Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Geology
Title: Textural and Heavy Minerals Characterization of Coastal Sediments in Ibeno and Eastern Obolo Local Government Areas of Akwa Ibom State – Nigeria
Abstract: Textural characterization and heavy mineral studies of beach sediments in Ibeno and Eastern Obolo Local Government Areas of Akwa Ibom State were carried out in the present study. The main aim was to infer their provenance, transport history and environment of deposition. Sediment samples were collected at the water–sediment contact along the shoreline at an interval of about 3m. Ten samples were collected from study location 1 (Ibeno Beach) and twelve samples were collected from study location 2 (Eastern Obolo Beach). A total of twenty–two samples were collected from the field and brought to the laboratory for textural and compositional analyses. The results showed that the value of graphic mean size ranged from 1.70Ф to 2.83Ф, sorting values ranged from 0.39Ф – 0.60Ф, skewness values ranged from -0.02 to 0.10 while kurtosis values ranged from 1.02 to 2.46, indicating medium to fine grained and well sorted sediments. This suggested that the sediments have been transported far from their source. Longshore current and onshore–offshore movements of sediment are primarily responsible in sorting of the heavy minerals. The histogram charts for the different samples and standard deviation versus skewness indicated a beach environment of deposition. This implies that the sediments are dominated by one class of grain size; a phenomenon characteristic of beach environments. The heavy mineral assemblages identified in this research work were rutile, zircon, tourmaline, hornblende, apatite, diopside, glauconite, pumpellyite, cassiterite, epidote, garnet, augite, enstatite, andalusite and opaque minerals. The zircon-tourmaline-rutile (ZTR) index ranged from 47.30% to 87.00% with most of the samples showing a ZTR index greater than 50%. These indicated that the sediments were mineralogically sub-mature and have been transported far from their source. The heavy minerals identified are indicative of being products of reworked sediments of both metamorphic (high rank) and igneous (both mafic and sialic) origin probably derived from the basement rocks of the Oban Massif as well as reworked sediments of the Benue Trough. Therefore, findings from the present study indicated that erosion, accretion, and stability of beaches are controlled by strong hydrodynamic and hydraulic processes.
Extracted statement — Aim of the study: The main aim was to infer their provenance, transport history and environment of deposition.
Research field: Human and Clinical Nutrition
Title: Comparative Assessment of Iodine Content of Commercial Table Salt Brands Available in Nigerian Market
Abstract: Iodine deficiency disorders (IDD) has been a major global public health problem threatening more than 2 billion people worldwide. Considering various human health implications associated with iodine deficiency, universal salt iodization programme has been recognized as one of the best methods of preventing iodine deficiency disorder and iodizing table salt is currently done in many countries. In this study, comparative assessment of iodine content of commercially available table salt brands in Nigerian market were investigated and iodine content were measured in ten table salt brands samples using iodometric titration. The iodine content ranged from 14.80 mg/kg – 16.90 mg/kg with mean value of 15.90 mg/kg for Sea salt; 24.30 mg/kg – 25.40 mg/kg with mean value of 24.60 mg/kg for Dangote salt (blue sachet); 22.10 mg/kg – 23.10 mg/kg with mean value of 22.40 mg/kg for Dangote salt (red sachet); 23.30 mg/kg – 24.30 mg/kg with mean value of 23.60 mg/kg for Mr Chef salt; 23.30 mg/kg – 24.30 mg/kg with mean value of 23.60 mg/kg for Annapurna; 26.80 mg/kg – 27.50 mg/kg with mean value of 27.20mg/kg for Uncle Palm salt; 23.30 mg/kg – 29.60 mg/kg with mean content of 26.40 mg/kg for Dangote (bag); 25.40 mg/kg – 26.50 mg/kg with mean value of 26.50 mg/kg for Royal salt; 36.80 mg/kg – 37.20 mg/kg with mean iodine content of 37.0 mg/kg for Abakaliki refined salt, and 30.07 mg/kg – 31.20 mg/kg with mean value of 31.00 mg/kg for Ikom refined salt. The mean iodine content measured in the Sea salt brand (15.70 mg/kg) was significantly P < 0.01 lower compared to those measured in other table salt brands. Although the iodine content of Abakaliki and Ikom refined salt exceed the recommended value, it is clear that only Sea salt brand falls below the World Health Organization (WHO) recommended value (20 – 30 mg/kg), while the remaining table salt samples are just within the range. The results obtained have revealed that 70 % of the table salt brands were adequately iodized while 30 % of the table salt brands were not adequately iodized and provided baseline data that can be used for potential identification of human health risks associated with inadequate and/or excess iodine content in table salt brands consumed in households in Nigeria.
Extracted statement — Has method: Considering various human health implications associated with iodine deficiency, universal salt iodization programme has been recognized as one of the best methods of preventing iodine deficiency disorder and iodizing table salt is currently done in many countries.
Research field: Human and Clinical Nutrition
Title: Comparative Assessment of Iodine Content of Commercial Table Salt Brands Available in Nigerian Market
Abstract: Iodine deficiency disorders (IDD) has been a major global public health problem threatening more than 2 billion people worldwide. Considering various human health implications associated with iodine deficiency, universal salt iodization programme has been recognized as one of the best methods of preventing iodine deficiency disorder and iodizing table salt is currently done in many countries. In this study, comparative assessment of iodine content of commercially available table salt brands in Nigerian market were investigated and iodine content were measured in ten table salt brands samples using iodometric titration. The iodine content ranged from 14.80 mg/kg – 16.90 mg/kg with mean value of 15.90 mg/kg for Sea salt; 24.30 mg/kg – 25.40 mg/kg with mean value of 24.60 mg/kg for Dangote salt (blue sachet); 22.10 mg/kg – 23.10 mg/kg with mean value of 22.40 mg/kg for Dangote salt (red sachet); 23.30 mg/kg – 24.30 mg/kg with mean value of 23.60 mg/kg for Mr Chef salt; 23.30 mg/kg – 24.30 mg/kg with mean value of 23.60 mg/kg for Annapurna; 26.80 mg/kg – 27.50 mg/kg with mean value of 27.20mg/kg for Uncle Palm salt; 23.30 mg/kg – 29.60 mg/kg with mean content of 26.40 mg/kg for Dangote (bag); 25.40 mg/kg – 26.50 mg/kg with mean value of 26.50 mg/kg for Royal salt; 36.80 mg/kg – 37.20 mg/kg with mean iodine content of 37.0 mg/kg for Abakaliki refined salt, and 30.07 mg/kg – 31.20 mg/kg with mean value of 31.00 mg/kg for Ikom refined salt. The mean iodine content measured in the Sea salt brand (15.70 mg/kg) was significantly P < 0.01 lower compared to those measured in other table salt brands. Although the iodine content of Abakaliki and Ikom refined salt exceed the recommended value, it is clear that only Sea salt brand falls below the World Health Organization (WHO) recommended value (20 – 30 mg/kg), while the remaining table salt samples are just within the range. The results obtained have revealed that 70 % of the table salt brands were adequately iodized while 30 % of the table salt brands were not adequately iodized and provided baseline data that can be used for potential identification of human health risks associated with inadequate and/or excess iodine content in table salt brands consumed in households in Nigeria.
Extracted statement — Has method: In this study, comparative assessment of iodine content of commercially available table salt brands in Nigerian market were investigated and iodine content were measured in ten table salt brands samples using iodometric titration.
Research field: Information Science
Title: The New DBpedia Release Cycle: Increasing Agility and Efficiency in Knowledge Extraction Workflows
Abstract: Abstract Since its inception in 2007, DBpedia has been constantly releasing open data in RDF, extracted from various Wikimedia projects using a complex software system called the DBpedia Information Extraction Framework (DIEF). For the past 12 years, the software received a plethora of extensions by the community, which positively affected the size and data quality. Due to the increase in size and complexity, the release process was facing huge delays (from 12 to 17 months cycle), thus impacting the agility of the development. In this paper, we describe the new DBpedia release cycle including our innovative release workflow, which allows development teams (in particular those who publish large, open data) to implement agile, cost-efficient processes and scale up productivity. The DBpedia release workflow has been re-engineered, its new primary focus is on productivity and agility , to address the challenges of size and complexity. At the same time, quality is assured by implementing a comprehensive testing methodology. We run an experimental evaluation and argue that the implemented measures increase agility and allow for cost-effective quality-control and debugging and thus achieve a higher level of maintainability. As a result, DBpedia now publishes regular (i.e. monthly) releases with over 21 billion triples with minimal publishing effort .
Extracted statement — Process: agile, cost-efficient processes and scale up productivity
Research field: Information Science
Title: Expanding horizons in historical linguistics with the 400-million word Corpus of Historical American English
Abstract: The Corpus of Historical American English (COHA) contains 400 million words in more than 100,000 texts which date from the 1810s to the 2000s. The corpus contains texts from fiction, popular magazines, newspapers and non-fiction books, and is balanced by genre from decade to decade. It has been carefully lemmatised and tagged for part-of-speech, and uses the same architecture as the Corpus of Contemporary American English (COCA), BYU-BNC, the TIME Corpus and other corpora. COHA allows for a wide range of research on changes in lexis, morphology, syntax, semantics, and American culture and society (as viewed through language change), in ways that are probably not possible with any text archive (e.g., Google Books) or any other corpus of historical American English.
Extracted statement — description: allows for a wide range of research on changes in lexis, morphology, syntax, semantics, and American culture and society (as viewed through language change), in ways that are probably not possible with any text archive (e.g., Google Books) or any other corpus of historical American English
Research field: Information Science
Title: OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science
Abstract: Hundreds of years of biodiversity research have resulted in the accumulation of a substantial pool of communal knowledge; however, most of it is stored in silos isolated from each other, such as published articles or monographs. The need for a system to store and manage collective biodiversity knowledge in a community-agreed and interoperable open format has evolved into the concept of the Open Biodiversity Knowledge Management System (OBKMS). This paper presents OpenBiodiv: An OBKMS that utilizes semantic publishing workflows, text and data mining, common standards, ontology modelling and graph database technologies to establish a robust infrastructure for managing biodiversity knowledge. It is presented as a Linked Open Dataset generated from scientific literature. OpenBiodiv encompasses data extracted from more than 5000 scholarly articles published by Pensoft and many more taxonomic treatments extracted by Plazi from journals of other publishers. The data from both sources are converted to Resource Description Framework (RDF) and integrated in a graph database using the OpenBiodiv-O ontology and an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone. Through the application of semantic technologies, the project showcases the value of open publishing of Findable, Accessible, Interoperable, Reusable (FAIR) data towards the establishment of open science practices in the biodiversity domain.
Extracted statement — Material: an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone
Research field: Information Science
Title: More Complete Resultset Retrieval from Large Heterogeneous RDF Sources
Abstract: Over the last years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laudromat, SPARQL endpoints provide access to the hundered of thousands of RDF datasets, representing billions of facts. These datasets are available in different formats such as raw data dumps and HDT files or directly accessible via SPARQL endpoints. Querying such large amount of distributed data is particularly challenging and many of these datasets cannot be directly queried using the SPARQL query language. In order to tackle these problems, we present WimuQ, an integrated query engine to execute SPARQL queries and retrieve results from large amount of heterogeneous RDF data sources. Presently, WimuQ is able to execute both federated and non-federated SPARQL queries over a total of 668,166 datasets from LOD Stats and LOD Laudromat as well as 559 active SPARQL endpoints. These data sources represent a total of 221.7 billion triples from more than 5 terabytes of information from datasets retrieved using the service "Where is My URI" (WIMU). Our evaluation on state-of-the-art real-data benchmarks shows that WimuQ retrieves more complete results for the benchmark queries.
Extracted statement — Material: both federated and non-federated SPARQL queries
Research field: Information Science
Title: A streamlined workflow for conversion, peer review, and publication of genomics metadata as omics data papers 
Abstract: Abstract Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility.
Extracted statement — Material: European Nucleotide Archive, ArrayExpress, and BioSamples databases
Research field: Information Science
Title: OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science
Abstract: Hundreds of years of biodiversity research have resulted in the accumulation of a substantial pool of communal knowledge; however, most of it is stored in silos isolated from each other, such as published articles or monographs. The need for a system to store and manage collective biodiversity knowledge in a community-agreed and interoperable open format has evolved into the concept of the Open Biodiversity Knowledge Management System (OBKMS). This paper presents OpenBiodiv: An OBKMS that utilizes semantic publishing workflows, text and data mining, common standards, ontology modelling and graph database technologies to establish a robust infrastructure for managing biodiversity knowledge. It is presented as a Linked Open Dataset generated from scientific literature. OpenBiodiv encompasses data extracted from more than 5000 scholarly articles published by Pensoft and many more taxonomic treatments extracted by Plazi from journals of other publishers. The data from both sources are converted to Resource Description Framework (RDF) and integrated in a graph database using the OpenBiodiv-O ontology and an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone. Through the application of semantic technologies, the project showcases the value of open publishing of Findable, Accessible, Interoperable, Reusable (FAIR) data towards the establishment of open science practices in the biodiversity domain.
Extracted statement — Material: Findable, Accessible, Interoperable, Reusable (FAIR) data
Research field: Information Science
Title: Scalable SPARQL querying of large RDF graphs
Abstract: The generation of RDF data has accelerated to the point where many data sets need to be partitioned across multiple machines in order to achieve reasonable performance when querying the data. Although tremendous progress has been made in the Semantic Web community for achieving high performance data management on a single node, current solutions that allow the data to be partitioned across multiple machines are highly inefficient. In this paper, we introduce a scalable RDF data management system that is up to three orders of magnitude more efficient than popular multi-node RDF data management systems. In so doing, we introduce techniques for (1) leveraging state-of-the-art single node RDF-store technology (2) partitioning the data across nodes in a manner that helps accelerate query processing through locality optimizations and (3) decomposing SPARQL queries into high performance fragments that take advantage of how data is partitioned in a cluster.
Extracted statement — Material: popular multi-node RDF data management systems
Research field: Information Science
Title: More Complete Resultset Retrieval from Large Heterogeneous RDF Sources
Abstract: Over the last years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laudromat, SPARQL endpoints provide access to the hundered of thousands of RDF datasets, representing billions of facts. These datasets are available in different formats such as raw data dumps and HDT files or directly accessible via SPARQL endpoints. Querying such large amount of distributed data is particularly challenging and many of these datasets cannot be directly queried using the SPARQL query language. In order to tackle these problems, we present WimuQ, an integrated query engine to execute SPARQL queries and retrieve results from large amount of heterogeneous RDF data sources. Presently, WimuQ is able to execute both federated and non-federated SPARQL queries over a total of 668,166 datasets from LOD Stats and LOD Laudromat as well as 559 active SPARQL endpoints. These data sources represent a total of 221.7 billion triples from more than 5 terabytes of information from datasets retrieved using the service "Where is My URI" (WIMU). Our evaluation on state-of-the-art real-data benchmarks shows that WimuQ retrieves more complete results for the benchmark queries.
Extracted statement — Material: raw data dumps and HDT files
Research field: Information Science
Title: A streamlined workflow for conversion, peer review, and publication of genomics metadata as omics data papers 
Abstract: Abstract Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility.
Extracted statement — Process: streamlined import
Research field: Information Science
Title: OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science
Abstract: Hundreds of years of biodiversity research have resulted in the accumulation of a substantial pool of communal knowledge; however, most of it is stored in silos isolated from each other, such as published articles or monographs. The need for a system to store and manage collective biodiversity knowledge in a community-agreed and interoperable open format has evolved into the concept of the Open Biodiversity Knowledge Management System (OBKMS). This paper presents OpenBiodiv: An OBKMS that utilizes semantic publishing workflows, text and data mining, common standards, ontology modelling and graph database technologies to establish a robust infrastructure for managing biodiversity knowledge. It is presented as a Linked Open Dataset generated from scientific literature. OpenBiodiv encompasses data extracted from more than 5000 scholarly articles published by Pensoft and many more taxonomic treatments extracted by Plazi from journals of other publishers. The data from both sources are converted to Resource Description Framework (RDF) and integrated in a graph database using the OpenBiodiv-O ontology and an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone. Through the application of semantic technologies, the project showcases the value of open publishing of Findable, Accessible, Interoperable, Reusable (FAIR) data towards the establishment of open science practices in the biodiversity domain.
Extracted statement — method: the concept of the Open Biodiversity Knowledge Management System (OBKMS)