cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17634937
title: Meteorological time series in Brazil - conventional stations

description: Daily meteorological time series from conventional climate stations in Brazil.

This dataset is a mirror of official and public data released by Brazil's meteorological public services (INMET). The dataset here is streamlined for processing and managing large volumes of data.

Files

CONV_DATABASE.gpkg -- spatial database with the following layers:



fields -- table of field names and metadata;

stations -- points of climate stations with attributes;

series -- time series of meteorological varibales.




Note: data values are scaled by a factor to improve storage efficiency. See fields layer.


query.py -- standalone python script for data retrieval. See docstring for instructions.

 

Info

Number of stations in catalog: 135

Start of sampling: 1961-01-01 00:00:00

End of sampling: 2025-01-01 00:00:00

Meteorological variables:



p -- Total daily precipitation (mm);

evp -- Daily Piché evaporation  (mm);

sun -- Total sunshine daily (h);

tas_max -- Maximum daily temperature  (°C);

tas_mean -- Compensated daily average temperature (°C);

tas_min -- Minimum daily temperature (°C);

hur_mean -- Relative air humidity daily average (%);

hur_min -- Relative air humidity daily minimum (%);

winds_mean -- Wind daily average speed (m/s);


 

Query data

SQL tool

Data can be retrieved in QGIS via SQL tool with this query:



SELECT d.*,s.cd_stationFROM series AS dLEFT JOIN stations AS sON d.id_station = s.id_station-- define station codeWHERE s.cd_station = '83377'-- define datetime rangeAND d.datetime BETWEEN '2024-01-01' AND '2024-12-31'ORDER BY d.datetime;


This query can be imported as a table to QGIS and then exported as a CSV file.

Warning: data values are scaled. Check the fields layer for scale constants.

Python script

Using the terminal, go to folder with CONV_DATABASE.gpkg and query.py



>>> cd path/to/folder


Then call the query passing the arguments:



>>> python -m query -o "path/to/output" -s "83377" --start "2020-01-01" --end "2022-01-01"


Where -s is the station code string.

 

This will yield a CSV file for the query in the output folder. 

Note: This method already converts the values to the actual numerical range.

Warning: Pandas and Geopandas are required dependencies.

Source

Data was sourced from:

INMET (2025). Meteorological Database for Education and Research (BDMEP) from National Institute of Meteorology (Instituto Nacional de Meteorologia - INMET). Available at: https://bdmep.inmet.gov.br/ Latest access: February of 2025.

 

Logs

1.0.0 -- Operational release. Changes in some fields names. Changes in file name. Changes in layer names (data changed to series). Changes in no-data value (-1 changed to -9999).

0.0.1 -- Testing release. Data updated to 2025-01-01.
DOI: 10.6084/m9.figshare.30642743
title: Data for Development of three-colour cascade FRET for force sensing of the putative RIAM-Vinculin interaction in fibroblasts

description: Raw data used to produce the Main figures for our paper entitled "Development of three-colour cascade FRET for force sensing of the putative RIAM-Vinculin interaction in fibroblasts."
DOI: 10.6084/m9.figshare.30642743.v1
title: Data for Development of three-colour cascade FRET for force sensing of the putative RIAM-Vinculin interaction in fibroblasts

description: Raw data used to produce the Main figures for our paper entitled "Development of three-colour cascade FRET for force sensing of the putative RIAM-Vinculin interaction in fibroblasts."
DOI: 10.15468/dl.me3bmy
title: Occurrence Download

description: A dataset containing 7621 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myotis dasycneme",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7621 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039891-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.52txns
title: Occurrence Download

description: A dataset containing 1466 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Buchloe dactyloides",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1466 records from 102 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039892-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13770161
title: Booru.org Top Leaderboard
DOI: 10.15468/dl.bws56x
title: Occurrence Download

description: A dataset containing 2749 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Buteogallus lacernulatus",
 "Year 2005-2024"
 ]
}

 The dataset includes 2749 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039893-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28087490
title: Supplementary tables for SAR11 genomes from the tropical Pacific study Freel et al., (2024)

description: These supplementary files are for the Freel et al., (2024) study regarding SAR11 genomes from the tropical Pacific titled "New isolate genomes and global marine metagenomes resolve ecologically relevant units of SAR11".
DOI: 10.6084/m9.figshare.28087490.v4
title: Supplementary tables for SAR11 genomes from the tropical Pacific study Freel et al., (2024)

description: These supplementary files are for the Freel et al., (2024) study regarding SAR11 genomes from the tropical Pacific titled "New isolate genomes and global marine metagenomes resolve ecologically relevant units of SAR11".
DOI: 10.6084/m9.figshare.28087490.v3
title: Supplementary tables for SAR11 genomes from the tropical Pacific study Freel et al., (2024)

description: These supplementary files are for the Freel et al., (2024) study regarding SAR11 genomes from the tropical Pacific titled "New isolate genomes and global marine metagenomes resolve ecologically relevant units of SAR11".
DOI: 10.13130/rd_unimi/flxnmd/csphl0
title: D4B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/atjyt0
title: W1B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/l5m12h
title: W6B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/hjf7g1
title: D5A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/xm80by
title: V5_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/ockuvq
title: D5A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/k0rxr9
title: D6B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/peblhc
title: V3_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/52z220
title: V6_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/japh7k
title: D2A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/4ouown
title: V6_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/uc3dgn
title: W3B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/xbq1fq
title: D2B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/tdo1kf
title: D2B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/yuurja
title: W5A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/grfljf
title: W1B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/hfdgub
title: W1A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/ynwhe7
title: W6A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/kaqvwz
title: D1A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/vmtpqz
title: D6B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/0bdrmq
title: W6B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/17xsqx
title: Metadata_Wet_Dry_aged_Beef.tab
DOI: 10.13130/rd_unimi/flxnmd/lmqy9f
title: W3B_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/eg4sed
title: V3_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/jl40xs
title: W6A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/ytw78s
title: D2A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/7pip5e
title: D4B_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/uqnkz2
title: W3A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/tysnul
title: V5_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/ydd9lt
title: W3A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/i7htg3
title: D1A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/6zgmqo
title: W5A_raw_1.fq.gz
DOI: 10.13130/rd_unimi/flxnmd/dicvfy
title: W1A_raw_2.fq.gz
DOI: 10.13130/rd_unimi/57pfim/41qs5q
title: -1.DS_Store
DOI: 10.13130/rd_unimi/57pfim/jq5cgl
title: Data array RNA.tab

description: Data Figure 2
DOI: 10.13130/rd_unimi/57pfim/jehwal
title: Figure 3 FE.tab

description: Data Figure 3
DOI: 10.13130/rd_unimi/57pfim/zogxzp
title: Figure 1.tab

description: Data Figure 1
DOI: 10.13130/rd_unimi/57pfim/t94xjg
title: Figure 2.tab

description: Data Figure 2
DOI: 10.13130/rd_unimi/57pfim/tnv3wy
title: .DS_Store
DOI: 10.13130/rd_unimi/wijkqb/mz7j3r
title: Bonizzi et al. 2025.xlsx

description: This dataset aims to collect all raw data published in the manuscript "H-ferritin nanocages: refined strategy for optimized protein production and purification" by Bonizzi A. et al. The scope of the work is to compare two lysis methods and purification protocols using the Clear coli BL21(DE3) strain as a source of HFn nanocages. Please refer to the related publication for details
 about the methodology of data collection and analysis. All data were loaded in a single file, in seven separate sheets
 (each related to a specific table or figure in the manuscript).
DOI: 10.13130/rd_unimi/iuojv2/7jvzgx
title: 21_S136781678.fasta
DOI: 10.13130/rd_unimi/iuojv2/n0qikx
title: 31_S136784661.fasta
DOI: 10.13130/rd_unimi/iuojv2/31aqqa
title: 30_S136786653.fasta
DOI: 10.13130/rd_unimi/iuojv2/nnaofq
title: 27_S136788652.fasta
DOI: 10.13130/rd_unimi/iuojv2/huexfd
title: 18_S136780682.fasta
DOI: 10.13130/rd_unimi/iuojv2/yplmuh
title: 29_S136776698.fasta
DOI: 10.13130/rd_unimi/iuojv2/vui1qc
title: 22_S136784660.fasta
DOI: 10.13130/rd_unimi/iuojv2/jy86t5
title: Metadata
DOI: 10.13130/rd_unimi/iuojv2/tzetog
title: 15_S136772698.fasta
DOI: 10.13130/rd_unimi/iuojv2/t9vbzy
title: 24_S136776697.fasta
DOI: 10.13130/rd_unimi/iuojv2/0a1xyl
title: 28_S136787652.fasta
DOI: 10.13130/rd_unimi/iuojv2/nk81j6
title: 16_S136773708.fasta
DOI: 10.13130/rd_unimi/iuojv2/aun1pp
title: 25_S136785654.fasta
DOI: 10.13130/rd_unimi/iuojv2/mx07hg
title: 17_S136786652.fasta
DOI: 10.13130/rd_unimi/iuojv2/vmkvop
title: 19_S136784659.fasta
DOI: 10.13130/rd_unimi/iuojv2/1bomqy
title: 26_S136775695.fasta
DOI: 10.13130/rd_unimi/iuojv2/juwgqg
title: 23_S136775694.fasta
DOI: 10.13130/rd_unimi/iuojv2/5kpaez
title: 20_S136780684.fasta
DOI: 10.13130/rd_unimi/ocm22p/oba0qo
title: PZ22_C_bac_T20_S50_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/6zduxy
title: PZ16_B_T20_S147_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/2soisq
title: Metadata
DOI: 10.13130/rd_unimi/ocm22p/4oyetk
title: PZ16_B_T0.fasta
DOI: 10.13130/rd_unimi/ocm22p/09xf4h
title: PZ16_B_T20_S147_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/amtbmn
title: PZ22_B_bac_T20_S49_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/y29uxy
title: PZ22_B_arc_T20_S95_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/t5hbx4
title: PZ22_B_bac_T20_S49_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/y3caze
title: PZ16_A_T20_S146_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/fvwsxe
title: PZ22_A_bac_T20_S48_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/i88ljz
title: PZ16_A_T0.fasta
DOI: 10.13130/rd_unimi/ocm22p/opnxoa
title: PZ22_A_arc_T20_S94_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/wwpy7x
title: PZ22_C_arc_T20_S96_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/z4h96p
title: PZ22_C_arc_T20_S96_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/czgpc4
title: PZ22_A_arc_T20_S94_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/6206dd
title: PZ16_C_T0.fasta
DOI: 10.13130/rd_unimi/ocm22p/sffvmf
title: PZ22_A_bac_T20_S48_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/f3b6ng
title: PZ22_B_arc_T20_S95_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/twy7cv
title: PZ22_C_bac_T20_S50_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/hwi2l3
title: PZ16_A_T20_S146_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/clvyuv
title: PZ16_C_T20_S148_L001_R2_001.fastq.gz
DOI: 10.13130/rd_unimi/ocm22p/omuffb
title: PZ16_C_T20_S148_L001_R1_001.fastq.gz
DOI: 10.13130/rd_unimi/td9t4c/rkhvkm
title: 2_SC5II.fasta
DOI: 10.13130/rd_unimi/td9t4c/ei5fqt
title: 8_EPS3.fasta
DOI: 10.13130/rd_unimi/td9t4c/8hlyej
title: Metadata.rtf
DOI: 10.13130/rd_unimi/td9t4c/gd0ykh
title: 6_SC37.fasta
DOI: 10.13130/rd_unimi/td9t4c/akkyda
title: 4_As3-5a(5).fasta
DOI: 10.13130/rd_unimi/td9t4c/suxyul
title: 5_SC26.fasta
DOI: 10.13130/rd_unimi/td9t4c/mur5jd
title: 7_SC23.fasta
DOI: 10.13130/rd_unimi/td9t4c/iuqfex
title: 9_EPS5.fasta
DOI: 10.13130/rd_unimi/td9t4c/osrr1c
title: 3_SC3I(2).fasta
DOI: 10.13130/rd_unimi/td9t4c/zlch4u
title: 1_13a.fasta
DOI: 10.15468/dl.bsbjuc
title: Occurrence Download

description: A dataset containing 1895 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "NetworkKey is 99d66b6c-9087-452f-a9d4-f15f2c2d0e7e",
 "TaxonKey is Chordata"
 ]
 },
 {
 "and" : [
 "BasisOfRecord is one of (Specimen)",
 "TaxonKey is one of (Passerella iliaca [GBIF Backbone Taxonomy], Spizelloides arborea [GBIF Backbone Taxonomy], Catharus minimus [GBIF Backbone Taxonomy], Setophaga striata [GBIF Backbone Taxonomy], Leiothlypis celata [GBIF Backbone Taxonomy], Zonotrichia leucophrys [GBIF Backbone Taxonomy], Zonotrichia querula [GBIF Backbone Taxonomy], Cardellina pusilla [GBIF Backbone Taxonomy])",
 "Country is one of (United States of America, Canada)",
 "EventDate 1985-01-01-2025-08-15",
 {
 "and" : [
 "EndDayOfYear is less than or equal to 227"
 ]
 },
 {
 "and" : [
 "StartDayOfYear is greater than or equal to 145"
 ]
 }
 ]
 }
 ]
}

 The dataset includes 1895 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039895-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13130/rd_unimi/dp08sc
title: UMILRawData_Deliverable 5.2

description: This dataset collects all the raw data explained of the deliverable 5.2
DOI: 10.13130/rd_unimi/dp08sc/9ok1bp
title: IVD_NMBU shipment 3_chronic exposure_TEER.xlsx.tab
DOI: 10.13130/rd_unimi/dp08sc/mdpt2z
title: IVD_NMBU shipment 2_chronic exposure_TEER.tab
DOI: 10.13130/rd_unimi/dp08sc/dcnwua
title: IVD_NMBU shipment 3_chronic exposure_ANPEP.xlsx.tab
DOI: 10.13130/rd_unimi/dp08sc/smsozh
title: IVD_NMBU shipment 2_cytotoxicity_TEER.tab
DOI: 10.13130/rd_unimi/dp08sc/vkkfow
title: IVD_NMBU shipment 2_chronic exposure_ANPEP.tab
DOI: 10.13130/rd_unimi/dp08sc/0cb2hf
title: IVD_NMBU shipment 1_cytotoxicity_TEER.tab
DOI: 10.13130/rd_unimi/dp08sc/6fov5f
title: IVD_NMBU shipment 2_cytotoxicity_NRU.tab
DOI: 10.13130/rd_unimi/dp08sc/uoejia
title: IVD_NMBU shipment 1_cytotoxicity_PAPP.xlsx
DOI: 10.13130/rd_unimi/dp08sc/ivq5kk
title: IVD_NMBU shipment 1_cytotoxicity_NRU.tab
DOI: 10.13130/rd_unimi/dp08sc/ln1cmp
title: IVD_NMBU shipment 3_preliminary data_AAquantification.tab
DOI: 10.13130/rd_unimi/dp08sc/ermynw
title: README.txt
DOI: 10.13130/rd_unimi/p1oesm/70liyx
title: Data processing and Analysis_Ms.xlsx
DOI: 10.13130/rd_unimi/p1oesm/yq0vgz
title: pProteomic Report-Fig 4B.tab
DOI: 10.13130/rd_unimi/dyn4rw/7zhfou
title: 2021-09-09 CD4 pos GLP1R pos plate 2.xls
DOI: 10.13130/rd_unimi/dyn4rw/v5rqag
title: 2021-09-17 CD8posGLP1Rneg PLATE 2.xls
DOI: 10.13130/rd_unimi/dyn4rw/gylh3z
title: 2021-09-16 CD8posGLP1Rneg PLATE 1.xls
DOI: 10.13130/rd_unimi/dyn4rw/nguz0n
title: 2021-09-09 CD4 pos GLP1R pos plate 1.xls
DOI: 10.13130/rd_unimi/dyn4rw/tuimdd
title: 2021-09-17 CD8posGLP1Rpos PLATE 2.xls
DOI: 10.13130/rd_unimi/dyn4rw/0pujpc
title: 2021-09-09 CD4posGLP1neg PLATE 2.xls
DOI: 10.13130/rd_unimi/dyn4rw/k3kqf7
title: 2021-09-16 CD8posGLP1Rpos PLATE 1.xls
DOI: 10.13130/rd_unimi/dyn4rw/ne8yi5
title: 2021-09-08 CD4posGLP1neg PLATE 1.xls
DOI: 10.13130/rd_unimi/d7qmde/jvghch
title: Piu_S9_L001_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/xddul4
title: Piu_S9_L002_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/yjp8rh
title: Piu_S14_L002_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/kfukuz
title: Meno_S10_L002_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/zdioij
title: Piu_S9_L001_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/t5xqff
title: Piu_S9_L002_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/a5fk8q
title: Meno_S15_L002_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/dm4aor
title: Meno_S10_L002_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/1l0w2c
title: Meno_S10_L002_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/7jv74i
title: Piu_S9_L002_R1_001.fastq-1.gz
DOI: 10.15468/dl.5rda9w
title: Occurrence Download

description: A dataset containing 6420 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pulsatrix koeniswaldiana",
 "Year 2005-2024"
 ]
}

 The dataset includes 6420 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039896-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13130/rd_unimi/d7qmde/rcjipk
title: Meno_S10_L001_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/uiscph
title: Meno_S15_L002_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/bzitof
title: Piu.counts.tsv-1.gz
DOI: 10.13130/rd_unimi/d7qmde/kanpkw
title: Meno_S15_L002_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/qvvea0
title: Report_BenNasrM_1922_scRNAseq-1.html
DOI: 10.13130/rd_unimi/d7qmde/9nhsgq
title: Piu_S14_L002_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/hrxg9u
title: Meno_S15_L001_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/6e93tx
title: md5sum-3.txt
DOI: 10.13130/rd_unimi/d7qmde/rp6gjw
title: Meno_S10_L001_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/ujjrwk
title: -1.DS_Store
DOI: 10.13130/rd_unimi/d7qmde/hhb8z7
title: Piu_S14_L001_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/uothau
title: Piu_S14_L002_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/ex8l4x
title: md5sum-2.txt
DOI: 10.13130/rd_unimi/d7qmde/2mlvev
title: Meno_S15_L001_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/5fbadi
title: Meno_S10_L001_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/gbzzih
title: BenNasrM_1922_scRNAseq_integration-1.html
DOI: 10.13130/rd_unimi/d7qmde/wnlmpc
title: Piu_S9_L001_R2_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/3vdxod
title: Meno_S15_L001_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/97xkoe
title: Meno.counts.tsv-1.gz
DOI: 10.13130/rd_unimi/d7qmde/jpw2ln
title: -2.DS_Store
DOI: 10.5281/zenodo.17631157
title: Dataset and Replication package for Platform-Specific APIs, Defensive Code, and Security Issues: Are They Related?

description: This dataset was utilized in the research paper titled "Platform-Specific APIs, Defensive Code, and Security Issues: AreThey Related?" for publication in International Conference on Program Comprehension (ICPC).

 

We provide a roadmap to replicate all the steps of our methodology.

More information in the REPLICABILITY.md file.

 

Herein, we present a concise abstract of the study:

 

A platform-specific API is an interface implemented for a particular platform (e.g., Windows or Linux) that may not function correctly on others.

This paper presents a first empirical study of platform-specific APIs in the Python Standard Library, examining their relationship with defensive structures and their association with security issues.Our results show that platform-specific API usage is common in the Python Standard Library.We identified 12,728 cases of platform-specific APIs, of which 74% occur without defensive structures (RQ1). Furthermore, Bandit reported 2,417 security issues, of which 23% are related to platform-specific APIs (RQ2).These findings reveal that APIs that facilitate cross-platform compatibility can also introduce potential security issues.We conclude by discussing implications for both practitioners and researchers concerning cross-platform development and the trade-off between compatibility and security in the Python Standard Library.
DOI: 10.5281/zenodo.17631158
title: Dataset and Replication package for Platform-Specific APIs, Defensive Code, and Security Issues: Are They Related?

description: This dataset was utilized in the research paper titled "Platform-Specific APIs, Defensive Code, and Security Issues: AreThey Related?" for publication in International Conference on Program Comprehension (ICPC).

 

We provide a roadmap to replicate all the steps of our methodology.

More information in the REPLICABILITY.md file.

 

Herein, we present a concise abstract of the study:

 

A platform-specific API is an interface implemented for a particular platform (e.g., Windows or Linux) that may not function correctly on others.

This paper presents a first empirical study of platform-specific APIs in the Python Standard Library, examining their relationship with defensive structures and their association with security issues.Our results show that platform-specific API usage is common in the Python Standard Library.We identified 12,728 cases of platform-specific APIs, of which 74% occur without defensive structures (RQ1). Furthermore, Bandit reported 2,417 security issues, of which 23% are related to platform-specific APIs (RQ2).These findings reveal that APIs that facilitate cross-platform compatibility can also introduce potential security issues.We conclude by discussing implications for both practitioners and researchers concerning cross-platform development and the trade-off between compatibility and security in the Python Standard Library.
DOI: 10.13130/rd_unimi/d7qmde/1uqhtw
title: Piu_S14_L001_I1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/d7qmde/wnigbf
title: Piu_S14_L001_R1_001.fastq-1.gz
DOI: 10.13130/rd_unimi/oqb5le/kyurip
title: Tab. S2 growth increments G. vitreus and L. uva.tab
DOI: 10.13130/rd_unimi/oqb5le/7040s4
title: Brachiopods_as_archives_of_intra_and_interannual_environmental_variations.zip
DOI: 10.13130/rd_unimi/oqb5le/yskfii
title: Tab. S1 Stable Isotope and TE data.tab
DOI: 10.13130/rd_unimi/oqb5le/grhozq
title: README.md
DOI: 10.13130/rd_unimi/5879zg
title: Replication Data for: Predicting the binding of small molecules to proteins through invariant representation of the molecular structure

description: Network parameters and datasets to reproduce the results of the article "Predicting the binding of small molecules to proteins through invariant representation of the molecular structure" by R. Beccaria, A. Lazzeri and G. Tiana.
The scripts and the instructions can be obtained from https://github.com/guidotiana/Milbinding
DOI: 10.13130/rd_unimi/5879zg/i9rxf6
title: bins_ligand.npy
DOI: 10.13130/rd_unimi/5879zg/ogv0jo
title: final_random_forests_Best_DUDE_on_DUDE_40bins_rf_val_NoRep
DOI: 10.13130/rd_unimi/5879zg/v4iiu5
title: MUV_Properties_matrixes_for_regression.npy
DOI: 10.13130/rd_unimi/5879zg/ylgiyo
title: Binding_DB_my_filter_lig.npy
DOI: 10.13130/rd_unimi/5879zg/2osyxj
title: Binding_DB_train_dataset.npz
DOI: 10.13130/rd_unimi/5879zg/wyyfsr
title: DUDE_validation_matrix.npz
DOI: 10.21424/r4159q
title: CRREL/UCSB Energy Site
DOI: 10.13130/rd_unimi/5879zg/m7fn98
title: MUV_Properties_regressor_models_polararea_nn_val_polararea.pt
DOI: 10.13130/rd_unimi/5879zg/qhfit5
title: DUDE_target_val.npy
DOI: 10.13130/rd_unimi/5879zg/scefau
title: MUV_target_train.npy
DOI: 10.13130/rd_unimi/5879zg/7qhf1f
title: bins_pocket.npy
DOI: 10.13130/rd_unimi/5879zg/bpvegy
title: equivariant_autoencoder_128_ELU_ELU_500_1_3_1_1_3_3_8_0_200_1_model_val.pt
DOI: 10.13130/rd_unimi/5879zg/ewmvzq
title: MUV_validation_matrix.npz
DOI: 10.13130/rd_unimi/5879zg/i8comk
title: MUV_Properties_norm_values.npy
DOI: 10.13130/rd_unimi/5879zg/k3kupz
title: filters_names_bins_my_filter_lig.npy
DOI: 10.13130/rd_unimi/5879zg/qf4aue
title: 5exm.pdb
DOI: 10.13130/rd_unimi/5879zg/k0dtmt
title: final_random_forests_Best_DUDE_on_BindingDB_4bins_rf_val_NoRep
DOI: 10.13130/rd_unimi/5879zg/mejw5j
title: MUV_training_matrix.npz
DOI: 10.13130/rd_unimi/5879zg/kswnj5
title: filters_bins_name_pocket.npy
DOI: 10.13130/rd_unimi/5879zg/mzawer
title: filters_bins_pocket.npy
DOI: 10.13130/rd_unimi/5879zg/sy9wxa
title: Binding_DB_training_matrix.npz
DOI: 10.13130/rd_unimi/5879zg/dg9xgn
title: MUV_Properties_regressor_models_nn_val_xlogp.pt