cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11463118
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 505,821 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.8001530
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: In recent years, domain-specific knowledge bases (KBs) have been increasingly popular due to their expertise and in-depth representation in a specific domain. Among these domain-specific KBs, financial KBs have attracted considerable attention from academics and industries due to their broad spectrum of downstream applications, such as stock movement prediction, financial fraud detection, and supply chain management. Until now, no datasets including open-domain and domain-specific KBs provide dynamic, up-to-date, and comprehensive financial knowledge, which leads to a fair comparison and broader research among popular financial task models impossible or at least very difficult. We, therefore, construct a dynamic financial KB, HiDy, to address the current limitations discussed above. HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 492,600 relations, 17 entity types, and more than 51,000 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, <em>Macro</em>, <em>Meso</em>,<em> Micro</em>, and<em> Others</em>. Moreover, the robustness of HiDy is a result of the state-of-the-art knowledge extraction and fusion techniques as well as the manual cleaning. For temporality, HiDy's dynamic knowledge is extracted from various resources under different time-granularity to ensure each branch's knowledge is the most up-to-date.
DOI: 10.5281/zenodo.8219047
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 501,925 relations, 17 entity types, and more than 51,015 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, <em>Macro</em>, <em>Meso</em>,<em> Micro</em>, and<em> Others</em>. We then give explanations on the various csv files as follows. "hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company". "hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10". For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.10486548
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 504,156 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.10806851
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 504,736 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.12630355
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 506,024 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.13292095
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 506,444 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.8001486
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 506,444 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others.

We then give explanations on the various csv files as follows.



"hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company".

"hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10".


For details of HiDy, please refer to our GitHub.
DOI: 10.5281/zenodo.8001496
title: HiDy: A Large-scale Hierarchical Dynamic Financial Knowledge Base

description: In recent years, domain-specific knowledge bases (KBs) have been increasingly popular due to their expertise and in-depth representation in a specific domain. Among these domain-specific KBs, financial KBs have attracted considerable attention from academics and industries due to their broad spectrum of downstream applications, such as stock movement prediction, financial fraud detection, and supply chain management. Until now, no datasets including open-domain and domain-specific KBs provide dynamic, up-to-date, and comprehensive financial knowledge, which leads to a fair comparison and broader research among popular financial task models impossible or at least very difficult. We, therefore, construct a dynamic financial KB, HiDy, to address the current limitations discussed above. HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 495,000 relations, 17 entity types, and more than 51,000 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, <em>Macro</em>, <em>Meso</em>,<em> Micro</em>, and<em> Others</em>. Moreover, the robustness of HiDy is a result of the state-of-the-art knowledge extraction and fusion techniques as well as the manual cleaning. For temporality, HiDy's dynamic knowledge is extracted from various resources under different time-granularity to ensure each branch's knowledge is the most up-to-date.
DOI: 10.15468/dl.v5tkfy
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.029767 -33.983962, 149.029767 -33.992946, 149.032012 -33.992946, 149.032012 -33.986208, 149.034258 -33.986208, 149.034258 -33.983962, 149.029767 -33.983962))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059645-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7mk2t8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.047733 -33.983962, 149.047733 -33.986208, 149.049979 -33.986208, 149.049979 -33.983962, 149.047733 -33.983962))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059646-240626123714530/datasets/export for details.
DOI: 10.15468/dl.bu2jag
title: Occurrence Download

description: A dataset containing 4724 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Records of macrozoobenthos organisms in the Ukrainian part of the Danube delta during 2007-2021"
 ]
}

 The dataset includes 4724 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059647-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yeeutd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.573869 -33.986208, 148.573869 -33.9907, 148.576115 -33.9907, 148.576115 -33.986208, 148.573869 -33.986208))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059648-240626123714530/datasets/export for details.
DOI: 10.15468/dl.unqdj2
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron anhweiense E.H.Wilson"
 ]
}

 The dataset includes 33 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059649-240626123714530/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.26531527
title: TNT file with character matrix from A New Sauropod Dinosaur Hindlimb from the Lower Cretaceous Wessex Formation, Isle of Wight, United Kingdom

description: TNT file with character matrix for 128 taxa and 556 characters, including NHMUK PV R 16500
DOI: 10.6084/m9.figshare.26531527.v1
title: TNT file with character matrix from A New Sauropod Dinosaur Hindlimb from the Lower Cretaceous Wessex Formation, Isle of Wight, United Kingdom

description: TNT file with character matrix for 128 taxa and 556 characters, including NHMUK PV R 16500
DOI: 10.6084/m9.figshare.26531530
title: NEXUS file with character matrix from A New Sauropod Dinosaur Hindlimb from the Lower Cretaceous Wessex Formation, Isle of Wight, United Kingdom

description: NEXUS file with character matrix for 128 taxa and 556 characters, including NHMUK PV R 16500
DOI: 10.6084/m9.figshare.26531530.v1
title: NEXUS file with character matrix from A New Sauropod Dinosaur Hindlimb from the Lower Cretaceous Wessex Formation, Isle of Wight, United Kingdom

description: NEXUS file with character matrix for 128 taxa and 556 characters, including NHMUK PV R 16500
DOI: 10.15468/dl.tv2ujr
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.919723 -33.986208, 148.919723 -33.9907, 148.92646 -33.9907, 148.92646 -33.986208, 148.919723 -33.986208))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059650-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.98ee5b
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.063454 -33.986208, 149.063454 -33.9907, 149.065699 -33.9907, 149.065699 -33.986208, 149.063454 -33.986208))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059653-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hrqb55
title: Occurrence Download

description: A dataset containing 1318 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "TaxonKey is Phalacrocorax penicillatus (Brandt, 1837)"
 ]
}

 The dataset includes 1318 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059654-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8jn3tz
title: Occurrence Download

description: A dataset containing 16023 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Equus quagga Boddaert, 1785"
 ]
}

 The dataset includes 16023 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059652-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3yq8rw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.416044 -33.986208, 149.416044 -33.9907, 149.420536 -33.9907, 149.420536 -33.986208, 149.416044 -33.986208))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059655-240626123714530/datasets/export for details.
DOI: 10.15468/dl.fspek5
title: Occurrence Download

description: A dataset containing 30275 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "OccurrenceStatus is Present",
 "TaxonKey is Phalacrocorax pelagicus Pallas, 1811",
 "Year 2004-2015"
 ]
}

 The dataset includes 30275 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059656-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9cxm3x
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron aperantum Balf.fil. & Kingdon-Ward"
 ]
}

 The dataset includes 38 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059658-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9s76gf
title: Occurrence Download

description: A dataset containing 719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, November, December)",
 "TaxonKey is Phalacrocorax penicillatus (Brandt, 1837)"
 ]
}

 The dataset includes 719 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059657-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r32qaf
title: Occurrence Download

description: A dataset containing 217333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tringa stagnatilis (Bechstein, 1803)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 217333 records from 191 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059651-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vbbxj9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((147.974241 -33.9907, 147.974241 -33.992946, 147.976487 -33.992946, 147.976487 -33.9907, 147.974241 -33.9907))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059659-240626123714530/datasets/export for details.
DOI: 10.15468/dl.sz27rh
title: Occurrence Download

description: A dataset containing 1442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "TaxonKey is Phalacrocorax nigrogularis Ogilvie-Grant & H.O.Forbes, 1899"
 ]
}

 The dataset includes 1442 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059660-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ywtv7x
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.439122 -33.9907, 148.439122 -33.992946, 148.443613 -33.992946, 148.443613 -33.9907, 148.439122 -33.9907))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059661-240626123714530/datasets/export for details.
DOI: 10.15468/dl.rvpnn8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.865823 -33.9907, 148.865823 -33.992946, 148.872561 -33.992946, 148.872561 -33.9907, 148.865823 -33.9907))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059663-240626123714530/datasets/export for details.