cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.cwt7ep
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((98.858 1.861181, 98.7877 1.855613, 98.719133 1.839045, 98.653987 1.811886, 98.593868 1.774806, 98.540256 1.728717, 98.494471 1.674755, 98.457641 1.61425, 98.430671 1.548691, 98.414225 1.479694, 98.40870700000001 1.408956, 98.414252 1.338221, 98.430722 1.26923, 98.457711 1.203681, 98.494553 1.143187, 98.540342 1.089238, 98.59395000000001 1.043163, 98.65405699999999 1.006094, 98.719184 0.978945, 98.787727 0.962383, 98.858 0.956817, 98.928273 0.962383, 98.996816 0.978945, 99.061943 1.006094, 99.12205 1.043163, 99.175658 1.089238, 99.221447 1.143187, 99.258289 1.203681, 99.28527800000001 1.26923, 99.301748 1.338221, 99.307293 1.408956, 99.30177500000001 1.479694, 99.285329 1.548691, 99.258359 1.61425, 99.221529 1.674755, 99.17574399999999 1.728717, 99.12213199999999 1.774806, 99.06201299999999 1.811886, 98.99686699999999 1.839045, 98.92829999999999 1.855613, 98.858 1.861181))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002966-260120142942310/datasets/export for details.
DOI: 10.60520/ieda/114299
title: Whole rock and mineral data for hornblende−rich cumulates in the Gangdese arc, south Tibet

description: This dataset contains whole-rock major, trace element and isotopic analyses, mineral major and trace elements, zircon U-Pb geochronology and Hf isotope data for hornblende−rich cumulates in the Gangdese arc, south Tibet. The data were obtained by XRF, ICP-MS and EMP State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China (SKLaBIG, GIG, CAS) and by LA-ICP-MS at the Institute of Geology and Geophysics, Chinese Academy of Sciences (IGGCAS), Beijing, China. The data were used to trace the evolution of deep magma reservoir from the Late Jurassic Gangdese arc, south Tibet.
DOI: 10.57710/alba-es-20250340034
title: Importance of substrate spin-orbit coupling in layers of chiral organic molecules on metal surfaces, and the origin of the CISS effect

description: A great deal of attention is being devoted to the study of the CISS (Chiral-Induced Spin Selectivity) effect, which describes the appearance of spin polarization in electrons transmitted through homochiral media in absence of magnetic elements. This phenomenon has already been confirmed by a multitude of experimental observations and can revolutionize fields such as molecular spintronics or pharmacology, by providing means to separate enantiomers for biological or medical use. Nevertheless, a satisfactory theoretical understanding has not yet been reached, and there exists considerable debate regarding the role and magnitude of the spin-orbit coupling (SOC) in these systems and its importance in achieving the observed spin polarization. 
We propose to carry out a systematic analysis of the effects of SOC strength by using X ray circular dichroism in absorption to study the induced magnetic moments appearing in layers of homochiral organic molecules adsorbed on Al(111), Cu(111) and Au(111) metal surfaces, resolving separately the orbital and spin contributions. These substrates feature amply different SOCs, and the deposited chiral organic compounds, methylbenzylamine and diphenylethylenediamine, have different but closely related configurations possessing 1 and 2 chiral centers respectively. With these experiments we expect to identify relevant trends and shed light on the fundamental origin of this suggestive effect.
DOI: 10.15468/dl.854rks
title: Occurrence Download

description: A dataset containing 263 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-73.24299999999999 4.384161, -73.313467 4.378591, -73.38219700000001 4.362019, -73.44749299999999 4.334853, -73.507746 4.297763, -73.561471 4.251664, -73.60734600000001 4.197693, -73.64424 4.137179, -73.67124800000001 4.071614, -73.68770499999999 4.002614, -73.69320999999999 3.931878, -73.68763 3.861148, -73.671105 3.792165, -73.64404399999999 3.726627, -73.60711499999999 3.666146, -73.561229 3.612212, -73.507515 3.56615, -73.44729599999999 3.529093, -73.382054 3.501954, -73.31339199999999 3.485398, -73.24299999999999 3.479834, -73.172608 3.485398, -73.10394599999999 3.501954, -73.038704 3.529093, -72.97848500000001 3.56615, -72.92477100000001 3.612212, -72.878885 3.666146, -72.841956 3.726627, -72.81489500000001 3.792165, -72.79837000000001 3.861148, -72.79279 3.931878, -72.798295 4.002614, -72.814752 4.071614, -72.84175999999999 4.137179, -72.878654 4.197693, -72.92452900000001 4.251664, -72.97825400000001 4.297763, -73.038507 4.334853, -73.103803 4.362019, -73.172533 4.378591, -73.24299999999999 4.384161))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 263 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002967-260120142942310/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.31116069
title: Computerized instruments for assessment of executive function: a scoping review with emphasis on game-based assessment

description: This review aimed to identify and characterize computerized neuropsychological instruments used for executive function (EF) assessment, with a focus on digital games. Guided by the PRISMA-ScR protocol, the review included studies from multiple databases without time restrictions, resulting in the selection of 312 studies from an initial pool of 3,347. Most studies were published between 2020 and 2022, predominantly in North America and Europe. While computerized tests (<i>n</i> = 283) were widely used and more established, digital games (<i>n</i> = 29) were less common and mainly in exploratory stages. The most frequently assessed EF components were core domains such as working memory, inhibitory control, and cognitive flexibility. Children and adolescents were underrepresented among the study populations. The analysis revealed wide variation in game terminology, technology, and outcome indicators, reflecting a lack of standardization. Overall, computerized tests dominate the field in both research and clinical practice. Although digital games hold significant potential for EF assessment, especially due to their engaging nature, more research is needed to standardize these tools and establish their psychometric validity. The review contributes to mapping the current landscape and identifying critical gaps for future development and implementation of digital tools in neuropsychological assessment.
DOI: 10.6084/m9.figshare.31116069.v1
title: Computerized instruments for assessment of executive function: a scoping review with emphasis on game-based assessment

description: This review aimed to identify and characterize computerized neuropsychological instruments used for executive function (EF) assessment, with a focus on digital games. Guided by the PRISMA-ScR protocol, the review included studies from multiple databases without time restrictions, resulting in the selection of 312 studies from an initial pool of 3,347. Most studies were published between 2020 and 2022, predominantly in North America and Europe. While computerized tests (<i>n</i> = 283) were widely used and more established, digital games (<i>n</i> = 29) were less common and mainly in exploratory stages. The most frequently assessed EF components were core domains such as working memory, inhibitory control, and cognitive flexibility. Children and adolescents were underrepresented among the study populations. The analysis revealed wide variation in game terminology, technology, and outcome indicators, reflecting a lack of standardization. Overall, computerized tests dominate the field in both research and clinical practice. Although digital games hold significant potential for EF assessment, especially due to their engaging nature, more research is needed to standardize these tools and establish their psychometric validity. The review contributes to mapping the current landscape and identifying critical gaps for future development and implementation of digital tools in neuropsychological assessment.
DOI: 10.6084/m9.figshare.25444247
title: Unlocking personal data from online services: user studies on data export experiences and data transfer scenarios

description: In recent years, online services have started to make personal data of users more accessible by offering dedicated ways of exporting data. The introduction of download portals is associated with increasing demands by privacy regulations regarding the rights of users, such as the Right of Access (Art. 15) and the Right to Data Portability (Art. 20) of the European Union’s General Data Protection Regulation (GDPR). These rights aim to empower users by increasing their control over the personal data that online services hold about them. They allow users to export their personal data and thereby gain insights on the scope of personal data held by the services and to transfer this data to other services. However, until now, little is known about how users experience and evaluate the process of accessing and exporting their data and how it impacts individual-level factors such as privacy-related attitudes (i.e. attitudes regarding sharing personal data, perceived control over data, and using privacy-protective strategies). In this paper, we report the results of an online survey with an experimental condition (<i>N</i> = 728) and a second online survey (<i>N</i> = 817) where participants from two university courses were asked to request real data exports from online services and inspect the exported data afterward. We find that inspecting exported personal data has a statistically significant positive effect on users’ privacy-related attitudes. However, users perceive limited usefulness in switching scenarios where personal data is transferred to a new substitutional service and rather prefer to use the data at multiple complementary services.
DOI: 10.6084/m9.figshare.25444247.v1
title: Unlocking personal data from online services: user studies on data export experiences and data transfer scenarios

description: In recent years, online services have started to make personal data of users more accessible by offering dedicated ways of exporting data. The introduction of download portals is associated with increasing demands by privacy regulations regarding the rights of users, such as the Right of Access (Art. 15) and the Right to Data Portability (Art. 20) of the European Union’s General Data Protection Regulation (GDPR). These rights aim to empower users by increasing their control over the personal data that online services hold about them. They allow users to export their personal data and thereby gain insights on the scope of personal data held by the services and to transfer this data to other services. However, until now, little is known about how users experience and evaluate the process of accessing and exporting their data and how it impacts individual-level factors such as privacy-related attitudes (i.e. attitudes regarding sharing personal data, perceived control over data, and using privacy-protective strategies). In this paper, we report the results of an online survey with an experimental condition (<i>N</i> = 728) and a second online survey (<i>N</i> = 817) where participants from two university courses were asked to request real data exports from online services and inspect the exported data afterward. We find that inspecting exported personal data has a statistically significant positive effect on users’ privacy-related attitudes. However, users perceive limited usefulness in switching scenarios where personal data is transferred to a new substitutional service and rather prefer to use the data at multiple complementary services.
DOI: 10.15468/dl.kgca9s
title: Occurrence Download

description: A dataset containing 346 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pegias fabula"
 ]
}

 The dataset includes 346 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002968-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18317741
title: Global Public Domain Database of Allosteric Pharmacophores for 50+ Critical Drug Targets (KRAS, p53, PCSK9, SMN2)

description: The Global Public Domain Database of Allosteric Pharmacophores (v2.0 - Complete Trilogy)

1. Executive Summary & Legal Declaration This repository constitutes a comprehensive strategic disclosure of over 150 critical therapeutic targets, releasing precise 3D coordinates (X, Y, Z) of computationally identified allosteric binding sites into the Global Public Domain.

By publishing this dataset under the CC0 1.0 Universal License, the author explicitly waives all copyright and related rights. These disclosures serve as "PRIOR ART" under 35 U.S.C. § 102 (USA) and Article 54 of the European Patent Convention (EPC). Any subsequent patent application claiming "novelty" for small molecules binding specifically to the cryptic pockets disclosed herein is legally invalid.

2. Methodology: The Lrenom Protocol Target structures were analyzed using a proprietary Inverse Covariance Matrix (Precision Matrix) approach, filtered by the topological Lrenom Constant (Λr≈1.1107). This mathematical filter effectively distinguishes obligate functional allosteric sites from transient thermal noise, identifying high-affinity "lock-and-key" mechanisms previously unknown or undisclosed by the pharmaceutical industry.

3. Dataset Contents (The Trilogy)

📂 PART 1: ONCOLOGY & METABOLIC TARGETS (Dataset_01_...csv)





Target Scope: The "Undruggable" Cancer Targets & Chronic Diseases.




Key Targets: KRAS G12C, p53 (Y220C Stabilizer), EGFR T790M, PCSK9 (Cholesterol), SMN2 (SMA), and Beta-Amyloid (Alzheimer).




Impact: Preempts monopolies on next-generation cancer therapies and gene modulation.



📂 PART 2: IMMUNOLOGY & ANTIMICROBIAL RESISTANCE (Dataset_02_...csv)





Target Scope: Autoimmune Blockbusters & Superbugs.




Key Targets: TNF-Alpha (Humira target), JAK1/2/3 Kinases, IL-17A, NDM-1 (New Delhi Metallo-beta-lactamase), MRSA PBP2a, and Vancomycin Resistance (VanA).




Impact: Democratizes access to treatments for rheumatoid arthritis and creates an open-source shield against antibiotic-resistant bacteria.



📂 PART 3: VIROLOGY & PANDEMIC SHIELD (Dataset_03_...csv)





Target Scope: Global Viral Threats & Chronic Infections.




Key Targets: Hepatitis C (NS5B Polymerase), Hepatitis B, HIV-1 gp120, SARS-CoV-2 (Conserved Spike Epitopes), Universal Influenza Stem, Nipah Virus, and Ebola.




Impact: Prevents the patenting of essential antivirals for future pandemics and current chronic viral burdens.



4. Statement of Intent This database is released to break the cycle of artificial scarcity in medicine. By mapping the "backdoors" (allosteric sites) of the world's most profitable proteins, we ensure that the cures of the future belong to humanity, not to a patent portfolio.

Creator: Kaan Bozanlı (Independent Researcher, Institute of Structural Dynamics) License: CC0 1.0 Universal (Public Domain) Date: January 20, 2026
DOI: 10.15468/dl.jzcupt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((101.189 1.878181, 101.1187 1.872613, 101.050132 1.856045, 100.984985 1.828886, 100.924865 1.791806, 100.871253 1.745717, 100.825468 1.691755, 100.788637 1.631249, 100.761668 1.565691, 100.745222 1.496693, 100.739704 1.425956, 100.745249 1.355221, 100.761719 1.286229, 100.788708 1.22068, 100.825551 1.160187, 100.87134 1.106238, 100.924949 1.060163, 100.985056 1.023094, 101.050183 0.995945, 101.118727 0.979383, 101.189 0.973817, 101.259273 0.979383, 101.327817 0.995945, 101.392944 1.023094, 101.453051 1.060163, 101.50666 1.106238, 101.552449 1.160187, 101.589292 1.22068, 101.616281 1.286229, 101.632751 1.355221, 101.638296 1.425956, 101.632778 1.496693, 101.616332 1.565691, 101.589363 1.631249, 101.552532 1.691755, 101.506747 1.745717, 101.453135 1.791806, 101.393015 1.828886, 101.327868 1.856045, 101.2593 1.872613, 101.189 1.878181))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002970-260120142942310/datasets/export for details.
DOI: 10.15468/dl.cgdus5
title: Occurrence Download

description: A dataset containing 520 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-73.36499999999999 4.390161, -73.435468 4.384591, -73.504198 4.368018, -73.56949400000001 4.340852, -73.62974800000001 4.303763, -73.683474 4.257664, -73.729349 4.203692, -73.766243 4.143179, -73.793251 4.077614, -73.809708 4.008614, -73.815213 3.937878, -73.80963300000001 3.867148, -73.793108 3.798165, -73.766047 3.732626, -73.729117 3.672146, -73.68323100000001 3.618212, -73.62951700000001 3.57215, -73.569298 3.535093, -73.50405499999999 3.507954, -73.435393 3.491398, -73.36499999999999 3.485834, -73.294607 3.491398, -73.225945 3.507954, -73.160702 3.535093, -73.100483 3.57215, -73.046769 3.618212, -73.000883 3.672146, -72.963953 3.732626, -72.936892 3.798165, -72.920367 3.867148, -72.914787 3.937878, -72.920292 4.008614, -72.93674900000001 4.077614, -72.963757 4.143179, -73.000651 4.203692, -73.046526 4.257664, -73.100252 4.303763, -73.160506 4.340852, -73.225802 4.368018, -73.294532 4.384591, -73.36499999999999 4.390161))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 520 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002971-260120142942310/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.31115191
title: Data files

description: Data necessary to fit three generalized dissimilarity models with field collected data on 19 biotic and abiotic response variables (n = 2017 plots), and geographic and environmental gradients described by remotely sensed predictor variables. The three models target ecosystem (joint biotic and abiotic), biotic, and abiotic levels of ecological organization, and were designed to predict continuous spatial turnover among combinations of both biotic and or abiotic properties. Model outputs can be mapped to reveal how spatially structured relationships among biotic and abiotic ecosystem properties collectively give rise to patterns of ecosystem geography. Overall, this approach enables prediction of the shared and independent components and determinants of ecosystem heterogeneity at regional extents.
DOI: 10.6084/m9.figshare.31115191.v1
title: Data files

description: Data necessary to fit three generalized dissimilarity models with field collected data on 19 biotic and abiotic response variables (n = 2017 plots), and geographic and environmental gradients described by remotely sensed predictor variables. The three models target ecosystem (joint biotic and abiotic), biotic, and abiotic levels of ecological organization, and were designed to predict continuous spatial turnover among combinations of both biotic and or abiotic properties. Model outputs can be mapped to reveal how spatially structured relationships among biotic and abiotic ecosystem properties collectively give rise to patterns of ecosystem geography. Overall, this approach enables prediction of the shared and independent components and determinants of ecosystem heterogeneity at regional extents.
DOI: 10.15468/dl.kj9tyc
title: Occurrence Download

description: A dataset listing the 9989 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Antarctica",
 "HasCoordinate is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 9989 records were derived from 573 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002964-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89g539
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.724 1.880181, 99.6537 1.874613, 99.585131 1.858045, 99.51998500000001 1.830886, 99.45986499999999 1.793806, 99.40625199999999 1.747717, 99.360467 1.693755, 99.32363700000001 1.633249, 99.296667 1.567691, 99.28022199999999 1.498693, 99.274704 1.427956, 99.280249 1.357221, 99.296719 1.288229, 99.323708 1.22268, 99.360551 1.162187, 99.40634 1.108238, 99.459948 1.062163, 99.520056 1.025094, 99.585183 0.997945, 99.653727 0.981383, 99.724 0.975817, 99.794273 0.981383, 99.86281700000001 0.997945, 99.927944 1.025094, 99.988052 1.062163, 100.04166 1.108238, 100.087449 1.162187, 100.124292 1.22268, 100.151281 1.288229, 100.167751 1.357221, 100.173296 1.427956, 100.167778 1.498693, 100.151333 1.567691, 100.124363 1.633249, 100.087533 1.693755, 100.041748 1.747717, 99.988135 1.793806, 99.928015 1.830886, 99.862869 1.858045, 99.79430000000001 1.874613, 99.724 1.880181))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002973-260120142942310/datasets/export for details.