Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Environmental Sciences
Title: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM)
Abstract: Abstract. The recently developed Norwegian Earth System Model (NorESM) is employed for simulations contributing to the CMIP5 (Coupled Model Intercomparison Project phase 5) experiments and the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC-AR5). In this manuscript, we focus on evaluating the ocean and land carbon cycle components of the NorESM, based on the preindustrial control and historical simulations. Many of the observed large scale ocean biogeochemical features are reproduced satisfactorily by the NorESM. When compared to the climatological estimates from the World Ocean Atlas (WOA), the model simulated temperature, salinity, oxygen, and phosphate distributions agree reasonably well in both the surface layer and deep water structure. However, the model simulates a relatively strong overturning circulation strength that leads to noticeable model-data bias, especially within the North Atlantic Deep Water (NADW). This strong overturning circulation slightly distorts the structure of the biogeochemical tracers at depth. Advancements in simulating the oceanic mixed layer depth with respect to the previous generation model particularly improve the surface tracer distribution as well as the upper ocean biogeochemical processes, particularly in the Southern Ocean. Consequently, near-surface ocean processes such as biological production and air–sea gas exchange, are in good agreement with climatological observations. The NorESM adopts the same terrestrial model as the Community Earth System Model (CESM1). It reproduces the general pattern of land-vegetation gross primary productivity (GPP) when compared to the observationally based values derived from the FLUXNET network of eddy covariance towers. While the model simulates well the vegetation carbon pool, the soil carbon pool is smaller by a factor of three relative to the observational based estimates. The simulated annual mean terrestrial GPP and total respiration are slightly larger than observed, but the difference between the global GPP and respiration is comparable. Model-data bias in GPP is mainly simulated in the tropics (overestimation) and in high latitudes (underestimation). Within the NorESM framework, both the ocean and terrestrial carbon cycle models simulate a steady increase in carbon uptake from the preindustrial period to the present-day. The land carbon uptake is noticeably smaller than the observations, which is attributed to the strong nitrogen limitation formulated by the land model.
Extracted statement — has research problem: CMIP5
Research field: Epidemiology
Title: The Infectious Disease Ontology in the age of COVID-19
Abstract: Abstract Background Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules. Results To assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Disease Ontology (CIDO); and an extension of CIDO focusing on COVID-19 (IDO-COVID-19). Reflecting the fact that viruses lack cellular parts, we have introduced into IDO Core the term acellular structure to cover viruses and other acellular entities studied by virologists. We now distinguish between infectious agents – organisms with an infectious disposition – and infectious structures – acellular structures with an infectious disposition. This in turn has led to various updates and refinements of IDO Core’s content. We believe that our work on VIDO, CIDO, and IDO-COVID-19 can serve as a model for yielding greater conformance with ontology building best practices. Conclusions IDO provides a simple recipe for building new pathogen-specific ontologies in a way that allows data about novel diseases to be easily compared, along multiple dimensions, with data represented by existing disease ontologies. The IDO strategy, moreover, supports ontology coordination, providing a powerful method of data integration and sharing that allows physicians, researchers, and public health organizations to respond rapidly and efficiently to current and future public health crises.
Extracted statement — Dataset name: IDO-COVID-19
Research field: Genomics
Title: The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia
Abstract: Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1, and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard-of-care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard-of-care diagnostics. KMT2A (MLL) rearrangements, although usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard-of-care testing in 9 patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the most common IKZF1 deletion from RNA-seq data and validated this using an RQ-PCR assay. We applied an expression classifier to identify Philadelphia chromosome-like B-ALL patients. T-ALL proved a rich source of novel gene fusions, which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.
Extracted statement — Has method: RNA-seq
Research field: Geology
Title: Spaceborne visible and thermal infrared lithologic mapping of impact-exposed subsurface lithologies at the Haughton impact structure, Devon Island, Canadian High Arctic: Applications to Mars
Abstract: Abstract— This study serves as a proof‐of‐concept for the technique of using visible‐near infrared (VNIR), short‐wavelength infrared (SWIR), and thermal infrared (TIR) spectroscopic observations to map impact‐exposed subsurface lithologies and stratigraphy on Earth or Mars. The topmost layer, three subsurface layers and undisturbed outcrops of the target sequence exposed just 10 km to the northeast of the 23 km diameter Haughton impact structure (Devon Island, Nunavut, Canada) were mapped as distinct spectral units using Landsat 7 ETM+ (VNIR/SWIR) and ASTER (VNIR/SWIR/TIR) multispectral images. Spectral mapping was accomplished by using standard image contrast‐stretching algorithms. Both spectral matching and deconvolution algorithms were applied to image‐derived ASTER TIR emissivity spectra using spectra from a library of laboratory‐measured spectra of minerals (Arizona State University) and whole‐rocks (Ward's). These identifications were made without the use of a priori knowledge from the field (i.e., a “blind” analysis). The results from this analysis suggest a sequence of dolomitic rock (in the crater rim), limestone (wall), gypsum‐rich carbonate (floor), and limestone again (central uplift). These matched compositions agree with the lithologic units and the pre‐impact stratigraphic sequence as mapped during recent field studies of the Haughton impact structure by Osinski et al. (2005a). Further conformation of the identity of image‐derived spectra was confirmed by matching these spectra with laboratory‐measured spectra of samples collected from Haughton. The results from the “blind” remote sensing methods used here suggest that these techniques can also be used to understand subsurface lithologies on Mars, where ground truth knowledge may not be generally available.
Extracted statement — has dataset:  ASTER
Research field: Geology
Title: Comparison of Airborne Hyperspectral Data and EO-1 Hyperion for Mineral Mapping
Abstract: Airborne hyperspectral data have been available to researchers since the early 1980s and their use for geologic applications is well documented. The launch of the National Aeronautics and Space Administration Earth Observing 1 Hyperion sensor in November 2000 marked the establishment of a test bed for spaceborne hyperspectral capabilities. Hyperion covers the 0.4-2.5-/spl mu/m range with 242 spectral bands at approximately 10-nm spectral resolution and 30-m spatial resolution. Analytical Imaging and Geophysics LLC and the Commonwealth Scientific and Industrial Research Organisation have been involved in efforts to evaluate, validate, and demonstrate Hyperions's utility for geologic mapping in a variety of sites in the United States and around the world. Initial results over several sites with established ground truth and years of airborne hyperspectral data show that Hyperion data from the shortwave infrared spectrometer can be used to produce useful geologic (mineralogic) information. Minerals mapped include carbonates, chlorite, epidote, kaolinite, alunite, buddingtonite, muscovite, hydrothermal silica, and zeolite. Hyperion data collected under optimum conditions (summer season, bright targets, well-exposed geology) indicate that Hyperion data meet prelaunch specifications and allow subtle distinctions such as determining the difference between calcite and dolomite and mapping solid solution differences in micas caused by substitution in octahedral molecular sites. Comparison of airborne hyperspectral data [from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)] to the Hyperion data establishes that Hyperion provides similar basic mineralogic information, with the principal limitation being limited mapping of fine spectral detail under less-than-optimum acquisition conditions (winter season, dark targets) based on lower signal-to-noise ratios. Case histories demonstrate the analysis methodologies and level of information available from the Hyperion data. They also show the viability of Hyperion as a means of extending hyperspectral mineral mapping to areas not accessible to aircraft sensors. The analysis results demonstrate that spaceborne hyperspectral sensors can produce useful mineralogic information, but also indicate that SNR improvements are required for future spaceborne sensors to allow the same level of mapping that is currently possible from airborne sensors such as AVIRIS.
Extracted statement — Data used: AVIRIS
Research field: Geology
Title: Integration of Raman, emission, and reflectance spectroscopy for earth and lunar mineralogy
Abstract: Abstract. Spectroscopy plays a vital role in the identification and characterization of minerals on terrestrial and planetary surfaces. We review the three different spectroscopic techniques for characterizing minerals on the Earth and lunar surfaces separately. Seven sedimentary and metamorphic terrestrial rock samples were analyzed with three field-based spectrometers, i.e., Raman, Fourier transform infrared (FTIR), and visible to near infrared and shortwave infrared (Vis–NIR–SWIR) spectrometers. Similarly, a review of work done by previous researchers on lunar rock samples was also carried out for their Raman, Vis–NIR–SWIR, and thermal (mid-infrared) spectral responses. It has been found in both the cases that the spectral information such as Si-O-Si stretching (polymorphs) in Raman spectra, identification of impurities, Christiansen and Restrahlen band center variation in mid-infrared spectra, location of elemental substitution, the content of iron, and shifting of the band center of diagnostic absorption features at 1 and 2 μm in reflectance spectra are contributing to the characterization and identification of terrestrial and lunar minerals. We show that quartz can be better characterized by considering silica polymorphs from Raman spectra, emission features in the range of 8 to 14 μm in FTIR spectra, and reflectance absorption features from Vis–NIR–SWIR spectra. KREEP materials from Apollo 12 and 14 samples are also better characterized using integrated spectroscopic studies. Integrated spectral responses felicitate comprehensive characterization and better identification of minerals. We suggest that Raman spectroscopy and visible and NIR-thermal spectroscopy are the best techniques to explore the Earth’s and lunar mineralogy.
Extracted statement — Minerals identified (Lunar rock samples): KREEP
Research field: Graphics
Title: An ontology of scientific experiments
Abstract: The formal description of experiments for efficient analysis, annotation and sharing of results is a fundamental part of the practice of science. Ontologies are required to achieve this objective. A few subject-specific ontologies of experiments currently exist. However, despite the unity of scientific experimentation, no general ontology of experiments exists. We propose the ontology EXPO to meet this need. EXPO links the SUMO (the Suggested Upper Merged Ontology) with subject-specific ontologies of experiments by formalizing the generic concepts of experimental design, methodology and results representation. EXPO is expressed in the W3C standard ontology language OWL-DL. We demonstrate the utility of EXPO and its ability to describe different experimental domains, by applying it to two experiments: one in high-energy physics and the other in phylogenetics. The use of EXPO made the goals and structure of these experiments more explicit, revealed ambiguities, and highlighted an unexpected similarity. We conclude that, EXPO is of general value in describing experiments and a step towards the formalization of science.
Extracted statement — Ontology: EXPO
Research field: Graphics
Title: Using Hierarchical Edge Bundles to visualize complex ontologies in GLOW
Abstract: In the past decade, much effort has been put into the visual representation of ontologies. However, present visualization strategies are not equipped to handle complex ontologies with many relations, leading to visual clutter and inefficient use of space. In this paper, we propose GLOW, a method for ontology visualization based on Hierarchical Edge Bundles. Hierarchical Edge Bundles is a new visually attractive technique for displaying relations in hierarchical data, such as concept structures formed by 'subclass-of' and 'type-of' relations. We have developed a visualization library based on OWL API, as well as a plug-in for Protégé, a well-known ontology editor. The displayed adjacency relations can be selected from an ontology using a set of common configurations, allowing for intuitive discovery of information. Our evaluation demonstrates that the GLOW visualization provides better visual clarity, and displays relations and complex ontologies better than the existing Protégé visualization plug-in Jambalaya.
Extracted statement — implementation: GLOW
Research field: Graphics
Title: Using Hierarchical Edge Bundles to visualize complex ontologies in GLOW
Abstract: In the past decade, much effort has been put into the visual representation of ontologies. However, present visualization strategies are not equipped to handle complex ontologies with many relations, leading to visual clutter and inefficient use of space. In this paper, we propose GLOW, a method for ontology visualization based on Hierarchical Edge Bundles. Hierarchical Edge Bundles is a new visually attractive technique for displaying relations in hierarchical data, such as concept structures formed by 'subclass-of' and 'type-of' relations. We have developed a visualization library based on OWL API, as well as a plug-in for Protégé, a well-known ontology editor. The displayed adjacency relations can be selected from an ontology using a set of common configurations, allowing for intuitive discovery of information. Our evaluation demonstrates that the GLOW visualization provides better visual clarity, and displays relations and complex ontologies better than the existing Protégé visualization plug-in Jambalaya.
Extracted statement — System: GLOW
Research field: Graphics
Title: Formal Linked Data Visualization Model
Abstract: Recently, the amount of semantic data available in the Web has increased dramatically. The potential of this vast amount of data is enormous but in most cases it is difficult for users to explore and use this data, especially for those without experience with Semantic Web technologies. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. In this article we devise a formal Linked Data Visualization Model (LDVM), which allows to dynamically connect data with visualizations. We report about our implementation of the LDVM comprising a library of generic visualizations that enable both users and data analysts to get an overview on, visualize and explore the Data Web and perform detailed analyzes on Linked Data.
Extracted statement — implementation: LDVM
Research field: Graphics
Title: Formal Linked Data Visualization Model
Abstract: Recently, the amount of semantic data available in the Web has increased dramatically. The potential of this vast amount of data is enormous but in most cases it is difficult for users to explore and use this data, especially for those without experience with Semantic Web technologies. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. In this article we devise a formal Linked Data Visualization Model (LDVM), which allows to dynamically connect data with visualizations. We report about our implementation of the LDVM comprising a library of generic visualizations that enable both users and data analysts to get an overview on, visualize and explore the Data Web and perform detailed analyzes on Linked Data.
Extracted statement — System: LDVM
Research field: Graphics
Title: RDF data exploration and visualization
Abstract: We present Paged Graph Visualization (PGV), a new semi-autonomous tool for RDF data exploration and visualization. PGV consists of two main components: a) the "PGV explorer" and b) the "RDF pager" module utilizing BRAHMS, our high per-formance main-memory RDF storage system. Unlike existing graph visualization techniques which attempt to display the entire graph and then filter out irrelevant data, PGV begins with a small graph and provides the tools to incrementally explore and visualize relevant data of very large RDF ontologies. We implemented several techniques to visualize and explore hot spots in the graph, i.e. nodes with large numbers of immediate neighbors. In response to the user-controlled, semantics-driven direction of the exploration, the PGV explorer obtains the necessary sub-graphs from the RDF pager and enables their incremental visualization leaving the previously laid out sub-graphs intact. We outline the problem of visualizing large RDF data sets, discuss our interface and its implementation, and through a controlled experiment we show the benefits of PGV.
Extracted statement — implementation: PGV
Research field: Graphics
Title: RDF data exploration and visualization
Abstract: We present Paged Graph Visualization (PGV), a new semi-autonomous tool for RDF data exploration and visualization. PGV consists of two main components: a) the "PGV explorer" and b) the "RDF pager" module utilizing BRAHMS, our high per-formance main-memory RDF storage system. Unlike existing graph visualization techniques which attempt to display the entire graph and then filter out irrelevant data, PGV begins with a small graph and provides the tools to incrementally explore and visualize relevant data of very large RDF ontologies. We implemented several techniques to visualize and explore hot spots in the graph, i.e. nodes with large numbers of immediate neighbors. In response to the user-controlled, semantics-driven direction of the exploration, the PGV explorer obtains the necessary sub-graphs from the RDF pager and enables their incremental visualization leaving the previously laid out sub-graphs intact. We outline the problem of visualizing large RDF data sets, discuss our interface and its implementation, and through a controlled experiment we show the benefits of PGV.
Extracted statement — System: PGV
Research field: Graphics
Title: The Publishing Workflow Ontology (PWO)
Abstract: . In this paper we introduce the Publishing Workﬂow Ontology ( PWO ), i.e., an OWL 2 DL ontology for the description of workﬂows that is particularly suitable for formalising typical publishing processes such as the publication of articles in journals. We support the presentation with a discussion of all the ontology design patterns that have been reused for modelling the main characteristics of publishing workﬂows. In addition, we present two possible application of PWO in the publishing and legislative domains.
Extracted statement — Ontology: PWO