288 readings/day, 16128 readings / 56 days).
DOI: 10.5281/zenodo.3653880
title: Road traffic prediction dataset.

description: <em>Public (anonymized) road traffic prediction datasets from Huawei Munich Research Center.</em> Datasets from a variety of traffic sensors (i.e. induction loops) for traffic prediction. The data is useful for forecasting traffic patterns and adjusting stop-light control parameters, i.e. cycle length, offset and split times. The dataset contains recorded data from 6 crosses in the urban area for the last 56 days, in the form of flow timeseries, depicted the number of vehicles passing every 5 minutes for a whole day (i.e. 12 readings/h, 288 readings/day, 16128 readings / 56 days).
DOI: 10.6073/pasta/9aaa72339838382b0a5c4d217e5ea1d0
title: Mangrove Litterfall from the Shark River Slough and Taylor Slough, Everglades National Park (FCE), South Florida from January 2001 to Present

description: Monthly litterfall data is being collected in two mangrove-dominated regions (Shark River and Taylor Slough) in South Florida. Three sites (SRS4, SRS5, SRS6) in the Shark River region and one site (TS/Ph8) in the Taylor Slough region were used to characterize patterns of litterfall production. At each mangrove site 10 litter baskets (0.5 x 0.5 m) were placed in two 20 x 20 m plots (five baskets per plot). Data has been collected since January 2001. Statistical analysis is being performed.
DOI: 10.5281/zenodo.3653835
title: BuGL - A Cross-Language Dataset for Bug Localization

description: BuGL - A Cross-Language Dataset for Bug Localization
DOI: 10.5281/zenodo.3653836
title: BuGL - A Cross-Language Dataset for Bug Localization

description: BuGL - A Cross-Language Dataset for Bug Localization
DOI: 10.5281/zenodo.3653891
title: Fault geometry and slip distribution of the 2013 Mw 7.7 Balochistan earthquake from non-linear and linear inversions of SAR and optical data

description: This archive contains data related to the paper “Fault geometry and slip distribution of the 2013 Mw 7.7 Balochistan earthquake from non-linear and linear inversions of SAR and optical data” by Benjamin Lauer, Raphael Grandin and Yann Klinger.
DOI: 10.5281/zenodo.3653892
title: Fault geometry and slip distribution of the 2013 Mw 7.7 Balochistan earthquake from non-linear and linear inversions of SAR and optical data

description: This archive contains data related to the paper “Fault geometry and slip distribution of the 2013 Mw 7.7 Balochistan earthquake from non-linear and linear inversions of SAR and optical data” by Benjamin Lauer, Raphael Grandin and Yann Klinger.
DOI: 10.5281/zenodo.3653140
title: Synthetic Data Set for Uplift Modeling

description: This dataset is designed and simulated for evaluating uplift modeling and feature selection methods. The main feature of this dataset is that it generates features with various patterns associated with the outcome variable and the causal effect (or treatment effect). Thus it is suitable for evaluating feature importance and model interpretation for uplift modeling. This dataset consists of 100 trials (replicates with different random seeds), each trial with 10,000 samples and 36 features. The outcome variable is binary, that makes this dataset for classification problem. The samples are equally split for control and treatment group (5,000 samples in each group in each trial). The generated data has three types of features: (1) uplift features influencing the treatment effect on the conversion probability; (2) classification features affecting the conversion probability but independent of the treatment effect; and (3) irrelevant features that are independent of both conversion probability and the treatment effect. To model the relationship between uplift features and the treatment effect and classification features and outcome probability, we implement six types of association patterns in the data generation process: linear, quadratic, cubic, ReLU (Rectified Linear Unit), trigonometric function sine, and cosine. In this data set, there are 36 features in total, including 10 classification features, 6 uplift features, and 20 irrelevant features. Column names: Trial ID: 'trial_id' Experiment group label: 'treatment_group_key' Outcome variable (classification label): 'conversion' Feature names: ['x1_informative',<br> 'x2_informative',<br> 'x3_informative',<br> 'x4_informative',<br> 'x5_informative',<br> 'x6_informative',<br> 'x7_informative',<br> 'x8_informative',<br> 'x9_informative',<br> 'x10_informative',<br> 'x11_irrelevant',<br> 'x12_irrelevant',<br> 'x13_irrelevant',<br> 'x14_irrelevant',<br> 'x15_irrelevant',<br> 'x16_irrelevant',<br> 'x17_irrelevant',<br> 'x18_irrelevant',<br> 'x19_irrelevant',<br> 'x20_irrelevant',<br> 'x21_irrelevant',<br> 'x22_irrelevant',<br> 'x23_irrelevant',<br> 'x24_irrelevant',<br> 'x25_irrelevant',<br> 'x26_irrelevant',<br> 'x27_irrelevant',<br> 'x28_irrelevant',<br> 'x29_irrelevant',<br> 'x30_irrelevant',<br> 'x31_uplift_increase',<br> 'x32_uplift_increase',<br> 'x33_uplift_increase',<br> 'x34_uplift_increase',<br> 'x35_uplift_increase',<br> 'x36_uplift_increase'] True underlying control conversion probability: 'control_conversion_prob' True underlying treatment conversion probability: 'treatment1_conversion_prob' True treatment effect: 'treatment1_true_effect'
DOI: 10.5281/zenodo.3653141
title: Synthetic Data Set for Uplift Modeling

description: This dataset is designed and simulated for evaluating uplift modeling and feature selection methods. The main feature of this dataset is that it generates features with various patterns associated with the outcome variable and the causal effect (or treatment effect). Thus it is suitable for evaluating feature importance and model interpretation for uplift modeling. This dataset consists of 100 trials (replicates with different random seeds), each trial with 10,000 samples and 36 features. The outcome variable is binary, that makes this dataset for classification problem. The samples are equally split for control and treatment group (5,000 samples in each group in each trial). The generated data has three types of features: (1) uplift features influencing the treatment effect on the conversion probability; (2) classification features affecting the conversion probability but independent of the treatment effect; and (3) irrelevant features that are independent of both conversion probability and the treatment effect. To model the relationship between uplift features and the treatment effect and classification features and outcome probability, we implement six types of association patterns in the data generation process: linear, quadratic, cubic, ReLU (Rectified Linear Unit), trigonometric function sine, and cosine. In this data set, there are 36 features in total, including 10 classification features, 6 uplift features, and 20 irrelevant features. Column names: Trial ID: 'trial_id' Experiment group label: 'treatment_group_key' Outcome variable (classification label): 'conversion' Feature names: ['x1_informative',<br> 'x2_informative',<br> 'x3_informative',<br> 'x4_informative',<br> 'x5_informative',<br> 'x6_informative',<br> 'x7_informative',<br> 'x8_informative',<br> 'x9_informative',<br> 'x10_informative',<br> 'x11_irrelevant',<br> 'x12_irrelevant',<br> 'x13_irrelevant',<br> 'x14_irrelevant',<br> 'x15_irrelevant',<br> 'x16_irrelevant',<br> 'x17_irrelevant',<br> 'x18_irrelevant',<br> 'x19_irrelevant',<br> 'x20_irrelevant',<br> 'x21_irrelevant',<br> 'x22_irrelevant',<br> 'x23_irrelevant',<br> 'x24_irrelevant',<br> 'x25_irrelevant',<br> 'x26_irrelevant',<br> 'x27_irrelevant',<br> 'x28_irrelevant',<br> 'x29_irrelevant',<br> 'x30_irrelevant',<br> 'x31_uplift_increase',<br> 'x32_uplift_increase',<br> 'x33_uplift_increase',<br> 'x34_uplift_increase',<br> 'x35_uplift_increase',<br> 'x36_uplift_increase'] True underlying control conversion probability: 'control_conversion_prob' True underlying treatment conversion probability: 'treatment1_conversion_prob' True treatment effect: 'treatment1_true_effect'
DOI: 10.18112/openneuro.ds002543.v1.0.0
title: Learning, Inhibitory Control, and Perception
DOI: 10.5281/zenodo.3606382
title: Supporting publication for 'Prevalence sample-based guidance for reporting 2019 data'

description: These two Excel documents help you to map terms from the matrix catalogue ZOO_CAT_MATRIX used in the aggregated prevalence data model to FoodEx2 codes and offer you examples on how prevalence data can be reported using SSD2
description: EU; XLS; zoonoses_support@efsa.europa.eu