Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Information Science
Title: Ontology-based exchange of product data semantics
Abstract: An increasing trend toward product development in a collaborative environment has resulted in the use of various software tools to enhance the product design. This requires a meaningful representation and exchange of product data semantics across different application domains. This paper proposes an ontology-based framework to enable such semantic interoperability. A standards-based approach is used to develop a Product Semantic Representation Language (PSRL). Formal description logic (DAML+OIL) is used to encode the PSRL. Mathematical logic and corresponding reasoning is used to determine semantic equivalences between an application ontology and the PSRL. The semantic equivalence matrix enables resolution of ambiguities created due to differences in syntaxes and meanings associated with terminologies in different application domains. Successful semantic interoperability will form the basis of seamless communication and thereby enable better integration of product development systems. Note to Practitioners-Semantic interoperability of product information refers to automating the exchange of meaning associated with the data, among information resources throughout the product development. This research is motivated by the problems in enabling such semantic interoperability. First, product information is formalized into an explicit, extensible, and comprehensive product semantics representation language (PSRL). The PSRL is open and based on standard W3C constructs. Next, in order to enable semantic translation, the paper describes a procedure to semi-automatically determine mappings between exactly equivalent concepts across representations of the interacting applications. The paper demonstrates that this approach to translation is feasible, but it has not yet been implemented commercially. Current limitations and the directions for further research are discussed. Future research addresses the determination of semantic similarities (not exact equivalences) between the interacting information resources.
Extracted statement — hasRepresentationMasterData: Description Logic
Research field: Information Science
Title: The Pattern of Patterns: What is a pattern in conceptual modeling?
Abstract: It has been proven that using structured methods to represent the domain reduces human errors in the process of creating models and also in the process of using them. Using modeling patterns is a proven structural method in this regard. A pattern is a generalizable reusable solution to a design problem. Positive effects of using patterns were demonstrated in several experimental studies and explained using theories. However, detailed knowledge about how properties of patterns lead to increased performance in writing and reading conceptual models is currently lacking. This paper proposes a theoretical framework to characterize the properties of ontology-driven conceptual model patterns. The development of such framework is the first step in investigating the effects of pattern properties and devising rules to compose patterns based on well-understood properties.
Extracted statement — Process: design problem
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: distributed data
Research field: Information Science
Title: Rule-based named entity recognition for drug-related crime news documents
Abstract: Drug abuse pertains to the consumption of a substance that may induce adverse effects to a person. In international security studies, drug trafficking has become an important topic. In this regard, drug-related crimes are identified as an extremely significant challenge faced by any community. Several techniques for investigations in the crime domain have been implemented by many researchers. However, most of these researchers focus on extracting general crime entities. The number of studies that focus on the drug crime domain is relatively limited. This paper mainly aims to propose a rule-based named entity recognition model for drug-related crime news documents. In this work, a set of heuristic and grammatical rules is used to extract named entities, such as types of drugs, amount of drugs, price of drugs, drug hiding methods, and the nationality of the suspect. A set of grammatical and heuristic rules is established based on part-ofspeech information, developed gazetteers, and indicator word lists. The combined approach of heuristic and grammatical rules achieves a good performance with an overall precision of 86%, a recall of 87%, and an F1-measure of 87%. Results indicate that the ensemble of both heuristic and grammatical rules improves the extraction effectiveness in terms of macro-F1 for all entities.
Extracted statement — Language/domain: Drug-related crime news documents
Research field: Information Science
Title: Improvements in Timeliness Resulting from Implementation of Electronic Laboratory Reporting and an Electronic Disease Surveillance System
Abstract: Objectives. Electronic laboratory reporting (ELR) reduces the time between communicable disease diagnosis and case reporting to local health departments (LHDs). However, it also imposes burdens on public health agencies, such as increases in the number of unique and duplicate case reports. We assessed how ELR affects the timeliness and accuracy of case report processing within public health agencies. Methods. Using data from May–August 2010 and January–March 2012, we assessed timeliness by calculating the time between receiving a case at the LHD and reporting the case to the state (first stage of reporting) and between submitting the report to the state and submitting it to the Centers for Disease Control and Prevention (second stage of reporting). We assessed accuracy by calculating the proportion of cases returned to the LHD for changes or additional information. We compared timeliness and accuracy for ELR and non-ELR cases. Results. ELR was associated with decreases in case processing time (median = 40 days for ELR cases vs. 52 days for non-ELR cases in 2010; median = 20 days for ELR cases vs. 25 days for non-ELR cases in 2012; both p<0.001). ELR also allowed time to reduce the backlog of unreported cases. Finally, ELR was associated with higher case reporting accuracy (in 2010, 2% of ELR case reports vs. 8% of non-ELR case reports were returned; in 2012, 2% of ELR case reports vs. 6% of non-ELR case reports were returned; both p<0.001). Conclusion. The overall impact of increased ELR is more efficient case processing at both local and state levels.
Extracted statement — Epidemiological surveillance software: Electronic Laboratory Reporting
Research field: Information Science
Title: Estimating relative depth in single images via rankboost
Abstract: In this paper, we present a novel approach to estimate the relative depth of regions in monocular images. There are several contributions. First, the task of monocular depth estimation is considered as a learning-to-rank problem which offers several advantages compared to regression approaches. Second, monocular depth clues of human perception are modeled in a systematic manner. Third, we show that these depth clues can be modeled and integrated appropriately in a Rankboost framework. For this purpose, a space-efficient version of Rankboost is derived that makes it applicable to rank a large number of objects, as posed by the given problem. Finally, the monocular depth clues are combined with results from a deep learning approach. Experimental results show that the error rate is reduced by adding the monocular features while outperforming state-of-the-art systems.
Extracted statement — Has metric: Error rate
Research field: Information Science
Title: Developing open source, self-contained disease surveillance software applications for use in resource-limited settings
Abstract: Abstract Background Emerging public health threats often originate in resource-limited countries. In recognition of this fact, the World Health Organization issued revised International Health Regulations in 2005, which call for significantly increased reporting and response capabilities for all signatory nations. Electronic biosurveillance systems can improve the timeliness of public health data collection, aid in the early detection of and response to disease outbreaks, and enhance situational awareness. Methods As components of its Suite for Automated Global bioSurveillance (SAGES) program, The Johns Hopkins University Applied Physics Laboratory developed two open-source, electronic biosurveillance systems for use in resource-limited settings. OpenESSENCE provides web-based data entry, analysis, and reporting. ESSENCE Desktop Edition provides similar capabilities for settings without internet access. Both systems may be configured to collect data using locally available cell phone technologies. Results ESSENCE Desktop Edition has been deployed for two years in the Republic of the Philippines. Local health clinics have rapidly adopted the new technology to provide daily reporting, thus eliminating the two-to-three week data lag of the previous paper-based system. Conclusions OpenESSENCE and ESSENCE Desktop Edition are two open-source software products with the capability of significantly improving disease surveillance in a wide range of resource-limited settings. These products, and other emerging surveillance technologies, can assist resource-limited countries compliance with the revised International Health Regulations.
Extracted statement — Epidemiological surveillance software: ESSENCE Desktop
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
Research field: Information Science
Title: Open Science meets Food Modelling: Introducing the Food Modelling Journal (FMJ)
Abstract: <jats:p>This Editorial describes the rationale, focus, scope and technology behind the newly launched, open access, innovative Food Modelling Journal (FMJ). The Journal is designed to publish those outputs of the research cycle that usually precede the publication of the research article, but have their own value and re-usability potential. Such outputs are methods, models, software and data. The Food Modelling Journal is launched by the AGINFRA+ community and is integrated with the AGINFRA+ Virtual Research Environment (VRE) to facilitate and streamline the authoring, peer review and publication of the manuscripts via the ARPHA Publishing Platform.</jats:p>
Extracted statement — Method: Food modelling
Research field: Information Science
Title: Open Science meets Food Modelling: Introducing the Food Modelling Journal (FMJ)
Abstract: <jats:p>This Editorial describes the rationale, focus, scope and technology behind the newly launched, open access, innovative Food Modelling Journal (FMJ). The Journal is designed to publish those outputs of the research cycle that usually precede the publication of the research article, but have their own value and re-usability potential. Such outputs are methods, models, software and data. The Food Modelling Journal is launched by the AGINFRA+ community and is integrated with the AGINFRA+ Virtual Research Environment (VRE) to facilitate and streamline the authoring, peer review and publication of the manuscripts via the ARPHA Publishing Platform.</jats:p>
Extracted statement — Has implementation: Food Modelling Journal
Research field: Information Science
Title: Open Science meets Food Modelling: Introducing the Food Modelling Journal (FMJ)
Abstract: <jats:p>This Editorial describes the rationale, focus, scope and technology behind the newly launched, open access, innovative Food Modelling Journal (FMJ). The Journal is designed to publish those outputs of the research cycle that usually precede the publication of the research article, but have their own value and re-usability potential. Such outputs are methods, models, software and data. The Food Modelling Journal is launched by the AGINFRA+ community and is integrated with the AGINFRA+ Virtual Research Environment (VRE) to facilitate and streamline the authoring, peer review and publication of the manuscripts via the ARPHA Publishing Platform.</jats:p>
Extracted statement — used in: Food Modelling Journal
Research field: Information Science
Title: Curating Scientific Information in Knowledge Infrastructures
Abstract: Interpreting observational data is a fundamental task in the sciences, specifically in earth and environmental science where observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by research communities, their research groups and individual scientists, who interpret such primary data for their meaning in the context of research investigations. The result of interpretation is information – meaningful secondary or derived data – about the observed environment. Research infrastructures and research communities are thus essential to evolving uninterpreted observational data to information. In digital form, the classical bearer of information are the commonly known “(elaborated) data products,” for instance maps. In such form, meaning is generally implicit e.g., in map colour coding, and thus largely inaccessible to machines. The systematic acquisition, curation, possible publishing and further processing of information gained in observational data interpretation – as machine readable data and their machine-readable meaning – is not common practice among environmental research infrastructures. For a use case in aerosol science, we elucidate these problems and present a Jupyter based prototype infrastructure that exploits a machine learning approach to interpretation and could support a research community in interpreting observational data and, more importantly, in curating and further using resulting information about a studied natural phenomenon.
Extracted statement — Process: further processing
Research field: Information Science
Title: The Pattern of Patterns: What is a pattern in conceptual modeling?
Abstract: It has been proven that using structured methods to represent the domain reduces human errors in the process of creating models and also in the process of using them. Using modeling patterns is a proven structural method in this regard. A pattern is a generalizable reusable solution to a design problem. Positive effects of using patterns were demonstrated in several experimental studies and explained using theories. However, detailed knowledge about how properties of patterns lead to increased performance in writing and reading conceptual models is currently lacking. This paper proposes a theoretical framework to characterize the properties of ontology-driven conceptual model patterns. The development of such framework is the first step in investigating the effects of pattern properties and devising rules to compose patterns based on well-understood properties.
Extracted statement — Material: generalizable reusable solution
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 — Data: genomic and other omics datasets
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: genomic and other omics datasets