Catalog Data Research Articles

Analysis of interjections in Supporting Characters in the Novel “Rindu” by Tere Liye

The use of Interjection in supporting supporting characters in the novel "Rindu" by Tere LiyeThe method used is qualitative descriptive. The subject is the author, and the object is the Suppport character’s.The primary data source for this study is the novel "Rindu" by Tere Liye. The data is that all interjections used by the support characters in the text will be identified and analyzed.A purposive sampling technique..Instruments Used in Research: Author, Novel "RIndu" by Tere Liye, and Notebook, table (datasheet). Data collection tools are first, textual content: Tere Liye's novel. The data collection process involves several steps: Identification: Reading the novel to identify all instances of interjections used by the supporting character, Cataloging and classification Data Analysis Procedures are: 1. Identification of Interjections, 2.Classification of Interjections, 3. Contextual Analysis, 4.Frequency Analysis, and 5. Function Based on the results of the research, the most interjection words are the type of greeting and Farewell. Based on the results the type of use of greetings and farewells interjection is the most in total, as many as 30 interjections by supporting character's : Daeng andipati wife, Anna, Elsa, etc. Meanwhile, the figure who uses greetings and farewells the most is Anna with 15 word. The novel "Rindu" by Tere Liye employs interjections effectively to build the characters and enhance the emotional depth of the story. Here are several ways interjections contribute to character development in the novel: Expressing Emotions, Revealing Personality, Creating Realistic Dialogue, Indicating Cultural Background, Enhancing Tension and Drama, and Character Relationships.

Coastal and Marine Management – Navigating islands of data

The disciplines of Coastal Management and Marine Spatial Planning (MSP) are predominantly focussed on creating a regulatory and legislative framework within which national and regional planning policies, climate mitigation measures and environmental monitoring requirements can be effectively implemented. These evidence-based processes necessitate the discoverability, accessibility and integration of appropriate ‘trusted’ coastal and marine data together with contiguous terrestrial datasets. This presents significant challenges at national and local levels. While authoritative open data is often available, the data for any management requirement is often dispersed across a wide range of national online portals, statistical and research hubs, ‘scientific’ platforms and occasionally, private companies. This is exemplified in Ireland, where MSP is in its infancy, and consequently, the breadth of MSP foundational thematic marine data requirements required to comply with this Directive has yet to be fully realised by end-users/stakeholders and data providers. This study examines the nexus between mandatory data requirements of the European Community’s Infrastructure for Spatial Information in the European Community (INSPIRE) Directive11INSPIRE Directive (2007/2/EC) is a legal EU initiative to establish an INfrastructure for SPatial InfoRmation in Europe and to make geographical information more accessible and interoperable for the management of the environment and other wide range of purposes towards supporting sustainable development (EC, 2021) (2007/2/EC), (EC, 2007) and the evidence-base needs of its Maritime Spatial Planning (MSP) Directive (2014/89/EU). An extensive inventory of coastal and MSP thematic data features is identified and categorised (into sectoral/thematic clusters) and appropriate and authoritative online sources (where available) are scoped out. Through an in-depth interrogation of national and EU sectoral platforms or portals, (much of whose data was originally captured for a diverse range of applications and management processes), and in view of INSPIRE’s well-established (legally-binding) data specifications, standards and guidance, a methodology is presented to accelerate coastal and marine data discovery, and to collate or ‘group’ these authoritative data sources under broad but succinct MSP thematic headings. The resulting coastal and marine data catalogue is the first step in the creation of an easy data reference and retrieval tool for Irish coastal and marine practitioners, and presents a model for other nations.

Getting ready for the European Health Data Space (EHDS): IDERHA's plan to align with the latest EHDS requirements for the secondary use of health data.

The European Health Data Space (EHDS) shapes the digital transformation of healthcare in Europe. The EHDS regulation will also accelerate the use of health data for research, innovation, policy-making, and regulatory activities for secondary use of data (known as EHDS2). The Integration of heterogeneous Data and Evidence towards Regulatory and HTA Acceptance (IDERHA) project builds one of the first pan-European health data spaces in alignment with the EHDS2 requirements, addressing lung cancer as a pilot. In this study, we conducted a comprehensive review of the EHDS regulation, technical requirements for EHDS2, and related projects. We also explored the results of the Joint Action Towards the European Health Data Space (TEHDAS) to identify the framework of IDERHA's alignment with EHDS2. We also conducted an internal webinar and an external workshop with EHDS experts to share expertise on the EHDS requirements and challenges. We identified the lessons learned from the existing projects and the minimum-set of requirements for aligning IDERHA infrastructure with EHDS2, including user journey, concepts, terminologies, and standards. The IDERHA framework (i.e., platform architecture, standardization approaches, documentation, etc.) is being developed accordingly. The IDERHA's alignment plan with EHDS2 necessitates the implementation of three categories of standardization for: data discoverability: Data Catalog Vocabulary (DCAT-AP), enabling semantics interoperability: Observational Medical Outcomes Partnership (OMOP), and health data exchange (DICOM and FHIR). The main challenge is that some standards are still being refined, e.g., the extension of the DCAT-AP (HealthDCAT-AP). Additionally, extensions to the Observational Health Data Sciences and Informatics (OHDSI) OMOP Common Data Model (CDM) to represent the patient-generated health data are still needed. Finally, proper mapping between standards (FHIR/OMOP) is a prerequisite for proper data exchange. The IDERHA's plan and our collaboration with other EHDS initiatives/projects are critical in advancing the implementation of EHDS2.

The 17 January 1994 Northridge, California, Earthquake: A Retrospective Analysis

Abstract The 17 January 1994 Northridge, California, earthquake was a watershed event with far-reaching societal and scientific impacts. The earthquake, which occurred in the early days of both broadband seismic networks and the Internet, spurred advances in seismic monitoring, real-time systems, and development of data products. Motivated by the 30th anniversary of the earthquake, we present a brief retrospective of the earthquake and its impact, and reconsider both ground motions and the aftershock distribution using modern tools and the best-available data. With improvements in instrumentation and analysis methodology, recent earthquakes continue to reveal the increasing complexity of ground motions, fault systems, and earthquake ruptures. Even in the absence of data from state-of-the-art instrumentation, a retrospective consideration of ground-motion data from the Northridge earthquake reveals complexities beyond what could be characterized (and modeled) 30 yr ago. Aftershock relocations for both the 1971 Sylmar and 1994 Northridge earthquakes also reveal an updated view of fault complexity. Our study does provide a cautionary tale regarding legacy data sets and research results that are not easily accessible, which can result in discrepancies between catalog data and products from the best available science. We also briefly describe outreach products produced as a part of the anniversary commemoration.

Characteristics of Earthquake Mechanisms Along the Andaman - Nicobar Region derived from Bayesian Moment Tensor Inversion

Abstract Earthquake activities in the Andaman - Nicobar region are generated mainly by several active faults and an active subduction zone that can activate multiple hypocenter clusters. Therefore, studying the seismotectonic process from source mechanism analysis using moment tensor inversion is essential. In this research, we applied a stochastic Bayesian inversion using Grond, a framework tool for moment tensor (MT) inversion, to characterize the earthquake mechanisms and the most appropriate centroid locations. Procedurally, several of the largest earthquakes with a moment magnitude Mw > 5.5 from 2007 to 2023 were analyzed using the regional and teleseismic networks up to 2000 km from the epicenter based on 1 Hz green function model and azimuthal gap coverage. We applied 10,000-30,000 iterations of inversions with 300 bootstrap chains for a stable result. The low-frequency bandpass with a range of 0.007 - 0.03 Hz was chosen for the inversion process. There were 17 solutions for earthquake mechanisms with good misfit values of < 0.65. Based on the division of the 5 clusters with the highest seismicity, the selected earthquakes’ source mechanism is dominated by strike-slip and oblique faulting. The results were compared with existing data catalogs showing differences in hypocentre and fault orientation direction, particularly for strike-slip earthquakes in the shallow crust and mantle zones.

The Contribution of Host Galaxy Properties in X-Ray Active Galactic Nuclei Clusters

In this study, the influence of host galaxy properties on X-ray active galactic nuclei (AGN) clusters was investigated using multiwavelength data. X-ray data from the eFEDS main catalog, optical and near-infrared data from the fourth data release of KiDS/VIKING, and mid-infrared data from WISE were utilized. By integrating these datasets and employing the CIGALE code, the star formation rate, luminosity, and stellar mass of the host galaxies were estimated. The analysis reveals significant associations between luminosity, stellar mass, and star formation rate, providing valuable insights into AGN activity. Furthermore, AGN clusters were compared with non-AGN clusters to uncover distinctive characteristics. AGN clusters exhibit differences in their population across various luminosity levels. Interestingly, a significant proportion of AGN clusters is concentrated in the middle range of luminosity (45-46 measured in logL<sub>(0.5-2.0 keV)</sub>) for both low and high redshift classifications. Additionally, galaxies hosting AGNs detected in X-ray emission tend to fall within a specific range of stellar mass (10-11 measured in log(M<sub>⋆</sub>(M<sub>⊚</sub>)). This stellar mass range is populated by a substantial number of AGN galaxies, irrespective of their redshift classification. Moreover, a significant population of X-ray AGN is concentrated within the star formation rate range of 1.5-2.5 (expressed in log(M<sub>⊚</sub> yr<sup>-1</sup>)) in both low and high redshift regions. By analyzing the dependencies on luminosity, stellar mass, and star formation rate, this study provides valuable insights into the correlation and relationship between AGN clusters and their host galaxies. The comparison with non-AGN clusters and the integration of multiwavelength data from eFEDS, KiDS/VIKING, and WISE enhance the depth of analysis, contributing to a comprehensive evaluation of AGN clusters. These findings advance our understanding of the complex relationship between AGN clusters and host galaxy properties in the field of astrophysics.

A consistent explanation of seemingly inconsistent experimental and theoretical data for N[formula omitted]O + O via MultiScale Informatics

The N2O + O reaction plays a critical role in NOx formation at high pressures and low peak temperatures, in the “dark zone” region of deflagration waves of organic energetic materials, and in N2O consumption in NH3 combustion. While the rate constant for N2O + O = NO + NO (R3) is considered reasonably well established, viewpoints regarding the rate constants for N2O + O = N2 + O2 (R2)—and even the main products of the N2O + O reaction—have not reached a consensus, with studies from the past few years continuing to reach drastically different conclusions. To date, no single model has been presented that can reproduce all key datasets on both sides of the debate. Using the MultiScale Informatics (MSI) approach, we identified a model consistent with a vast catalog of theoretical and experimental data previously used to determine rate constants for R2, R3, and other key reactions influencing experimental interpretations. Notably, this MSI model (presented herein) reproduces all experimental datasets previously used to anchor low-activation-energy k2 expressions that greatly favor R2 at intermediate temperatures. However, its kinetic parameters are also consistent with theoretical calculations that instead show high activation energy for R2 and k2 values many orders of magnitude lower—such that R3 is the main channel at essentially all temperatures. This model is also consistent with our new experimental data (presented in our companion paper) at optimally selected conditions that avoid the interpretation ambiguities that have hindered definitive conclusions from previous experimental data. The present analysis elucidates the role of secondary reactions that would have artificially inflated the apparent k2/k3 ratio previously deduced from experiments in a manner that may not have been detectable from even multi-species measurements at typical conditions—and may, therefore, explain the persistent historical difficulties in establishing the main products of N2O + O.Novelty and significance statementDespite decades of research, viewpoints regarding the rate constants for N2O + O = N2 + O2 (R2)—and even the main products of the N2O + O reaction—have not reached a consensus, with studies from the past few years still reaching drastically different conclusions. To date, no single model has been presented that can reproduce all key datasets on both sides of the debate. Here, we present a single model consistent with a vast catalog of theoretical and experimental data, including all experimental datasets previously used to anchor low-activation-energy expressions for k2 that greatly favor R2 as the main channel at intermediate temperatures—but with kinetic parameters consistent with theoretical calculations that instead show high activation energy for R2 and N2O + O = NO + NO (R3) as the main channel at essentially all temperatures.

On the Impact of Geospace Weather on the Occurrence of M7.8/M7.5 Earthquakes on 6 February 2023 (Turkey), Possibly Associated with the Geomagnetic Storm of 7 November 2022

A joint analysis of solar wind, geomagnetic field, and earthquake catalog data showed that before the catastrophic M = 7.8 and M = 7.5 Kahramanmaras earthquake sequence on 6 February 2023, a closed strong magnetic storm occurred on 7 November 2022, SYM/H = −117 nT. The storm started at 08:04 UT. At this time, the high-latitudinal part of Turkey’s longitudinal region of future epicenters was located under the polar cusp, where the solar wind plasma would directly access the Earth’s environment. The time delay between storm onset and earthquake occurrence was ~91 days. We analyzed all seven strong (M7+) earthquakes from 1967 to 2020 to verify the initial findings. A similar pattern has been revealed for all events. The time delay between magnetic storm onset and earthquake occurrence varies from days to months. To continue these investigations, a retrospective analysis of seismic and other geophysical parameters just after preceded geomagnetic storms in the epicenter areas is desirable.

Design of Library Collection Procurement System in Bali

The process of library collection development encompasses several crucial tasks, including identification, selection, acquisition, processing, and distribution of collections to the public. This study endeavors to develop a library collection procurement application focusing on two primary functionalities: selection and procurement. The system accommodates stakeholders, including publishers, librarian profiles, system masters, and other users, while adhering to specific user and system requirements. The design methodology employed in this study leverages the Unified Modeling Language (UML). The development process follows the waterfall method, encompassing stages such as requirements analysis, design, implementation, verification, and maintenance. The resulting application features an intuitive interface for collection procurement, incorporating essential components such as login mechanisms, a comprehensive book collection database, catalog data management, procurement selection tools, recommendation algorithms, catalog selection options, and access to selected catalog data. Employing the CodeIgniter (CI) framework, the system facilitates data filtration and selection processes based on publication year, price, and language criteria. Rigorous system testing, conducted through black box testing methods, confirms the functionality and reliability of the application. This research contributes to addressing the needs of libraries lacking robust collection procurement systems, offering a sophisticated solution to streamline and automate traditionally manual processes.

Synthetic orbit uncertainty generation through regression analysis of historical Conjunction Data Messages

In the last decades, the Earth-orbiting population of both active and non-active objects has grown significantly, leading to a substantial increase in number of possible in-orbit collisions. It is therefore crucial to monitor the orbit of space resident objects to assess in advance the threat of risky conjunctions. Within this framework, the 18th Space Defense Squadron (SDS) is consistently updating the orbit of thousands of tracked objects by processing observations of the U.S. Space Surveillance Network (SSN). The determined orbital data is continuously maintained in the Special Perturbation (SP) catalogue and used by the 19th SDS to issue close approach warnings to satellite operators around the globe in the form of Conjunction Data Messages (CDM). The Flight Dynamics (FD) group of the German Space Operation Centre (GSOC) receives on regular basis a subset of the SP catalogue data along with CDMs associated to the fleet of its controlled satellites. The SP ephemerides are in fact provided without any covariance information preventing any computation of the Probability of Collision (Pc). In GSOC FD we are implementing a service to link a series of synthetic orbital error covariance matrices to a given SP ephemeris by statistically analyzing historical CDMs of past events. More than 30 GB of past conjunction data are processed to extract state vector, covariance matrix and object size parameter of already encountered secondary objects. The orbital errors of these last are subsequently categorized and divided into orbital classes to decouple the high correlation the covariance has with respect to solar flux, object dimension, altitude of perigee, eccentricity and orbit inclination. The classification aims at collecting similar CDMs regarding the aforementioned dependencies, and approximates the predicted 1-sigma position errors in the orbital frame by optimal curve-fitting techniques. By evaluation of the curve fitting coefficients of a requested orbit class a covariance matrix can be generated for any prediction time in upcoming CDM refinements and other analyses. The work discusses the limiting cases of the classification approach, bringing possible solutions to the scenario of empty classes. An in-depth characterization of the parameters that affect the orbital errors is in fact performed to individualize the neighboring class that provides the closest and most meaningful covariance timeline. Successively, the effect of using synthetic covariance in a conjunction risk assessment is also explored, adapting the problem on real operations. Lastly, the entire data processing pipeline and how the described service fits into the GSOC Flight Dynamics System (FDS) framework is described.

Towards a Data Catalog for Data Analytics

Understanding the reliability and health of critical business assets is essential for every organization. Digital transformation changes users' behaviours and imposes several challenges to organizations that need to collect and use more diversified data to improve digital services, drive decision-making, and spur innovation. Coupled with data growth and diversification, new approaches for analysing data rely on the schema-on-read approach, prioritizing data collection over data organization. Thus, knowing where data is stored, and how can be used, improves the capability to respond to business changes and thus helps to take better actions. To enable the creation, verification, and upkeep of dashboards in the analytical system, this work proposes a measure data catalog used to support the management and validation of metadata.

The KISS Network in 2015–2016: Catalogs and Comparison of the Processing Results with Operational Estimates from the Permanent Network

As part of the international collaboration of several research groups from Russia, France, and Germany, 77 temporary seismic stations were installed in the summer of 2015 for one-year period to conduct a detailed study of the deep structure of the Earth’s crust and upper mantle in the region of the Klyuchevskoi Volcano Group (KGV) in the Kamchatka Peninsula. One of the results of the KISS experiment (Klyuchevskoi Investigation – Seismic Structure of an extraordinary volcanic system) was the final catalog of the joint data from the temporary stations and the permanent network of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS). The catalog comprises 2136 events, including 560 for which the permanent network catalog lacked sufficient data for correct processing. The catalog in .xlsx format and the station bulletin in .isf format are presented in the supplementary material to the paper. A comparative analysis was conducted on the joint solutions of two catalogs: one obtained solely from the data of the KB GS RAS permanent network stations and another from a denser seismic network integrated with KISS stations.

An interoperable software system to store, associate, visualize, and publish global open science data of earth surface system

Multi-source heterogeneous, multi-modal, and multi-type open scientific data (e.g., thematic sharing sites, metadata, journal articles, etc.) on earth surface systems (EES) provide important data sources for knowledge mining, discovery, and accurate recommendations, and also pose increasing challenges, resulting in the need to develop appropriate tools to address these challenges and support decision-making. This paper constructs an interoperable software system to store, visualize, and publish open science data of ESS. Utilizing an open scientific data catalogue repository encompassing EES information as foundational input and employing an integrated modeling methodology, this system endeavors to synthesize heterogeneous surface data of diverse linguistic, sourced, and typological origins. The objective is to facilitate multidimensional data retrieval and precise data auto-recommendation, thereby fostering the dissemination of scientific data and facilitating value-added services within EES domain. The tool may be used by stakeholders including researchers, data analysts, policymakers and national authorities to support decision-making on questions ranging from locating the location of open data related to the topic, to discovering high-quality data, selecting the data with the better overall evaluation. Along with a description of the system/platform design process, its structure, and the constituent models, key results are presented relating to the user interface, and several application examples. Software systems can help modelers to use the best features of a single software tool to answer open scientific data-related questions that seek to discovery, use, comparison or synthesis within or across topics of ESS.

Basic Performance Evaluation of a Radiation Survey Meter That Uses a Plastic-Scintillation Sensor.

After the Fukushima nuclear power plant accident in 2011, many types of survey meters were used, including Geiger-Müller (GM) survey meters, which have long been used to measure β-rays. Recently, however, a novel radiation survey meter that uses a plastic-scintillation sensor has been developed. Although manufacturers' catalog data are available for these survey meters, there have been no user reports on performance. In addition, the performance of commercial plastic-scintillation survey meters has not been evaluated. In this study, we experimentally compared the performance of a plastic-scintillation survey meter with that of a GM survey meter. The results show that the two instruments performed very similarly in most respects. The GM survey meter exhibited count losses when the radiation count rate was high, whereas the plastic-scintillation survey meter remained accurate under such circumstances, with almost no count loss at high radiation rates. For measurements at background rates (i.e., low counting rates), the counting rates of the plastic-scintillation and GM survey meters were similar. Therefore, an advantage of plastic-scintillation survey meters is that they are less affected by count loss than GM survey meters. We conclude that the plastic-scintillation survey meter is a useful β-ray measuring/monitoring instrument.

The W3C Data Catalog Vocabulary, Version 2: Rationale, Design Principles, and Uptake

ABSTRACT DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. Since its first release in 2014 as a W3C Recommendation, DCAT has seen a wide adoption across communities and domains, particularly in conjunction with implementing the FAIR data principles (for findable, accessible, interoperable and reusable data). These implementation experiences, besides demonstrating the fitness of DCAT to meet its intended purpose, helped identify existing issues and gaps. Moreover, over the last few years, additional requirements emerged in data catalogs, given the increasing practice of documenting not only datasets but also data services and APIs. This paper illustrates the new version of DCAT, explaining the rationale behind its main revisions and extensions, based on the collected use cases and requirements, and outlines the issues yet to be addressed in future versions of DCAT.

Planets similar in size are often dissimilar in interior

The number of discovered exoplanets now exceeds 5500 allowing statistical analyses of planetary systems. Multi-planet systems are mini-laboratories of planet formation and evolution, and analysing their system architectures can help us to constrain the physics of these processes. Recent works have found evidence of significant intrasystem uniformity in planet properties such as radius, mass, and orbital spacing, collectively termed ‘peas in a pod’ trends. In particular, correlations in radius and mass have been interpreted as implying uniformity in planet bulk density and composition within a system. However, the samples used to assess trends in mass tend to be small and biased. In this paper, we re-evaluate correlations in planet properties in a large sample of systems with at least two planets for which mass and radius have been directly measured, and therefore bulk density can be calculated. Our sample was assembled using the most up-to-date exoplanet catalogue data, and we compute the relevant statistics while using a procedure to ‘weight’ the data points according to measurement precision. We find a moderate correlation in radius and a weak correlation in the densities of adjacent planets. However, masses of neighbouring planets show no overall correlation in our main sample and a weak correlation among pairs of planets similar in size or pairs restricted to Mp<100 M⊕, Rp<10 R⊕. Similarly, we show that the intrasystem dispersion in radius is typically less than that in mass and density. We identify ranges in stellar host properties that correlate with stronger uniformity in pairs of adjacent planets: low Teff for planet masses, and low metallicity and old age for planet densities. Furthermore, we explore whether peas in a pod trends extend into planet compositions or interior structures. For small neighbouring planets with similar radii, we show that their masses and interior structures are often disparate, indicating that even within the same system, similarity in radii is not necessarily a good proxy for similarity in composition or the physical nature of the planets.

Model-Driven Approach for Making Citizen Science Data FAIR

Citizen Science (CS) initiatives have proliferated in different scientific and social fields, producing vast amounts of data. Existing CS projects usually adopt PPSR Core as a data and metadata standard. However, these projects are still not FAIR (Findable, Accessible, Interoperable and Reusable)-compliant. We propose to use DCAT as a data and metadata standard since it helps to improve the interoperability of CS data catalogs and all the FAIR features. For this purpose, in this paper we present a model-driven approach to make CS data FAIR. Our approach has the following contributions: (i) the definition of a metamodel based on PPSR Core, (ii) the definition of a DCAT profile for CS, (iii) a definition of set of automated transformations from PPSR Core to DCAT. Finally, the implementation of the model-driven process has been validated by evaluating several FAIR metrics. The results show that our proposal has significantly improved the FAIR quality of CS projects.

Exploring Opportunities for Clinical Data Warehouse Enhancement Through Data Catalog Integration.

Secondary use of clinical health data implies a prior integration of mostly heterogenous and multidimensional data sets. A clinical data warehouse addresses the technological and organizational framework conditions required for this, by making any data available for analysis. However, users of a data warehouse often do not have a comprehensive overview of all available data and only know about their own data in their own systems - a situation which is also referred to as 'data siloed state'. This problem can be addressed and ultimately solved by implementation of a data catalog. Its core function is a search engine, which allows for searching the metadata collected from different data sources and thereby accessing all data there is. With this in mind, we conducted an explorative online market survey followed by vendor comparison as a pre-requisite for system selection of a data catalog. Assessment of vendor performance was based on seven predetermined and weighted selection criteria. Although three vendors achieved the highest score, results were lying closely together. Detailed investigations and test installations are needed for further narrowing down the selection process.

Real-Time Clickstream Analytics with Apache

The purpose of this research work is to provide an overview of setting up an Apache-based real-time clickstream data lifecycle for user behaviour analysis and marketing strategy improvement. It uses tools like Apache Kafka, Apache Spark, Amazon S3, AWS Glue Data Catalog, Hive Metastore, and Tableau to meet the challenges of data collecting, purification, and storage. The design offers rapid data processing and analysis using Spark, high-throughput and fault-tolerant data import with Kafka, and scalable storage in Amazon S3. Data retrieval, querying, and transformation are made easier by AWS Glue Data Catalogue and Hive Metastore, while Tableau offers interactive visualisations. Data management capabilities are improved by optional interaction with a data warehouse and data lake. The scalable architecture accommodates increased data quantities and user traffic, and a mathematical model derives useful insights from clickstream data.

WFC3 Infrared Spectroscopic Parallel (WISP) survey: photometric and emission-line data release

ABSTRACT We present reduced images and catalogues of photometric and emission-line data (∼230 000 and ∼8000 sources, respectively) for the WFC3 (Wide Field Camera 3) Infrared Spectroscopic Parallel (WISP) survey. These data are made publicly available on the Mikulski Archive for Space Telescopes and include reduced images from various facilities: ground-based ugri, Hubble Space Telescope (HST) WFC3, and Spitzer IRAC (Infrared Array Camera). Coverage in at least one additional filter beyond the WFC3/IR data are available for roughly half of the fields (227 out of 483), with ∼20 per cent (86) having coverage in six or more filters from u band to IRAC 3.6 $\mu$m (0.35–3.6 $\mu$m). For the lower spatial resolution (and shallower) ground-based and IRAC data, we perform PSF (point spread function)-matched, prior-based, deconfusion photometry (i.e. forced-photometry) using the tphot software to optimally extract measurements or upper limits. We present the methodology and software used for the WISP emission-line detection and visual inspection. The former adopts a continuous wavelet transformation that significantly reduces the number of spurious sources as candidates before the visual inspection stage. We combine both WISP catalogues and perform spectral energy distribution fitting on galaxies with reliable spectroscopic redshifts and multiband photometry to measure their stellar masses. We stack WISP spectra as functions of stellar mass and redshift and measure average emission-line fluxes and ratios. We find that WISP emission-line sources are typically ‘normal’ star-forming galaxies based on the mass–excitation diagram ([O iii]/Hβ versus M⋆; 0.74 < zgrism < 2.31), the galaxy main sequence (SFR versus M⋆; 0.30 < zgrism < 1.45), S32 ratio versus M⋆ (0.30 < zgrism < 0.73), and O32 and R23 ratios versus M⋆ (1.27 < zgrism < 1.45).