cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15742532
title: Dataset and Scripts for 'Trade-off between Cost and Performance of Earth Observation Data in Olive Tree Health Assessment Using Machine Learning

description: This dataset supports the research article : Bouslihim, Y., Bouasria, A., Rochdi, A., Haissen, E. B. E., Loczy, D., Orban, Z., & Salem, A. (2025). Trade-off between cost and performance of earth observation data in olive trees health assessment: Digital crop mapping approach using machine learning algorithms. International Journal of Applied Earth Observation and Geoinformation, 142, 104732. https://doi.org/10.1016/j.jag.2025.104732. 

Data was collected and processed under the "Olive Trees Health and Yield Prediction through EO Data and Machine Learning" project, funded by the European Space Agency (ESA) within the framework of the EO AFRICA R&D Facility.

The dataset includes both raw and processed Earth Observation (EO) data as well as the full set of R scripts used in data preprocessing, machine learning model training, and evaluation. The study investigates how different EO data sources (e.g., Sentinel-2, Mohammed VI satellite, UAV imagery) compare in terms of cost-effectiveness and predictive performance for assessing olive tree health in a Mediterranean agroecosystem.

All materials are archived in a single compressed .rar file labeled "SCRIPTS & DATA", which contains:





Preprocessed EO datasets used in the analysis




Field-based ground truth data for validation




R scripts implementing feature extraction, model training, and evaluation pipelines



This repository is intended to facilitate transparency, reproducibility, and reuse of the research workflow and data by the scientific community.
DOI: 10.15468/dl.jk2kxr
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rattus norvegicus",
 "Country is Albania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023407-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15869377
title: Data and code for "A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable"

description: A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable


Authors: Tristan Stérin, Abeer Eshra, Janet Adio, Constantine G. Evans, Damien Woods


This archive contains all the data and code related to the manuscript *A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable*. This archive version (v1) is for the first Bioarxiv version of the manuscript.


See each folder of the archive for detailed instructions. Note that, in general, code needs to be run on a Unix-like (Mac OS or Linux) system; for Windows, however, WSL2 may be usable. Folders contain:




`0_DNA_sequence_design_code`: source code used to generate the DNA sequences for the DNA implementation of our SDC system.

`1_thermodynamic_analysis_code`: source code used to analyse theoretical thermodynamic properties of the SDC system.

`2_raw_qpcr_data`: all of the raw qPCR machine data of the project (only type of data that we use) acquired using several QuantStudio 5 machines (Applied Biosystems).

`3_data_plotting_code`: code used to generate all plots shown in the paper.

`4_data_analysis_code`: code used to generate all metrics reported in the paper.

`5_scaleup_code_modelling_and_analysis`: code analysing the sequence energetics, kinetics, and sink structure (for ADDITION) of scaled-up systems (11-domain and 25-domain scaffold).

`6_scaleup_data_and_code`: qPCR machine data, Echo picklists, and temperature protocols for scaled-up (length 11 and 25) systems, as well as code for data analysis and generation of main text Figure 6 and relevant SI plots.

`experiments_database.xlsx`: Excel database giving an overview of the pre-scale-up dataset and computed statistics. The file links each experiment to a raw qpcr machine data file, also it contains fields with statistics that were computed using the above code from the data for convenience. Scale-up data and statistics are in `5_scaleup_data_and_code`.


Licensing


Unless otherwise noted, all code is licensed under the MIT License.


Funding


Research supported by the European Union’s European Research Council (ERC, Active-DNA, no 772766); European Innovation Council (EIC, DISCO, No 101115422); and Science Foundation Ireland (SFI) under grant numbers 18/ERCS/5746 and 20/FFP-P/8843. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, European Research Council, European Innovation Council or Science Foundation Ireland. Neither the European Union nor the granting authority can be held responsible for them. The authors declare competing financial interest: listed as inventors on pending patents.
DOI: 10.5281/zenodo.15869378
title: Data and code for "A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable"

description: A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable


Authors: Tristan Stérin, Abeer Eshra, Janet Adio, Constantine G. Evans, Damien Woods


This archive contains all the data and code related to the manuscript *A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable*. This archive version (v1) is for the first Bioarxiv version of the manuscript.


See each folder of the archive for detailed instructions. Note that, in general, code needs to be run on a Unix-like (Mac OS or Linux) system; for Windows, however, WSL2 may be usable. Folders contain:




`0_DNA_sequence_design_code`: source code used to generate the DNA sequences for the DNA implementation of our SDC system.

`1_thermodynamic_analysis_code`: source code used to analyse theoretical thermodynamic properties of the SDC system.

`2_raw_qpcr_data`: all of the raw qPCR machine data of the project (only type of data that we use) acquired using several QuantStudio 5 machines (Applied Biosystems).

`3_data_plotting_code`: code used to generate all plots shown in the paper.

`4_data_analysis_code`: code used to generate all metrics reported in the paper.

`5_scaleup_code_modelling_and_analysis`: code analysing the sequence energetics, kinetics, and sink structure (for ADDITION) of scaled-up systems (11-domain and 25-domain scaffold).

`6_scaleup_data_and_code`: qPCR machine data, Echo picklists, and temperature protocols for scaled-up (length 11 and 25) systems, as well as code for data analysis and generation of main text Figure 6 and relevant SI plots.

`experiments_database.xlsx`: Excel database giving an overview of the pre-scale-up dataset and computed statistics. The file links each experiment to a raw qpcr machine data file, also it contains fields with statistics that were computed using the above code from the data for convenience. Scale-up data and statistics are in `5_scaleup_data_and_code`.


Licensing


Unless otherwise noted, all code is licensed under the MIT License.


Funding


Research supported by the European Union’s European Research Council (ERC, Active-DNA, no 772766); European Innovation Council (EIC, DISCO, No 101115422); and Science Foundation Ireland (SFI) under grant numbers 18/ERCS/5746 and 20/FFP-P/8843. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, European Research Council, European Innovation Council or Science Foundation Ireland. Neither the European Union nor the granting authority can be held responsible for them. The authors declare competing financial interest: listed as inventors on pending patents.
DOI: 10.5281/zenodo.15972431
title: Mental Health Sentiment Analysis Using Social Media Texts

description: This project aims to analyze public sentiment related to mental health and suicide by processing text data from social media and other open sources. It uses natural language processing (NLP) and machine learning techniques to classify user-generated content into positive, negative, and neutral sentiments. The goal is to identify emotional patterns that could help in early detection of mental distress and promote timely support.

The repository contains:





Cleaned and preprocessed dataset (.csv)




Python code for sentiment analysis




Model training scripts using scikit-learn and/or deep learning




Visualizations for data exploration and sentiment trends



This resource can be valuable for researchers, mental health professionals, and developers building mental health-aware AI systems.

Disclaimer: This dataset is for academic and research purposes only. It does not replace clinical advice or diagnosis.
DOI: 10.15468/dl.tb4tz7
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cardamine coronata"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023408-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.he8ng4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sturnella magna)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023413-250711103210423/datasets/export for details.
DOI: 10.15468/dl.gjreh8
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AAC1771"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023409-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.34des4
title: Occurrence Download

description: A dataset containing 226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scirpus hoppei, Scirpus lejeunei, Scirpus mucronatus, Scirpus pollichii, Scirpus pollichii coriacea, Scirpus seoanei, Scirpus trigonus, Scirpus triquertrus, Scirpus triqueter, Scirpus triqueter conglomeratus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 226 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023414-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/iwowui
title: Fleet Tire Metrics

description: The dataset was created by Prometeon Tyre Group and includes information on tire pressure (PSI), temperature (°C), and vehicle speed (km/h). Data collection took place during multiple trips along a designated route between the cities of São Paulo and Presidente Prudente, both located in the state of São Paulo, Brazil. A fleet bus equipped with six monitored 295/80R22.5 FR01 tires was used for this purpose.

Tire pressure and temperature measurements were recorded using Schrader TPMS (Tire Pressure Monitoring System) sensors - model TMS5. The tires were labeled based on their position on the vehicle: Front Right (FR), Front Left (FL), Rear Right Inner (RRI), Rear Left Inner (RLI), Rear Right Outer (RRO), and Rear Left Outer (RLO), as illustrated in Figure &lt;i&gt;fleet_tires_position&lt;/i&gt;.
DOI: 10.15468/dl.cv6wyv
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rattus norvegicus",
 "Country is Angola",
 "HasCoordinate is true"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023417-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.va4psk
title: Occurrence Download

description: A dataset containing 25357 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nothoscordum bivalve"
 ]
}

 The dataset includes 25357 records from 291 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023411-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jzhqdc
title: Occurrence Download

description: A dataset containing 2140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Psittacula krameri",
 "Country is Pakistan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2140 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023415-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.46b8w5
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Draba yukonensis"
 ]
}

 The dataset includes 121 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023418-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15972000
title: Images for 9RZG
DOI: 10.5281/zenodo.15971999
title: Images for 9RZG
DOI: 10.5281/zenodo.15973316
title: Dataset for Collective Intelligence Architecture for IoT Using Federated Process Mining

description: This dataset contains the key elements used in the paper Collective Intelligence Architecture for IoT Using Federated Process Mining which range from complex event processing to process mining applied over multiple datasets. The information included is organized into the following sections:

1.- CEPApp.siddhi: It contains the rules and configurations used for pattern detection and real-time event processing.

2.- ProcessStorage.sol: Smart contract code used in the case study implemented on solidity using Polygon blockchain platform.

3.- Datasets Used ({adlinterweave_dataset, adlmr_dataset, twor_dataset}.zip): Three datasets used in the study, each with events that have been processed using the CEP engine.

4.- CEP Engine Processing Results ({cepresult_adlinterweave, cepresult_adlmr, cepresult_twor}.json): Output generated by the Siddhi CEP engine, stored in JSON format.

5.- Federated Event Logs ({xesresult_adlinterweave, xesresult_adlmr, xesresult_twor}.xes): Federated event logs in XES format, standard in process mining. Contains event traces obtained after the execution of the Event Log Integrator.

6.- Process Mining Results: Models generated from the processed event logs:



Process Trees ({procestree_adlinterweave, procestree_adlmr, procestree_twor}.svg): structured representation of the detected workflows.

Petri Nets ({petrinet_adlinterweave, petrinet_adlmr, petrinet_twor}.svg): Mathematical model of the discovered processes, useful for compliance analysis and simulations.

Disco Results ({disco_adlinterweave, disco_adlmr, disco_twor}.pdf): Process models discovered with the Disco tool.

ProM Results ({prom_adlinterweave, prom_adlmr, prom_twor}.pdf): Models generated with ProM tool.
DOI: 10.5281/zenodo.15973315
title: Dataset for Collective Intelligence Architecture for IoT Using Federated Process Mining

description: This dataset contains the key elements used in the paper Collective Intelligence Architecture for IoT Using Federated Process Mining which range from complex event processing to process mining applied over multiple datasets. The information included is organized into the following sections:

1.- CEPApp.siddhi: It contains the rules and configurations used for pattern detection and real-time event processing.

2.- ProcessStorage.sol: Smart contract code used in the case study implemented on solidity using Polygon blockchain platform.

3.- Datasets Used ({adlinterweave_dataset, adlmr_dataset, twor_dataset}.zip): Three datasets used in the study, each with events that have been processed using the CEP engine.

4.- CEP Engine Processing Results ({cepresult_adlinterweave, cepresult_adlmr, cepresult_twor}.json): Output generated by the Siddhi CEP engine, stored in JSON format.

5.- Federated Event Logs ({xesresult_adlinterweave, xesresult_adlmr, xesresult_twor}.xes): Federated event logs in XES format, standard in process mining. Contains event traces obtained after the execution of the Event Log Integrator.

6.- Process Mining Results: Models generated from the processed event logs:



Process Trees ({procestree_adlinterweave, procestree_adlmr, procestree_twor}.svg): structured representation of the detected workflows.

Petri Nets ({petrinet_adlinterweave, petrinet_adlmr, petrinet_twor}.svg): Mathematical model of the discovered processes, useful for compliance analysis and simulations.

Disco Results ({disco_adlinterweave, disco_adlmr, disco_twor}.pdf): Process models discovered with the Disco tool.

ProM Results ({prom_adlinterweave, prom_adlmr, prom_twor}.pdf): Models generated with ProM tool.
DOI: 10.15468/dl.eh6j6x
title: Occurrence Download

description: A dataset containing 5921 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 5921 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023420-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h7h7c8
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opsopoeodus bollmani"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023422-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pmjc86
title: Occurrence Download

description: A dataset containing 63 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.datasetkey = 'ed6df385-67ec-4872-ad25-e6e76ca2dcb1'
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 63 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023412-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dmmzzd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scirpus triqueter macrostachys, Scirpus triqueter monostachys, Scirpus triqueter pallidus, Scirpus triqueter conglomeratus, Scirpus triqueter hoppei, Scirpus triqueter lejeunei, Scirpus triqueter macrostachys, Scirpus triqueter monostachys, Scirpus triqueter pallidus, Scirpus triqueter segregatus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023423-250711103210423/datasets/export for details.
DOI: 10.15468/dl.dke7fw
title: Occurrence Download

description: A dataset containing 391 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Elodea densa, Koenigia polystachya, Hydrocharis laevigata)",
 "BasisOfRecord is one of (Observation, Human Observation, Material sample, Specimen, Unknown evidence, Machine Observation, Occurrence evidence)",
 "Year is greater than or equal to 1971",
 "Year is less than or equal to 1980",
 "HasCoordinate is true"
 ]
}

 The dataset includes 391 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023424-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.phhpxz
title: Occurrence Download

description: A dataset containing 24370 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 24370 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023410-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e6rtbk
title: Occurrence Download

description: A dataset containing 1933 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eremobium aegyptiacum"
 ]
}

 The dataset includes 1933 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023421-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.