Science Data Products Research Articles

The Design of GECAM Scientific Ground Segment

The Gravitational wave burst high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a dedicated mission for monitoring high-energy transients. Here we report the design of the GECAM Scientific Ground Segment (GSGS) in terms of the scientific requirements, including the architecture, the external interfaces, the main function, and workflow. Judging from the analysis and verification results during the commissioning phase, the GSGS functions well and is able to monitor the status of the payloads, adjust the parameters, develop the scientific observation plans, generate the scientific data products, analyze the data, etc. Thus, the on-orbit operation and scientific researches of GECAM are guaranteed.

From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones

This paper presents an innovative, holistic, and comprehensive approach to drone-based imaging spectroscopy based on a small, cost-effective, and lightweight Unmanned Aerial Vehicle (UAV) payload intended for remote sensing applications. The payload comprises a push-broom imaging spectrometer built in-house with readily available Commercial Off-The-Shelf (COTS) components. This approach encompasses the entire process related to drone-based imaging spectroscopy, ranging from payload design, field operation, and data processing to the extraction of scientific data products from the collected data. This work focuses on generating directly georeferenced imaging spectroscopy datacubes using a Do-It-Yourself (DIY) imaging spectrometer, which is based on COTS components and freely available software and methods. The goal is to generate a remote sensing reflectance datacube that is suitable for retrieving chlorophyll-A (Chl-A) distributions as well as other properties of the ocean spectra. Direct georeferencing accuracy is determined by comparing landmarks in the directly georeferenced datacube to their true location. The quality of the remote sensing reflectance datacube is investigated by comparing the Chl-A distribution on various days with in situ measurements and satellite data products.

Spatially constrained atmosphere and surface retrieval for imaging spectroscopy

Imaging spectrometers provide important Earth surface data for terrestrial and aquatic ecology, hydrology, geology through retrieved surface reflectance spectra. Surface reflectance is generally recovered from measured radiance through model inversions of the surface and atmospheric system. Most retrieval approaches treat all pixels independently and ignore spatial correlations in the atmosphere for neighboring pixels, resulting in surface-related biases in the retrieved surface and atmospheric parameters. In this work, we present a mathematical framework to more accurately retrieve surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. This framework retrieves the full spatial–spectral reflectance data cube in a computationally efficient manner and is to our knowledge the first approach capable of accurately finding this global solution for large imaging spectroscopy datasets. We implement this mathematical framework in an example proposed algorithm which we call spatially constrained optimal estimation (SCOE). We show that SCOE improves the overall surface reflectance retrieval error, reduces surface-related biases in the retrieved surface reflectance and atmospheric parameters, and is more robust to noise than a traditional pixel-by-pixel approach and an operational empirical line approach in simulated and experimental results. This reduction in surface reflectance error will impact science data products across application areas, making imaging spectroscopy algorithms more robust for global acquisitions.

The EarthCARE mission – science and system overview

Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is a satellite mission implemented by the European Space Agency (ESA), in cooperation with the Japan Aerospace Exploration Agency (JAXA), to measure global profiles of aerosols, clouds and precipitation properties together with radiative fluxes and derived heating rates. The simultaneous measurements of the vertical structure and horizontal distribution of cloud and aerosol fields, together with outgoing radiation, will be used in particular to evaluate their representation in weather forecasting and climate models and to improve our understanding of cloud and aerosol radiative impact and feedback mechanisms. To achieve the objective, the goal is that a retrieved scene with footprint size of 10 km × 10 km is measured with sufficiently high resolution that the atmospheric vertical profile of short-wave (solar) and long-wave (thermal) flux can be reconstructed with an accuracy of 10 W m−2 at the top of the atmosphere. To optimise the performance of the two active instruments, the platform will fly at a relatively low altitude of 393 km, with an equatorial revisit time of 25 d. The scientific payload consists of four instruments: an atmospheric lidar, a cloud-profiling radar with Doppler capability, a multi-spectral imager and a broadband radiometer. Co-located measurements from these instruments are processed in the ground segment, which produces and distributes a wide range of science data products. As well as the Level 1 (L1) product of each instrument, a large number of multiple-instrument L2 products have been developed, in both Europe and Japan, benefiting from the data synergy. An end-to-end simulator and several test scenes have been developed that simulate EarthCARE observations and provide a development and test environment for L1 and L2 processors. Within this paper the EarthCARE observational requirements are addressed. An overview is given of the space segment with a detailed description of the four science instruments, demonstrating how the observational requirements will be met. Furthermore, the elements of the space segment and ground segment that are relevant for science data users are described and the data products are introduced.

First results from the Solar Orbiter Heavy Ion Sensor

Aims. Solar Orbiter launched in February 2020 with the goal of revealing the connections between the Sun’s interior, atmosphere, and the heliosphere. The Solar Orbiter Heavy Ion Sensor (HIS) is a time-of-flight ion mass spectrometer dedicated to measuring heavy ions in the solar wind. Methods. We present an overview of the first measurements of heavy ion composition from HIS, reviewing the methods used to transform the spectra obtained on board into scientific data products and examining two solar wind case studies as well as the statistical properties of the heavy ion composition observed by HIS. We also carried out a comparison with prior measurements of heavy ions at L1. Results. The HIS data set provides the first mass- and charge-resolved heavy ion measurements in the inner heliosphere. Conclusions. These high temporal resolution data have the potential to transform our understanding of the connections between the solar wind and its origin at the Sun, as well as the interaction between the solar wind and the environment around planets, comets, and in the interstellar medium.

Processing & Production of Scientific Data: An historical marriage, now in a permanent divorce?

Once upon a time, the same person generated and then processed data arising from an original scholarly pursuit. For example: an early modern astronomer predicted sky phenomena based on their observation; a ship's navigator plotted a course using readings from their instruments; and a natural philosopher uncovered laws of nature from basic physical measurements. These measuring and calculating skills would have been studied in tandem before being applied, thus ensuring their wedded deployment. And fittingly, when any results became known, "who got credit" would have been clear.

Establishing a sound scientific data ecosystem through the implementation of a data element policy

It has been widely recognized that data have become a basic and strategic resource at home and abroad, ranking as a production factor with land, labor, capital and technology. Scientific data are an important part of data elements. High-quality scientific data are a necessary strategic resource to promote the development of science and technology. Focusing on the characteristics of scientific data (e.g. openness, multi-level integration and evolution, and scientific data life cycle management), this paper analyzes the development and problems of scientific data in China, and puts forward comprehensive suggestions on establishing a sound scientific data ecosystem. By establishing and improving the data basic policy system, building a multi-agent governance framework, and strengthening the capacity of scientific data infrastructure and talent training, the paper aims to gradually create a virtuous circle of scientific data production, utilization, sharing and reuse.

Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign

Abstract. Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, western Germany, which is a pollution hotspot in Europe comprising urban and large industrial sources. The DOAS measurements are used to validate spaceborne NO2 tropospheric vertical column density (VCD) data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements that were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km × 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two Zenith-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 ± 0.09 and 0.89 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m × 30 m, the AirMAP tropospheric NO2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km × 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The observations on the 7 flight days show strong NO2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions. The AirMAP campaign data set is compared to the TROPOMI NO2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 ± 0.02 and a median relative difference of −9 %. With the modifications in the NO2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 ± 0.06 and +20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation data set has been and can be further significantly improved.

Global landscape of randomized controlled trials responding to the COVID-19 pandemic: a literature review protocol

Introduction: Evidence-based care is challenging during public health crisis. During the COVID-19 pandemic, although the tremendous number of clinical trials were conducted, small trials were prevalent, which posed the risk of duplication, heterogeneity, underreporting and limited applicability of the trial results to patients in the clinical setting. These factors are known to potentially jeopardize the efficient production of scientific data for evidence-based care. The objective of this review is to critically appraise the characteristics of randomized controlled trials related to COVID-19 therapeutics and vaccines. This article is a protocol for literature review. Methods: This review will include randomized controlled trials (RCTs) on therapeutics and vaccines for COVID-19. Therapeutics include a single drug or a combination of multiple drugs for COVID-19. Non-human trials will be excluded. The search strategy is designed for identifying publication of study results in peer-review journals. Databases to be searched include MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), Web of science and CINAHL. Two or more independent reviewers will screen identified publications for inclusion/exclusion and retrieve data including standard information of studies and specific details about RCT designs as well as reporting, for which we will follow the set of information in international trial registries and the CONSORT statement. Discussion: It remains unclear what should be improved or strengthened for ecosystems of clinical trials for future pandemics. This review is expected to provide a landscape of RCTs related to COVID-19 therapeutics and vaccines and to explicitly show successful factors for evidence generation in response to pandemics.

Plans for building a prototype SKA regional centre in India

In order to deliver the full science potential of the Square Kilometer Array (SKA) telescope, several SKA Regional Centres (SRCs) will be required to be constructed in different SKA member countries around the world. These SRCs will provide high performance compute and storage for the generation of advanced science data products from the basic data streams generated by the SKA Science Data Handling and Processing system, critically necessary to the success of the key science projects to be carried out by the SKA user community. They will also provide support to astronomers to enable them to carry out analysis on very large SKA datasets. Construction of such large data centres is a technical challenge for all SKA member nations. In such a situation, each country plans to construct a smaller SRC over the next few years (2022 onwards), known as a proto-SRC. In India, we propose to construct a proto-SRC which will be used for the analysis of data from SKA pathfinders and precursors with strong Indian involvement such as uGMRT, Meerkat and MWA. We describe our thinking on some aspects of the the storage, compute and network of the proto-SRC and how it will be used for data analysis as well as for carrying out various simulations related to SKA key science projects led by Indian astronomers. We also present our thoughts on how the proto-SRC plans to evaluate emerging hardware and software technologies and to also begin software development in areas of relevance to SKA data processing and analysis such as algorithm implementation, pipeline development and data visualisation software.

Observed Atmospheric Features for the 2022 Hunga Tonga Volcanic Eruption from Joint Polar Satellite System Science Data Products

The Joint Polar Satellite System (JPSS) mission has provided over ten years of high-quality data products for environment forecasting and monitoring through the current Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Particularly, the sensor data record (SDR) and the derived environmental data record (EDR) products from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapping and Profiler Suite (OMPS) offer an unprecedented opportunity to observe severe weather and environmental events over the Earth. This paper presents the observations about atmospheric features of the Hunga Tonga Volcanic eruption of January 2022, e.g., the gravity wave, volcanic cloud, and aerosol (sulfate) plume phenomena, by using the ATMS, CrIS, OMPS, and VIIRS SDR and EDR products. Powerful gravity waves ringing through the atmosphere after the eruption of the Hunga Tonga volcano are discovered at two CrIS upper sounding channels (670 cm−1 and 2320 cm−1) in the deviations of the observed brightness temperature (O) from the simulated baseline brightness temperature (B) using the Community Radiative Transfer Model (CRTM), i.e., O—B. A similar pattern is also observed in the ATMS global maps at channel 15, whose peak weighting function is around 40 km, showing the atmospheric disturbance caused by the eruption that reached 40 km above the surface. The Tonga volcanic cloud (plume) was also captured by the OMPS SO2 EDR product. The gravity wave features were also captured in the native resolution image of the S-NPP VIIRS I-5 band nighttime observations. In addition, the VIIRS Aerosol Optical Depth (AOD) captured and tracked the volcanic aerosol (sulfate) plume successfully. These discoveries demonstrate the scientific potential of the JPSS SDR and EDR products in monitoring and tracking the eruption of the Hunga Tonga volcano and its severe environmental impacts. This paper presents the atmospheric features of the Hunga Tonga volcano eruption that is uniquely captured by all four advanced sensors onboard JPSS satellites, with different spectral coverages and spatial resolutions.

SIRGAS reference frame analysis at DGFI–TUM

Abstract The Deutsches Geodätisches Forschungsinstitut (DGFI) has been involved in the research activities of the Latin American Reference Frame SIRGAS since its establishment in 1993. DGFI coordinated the SIRGAS Global Positioning System campaigns of 1995 and 2000 and acted as an analysis centre of both campaigns contributing to the first two SIRGAS realisations known as SIRGAS95 and SIRGAS2000. In 1996, DGFI established the Regional Network Associate Analysis Centre for SIRGAS of the International GNSS (Global Navigation Satellite System) Service (IGS RNAAC SIRGAS) and took on responsibility for processing the SIRGAS continuously operating stations and generating weekly position solutions. Later followed the determination of cumulative (multi-year) solutions, consisting of station positions and constant velocities, providing accurate solutions for the SIRGAS reference frame. DGFI was integrated into the Technical University of Munich (TUM) in 2015, becoming DGFI–TUM, and based on the SIRGAS operational analyses, it continues investigating strategies to guarantee the reliability of the reference frame through time. This includes the estimation of the reference frame kinematics, evaluation, modelling, and reduction of seismic and post-seismic deformations on the reference frame, and modelling crustal kinematics in the SIRGAS region by continuous velocity models. This article summarises analysis strategies and science data products developed by DGFI–TUM as a SIRGAS analysis centre and as the IGS RNAAC SIRGAS. Special care is given to the determination of the most recent SIRGAS reference frame solution called SIRGAS2022, which is based on the second SIRGAS reprocessing campaign performed by DGFI–TUM to obtain homogeneously computed SIRGAS daily and weekly station position solutions referring to the IGS reference frame IGS14/IGb14 since January 2000.

Calibration Inter-Comparison of MODIS and VIIRS Reflective Solar Bands Using Lunar Observations

Multispectral band observations from Terra and Aqua MODIS, launched in December 1999 and May 2002, respectively, and from SNPP and NOAA-20 VIIRS, launched in November 2011 and October 2017, respectively, have continuously enabled a broad range of applications and studies of the Earth system and its changes via a set of geophysical and environmental parameters. The quality of MODIS and VIIRS science and environmental data products relies strongly on the calibration accuracy and stability of individual sensors, as well as their calibration consistency, especially for the data products generated using observations from sensors across different platforms. Both MODIS and VIIRS instruments carry a similar set of on-board calibrators for their on-orbit calibration. Besides, lunar observations are regularly scheduled and implemented in support of their reflective solar bands (RSB) calibration, especially their long-term stability monitoring. In this paper, we provide an overview of MODIS and VIIRS solar and lunar calibration methodologies applied for the RSB on-orbit calibration, and describe the approach developed for their calibration inter-comparisons using lunar observations, including corrections for the effects caused by differences in the relative spectral response and adopted solar spectra between individual sensors. The MODIS and VIIRS calibration inter-comparison results derived from their regularly scheduled lunar observations are presented and discussed, including associated uncertainties and a comparison with those derived using the Earth-view targets. Also discussed are remaining challenges in lunar calibration and inter-comparison for the Earth-observing sensors, as well as on-going efforts for future improvements.

Application of geographical information system-based analytical hierarchy process modeling for flood susceptibility mapping of Krishna District in Andhra Pradesh.

Flooding is one of the most catastrophic natural disasters in terms of provoking socio-economic losses. The current study is to foster a flood susceptibility map of Krishna District in Andhra Pradesh (AP) through integrating remote sensing data, geographical information system (GIS), and the analytical hierarchy process (AHP). Eleven factors, including elevation, slope, aspect, land use/land cover (LULC), drainage density, topographic wetness index, stream power index, lithology, soil, precipitation, and distance from the streams, are considered for identifying and evaluating the spatial distribution of critical flood-susceptible regions. Thematic maps of different factors were derived in GIS using remote sensing data obtained from Sentinel-2A (satellite sensor), shuttle radar topography mission digital elevation model (SRTM DEM v3), and other scientific data products. An analytical hierarchy process is a mathematical approach for decision support, primarily based on the weight and rank of different causative factors. AHP technique is implemented for flood hazard modeling and ascertaining the Flood Hazard Index (FHI) to produce a flood susceptibility map. Different thematic maps weighed with the AHP framework are combined using overlay analysis to produce the flood susceptibility map of the study region. The outcomes of the study demonstrate the potential of GIS and AHP in providing a premise to recognize the vulnerable areas that are susceptible to flood. According to the findings, the Flood Hazard Index is 42% and the study region is classified into very high, high, moderate, low, and very low susceptible, respectively. Following that, historical flood data was used to validate the accuracy of the generated flood susceptibility map. This shows that a maximum of 90% of the data points are within floodplain.

A probabilistic approach: Uncertain navigation of the uncertain web

SummaryIn the era of Internet Technology (IT), uncertainty management is a challenge in many fields. These include e‐commerce, social and sensor networks, scientific data production and mining, object tracking, data integration, geo‐located services, and recently Internet and Web of Things. Due to the uncertain data published on the web, web resources are diverse. Hence, identical resources could be available from heterogeneous platforms and heterogeneous resources could represent the same objects. These resources are hugely heterogeneous, conflict, inconsistent, or have incompatible formats. This uncertainty is inherently related to many facts, such as information extraction and integration. Hence, with web resources proliferation on the web, referencing through the uncertain web has become increasingly difficult. The traditional techniques used for the classical web could not handle uncertain navigation. Generally, it's implicitly represented, decided randomly, or even neglected. Harnessing these uncertain resources to their full potential in order to handle the uncertain navigation, raises major challenges that relate to each phase of their life cycle: creation, representation, and navigation. In this article, we establish a probabilistic approach to model and interpret uncertain web resources. We present operators to compute response uncertainty. Finally, we create algorithms in order to validate resources and achieve uncertain hypertext navigation.

Thousands of examining eyes: credibility, authority and validity in biodiversity citizen science data production

PurposeThe purpose of this study is to contribute with knowledge about how valid research data in biodiversity citizen science are produced through information practices and how notions of credibility and authority emerge from these practices.Design/methodology/approachData were collected through an empirical, interview-based study of the information practices of 15 participants active in the vicinity of the Swedish biodiversity citizen science information system Artportalen. Interview transcripts were analysed abductively and qualitatively through a coding scheme by working back and forth between theory and data. Values of credibility, authority and validity of research data were unfolded through a practice-oriented perspective to library and information studies by utilising the theoretical lens of boundary objects.FindingsNotions of credibility, authority and validity emerge through participant activities of transforming species observations to data, supplementing reports with objects of trust, augmenting identification through authority outreach and assessing credibility via peer monitoring. Credibility, authority and validity of research data are shown to be co-constructed in a distributed fashion by the participants and the information system.Originality/valueThe article extends knowledge about information practices in emerging, heterogeneous scholarly settings by focussing on the complex co-construction of credibility, authority and validity in relation to data production.

Square Kilometre Array Low Atomic commercial off-the-shelf correlator and beamformer

The Square Kilometre Array Low is a next generation radio telescope, consisting of 512 antenna stations spread over 65 km, to be built in Western Australia. The correlator and beamformer (CBF) design is central to the telescope signal processing. CBF receives 6 Tera-bits-per-second (Tbps) of station data continuously and processes it in real time with a compute load of 2 Peta-operations-per-second (Pops). The correlator calculates up to 22 million cross products between all pairs of stations, whereas the beamformers (BFs) coherently sum station data to form more than 500 beams. The output of the correlator is up to 7 Tbps, and the BF 2 Tbps. The design philosophy, called “Atomic COTS,” is based on commercial off-the-shelf (COTS) hardware. Data routing is implemented in network switches programmed using the Programming Protocol-Independent Packet Processors (P4) language and the signal processing occurs in COTS field-programmable gate array (FPGA) cards. The P4 language allows routing to be determined from the metadata in the Ethernet packets from the stations. That is, metadata describing the contents of the packet determines the routing. Each FPGA card inputs a fraction of the overall bandwidth for all stations and then implements the processing needed to generate complete science data products. Generation of complete science products in a single FPGA is named here as Atomic processing. A Tango distributed control system configures the multitude of processing modes as well as maintaining the overall health of the CBF system hardware. The resulting 6 Tbps in and 9 Tbps out, 2 Pops Atomic COTS network attached accelerator occupies five racks and consumes 60 kW.

CHILES. VII. Deep Imaging for the CHILES Project, an SKA Prototype

Abstract Radio astronomy is undergoing a renaissance, as the next generation of instruments provides a massive leap forward in collecting area and therefore raw sensitivity. However, to achieve this theoretical level of sensitivity in the science data products, we need to address the much more pernicious systematic effects, which are the true limitation. These become all the more significant when we consider that much of the time used by survey instruments, such as the Square Kilometre Array (SKA), will be dedicated to deep surveys. CHILES is a deep H i survey of the COSMOS field, with 1000 hr of Very Large Array time. We present our approach for creating the image cubes from the first epoch, with discussions of the methods and quantification of the data quality from 946 to 1420 MHz—a redshift range of 0.5−0. We lay out the problems we had to solve and describe how we tackled them. These are important because CHILES is the first deep wide-band multiepoch H i survey and has relevance for ongoing and future surveys. We focus on the accumulated systematic errors in the imaging, as the goal is to deliver a high-fidelity image that is only limited by the random thermal errors. To understand and correct these systematic effects, we ideally manage them in the domain in which they arise, and that is predominately the visibility domain. CHILES is a perfect test bed for many of the issues we can expect for deep imaging with the SKA or ngVLA, and we discuss the lessons we have learned.

Contributions of Iranian Journal of Medical Sciences (IJMS) during the COVID-19 Pandemic.

Since late 2019, the world and since early 2020, Iran has been experiencing a catastrophic pandemic of the coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).1 This fatal virus has a high potential for person-to-person transmission; therefore, this deadly outbreak has caused massive job losses, various psychiatric problems, and increasing difficulties for all businesses worldwide.2-5 Production of scientific data and its timely dissemination are the essential elements of an effective response to any crisis including the current pandemic. The current study aimed to determine the early contributions of the Iranian Journal of Medical Sciences (IJMS) during the COVID-19 pandemic in 2020. We retrieved all the IJMS publications in 2020 and divided the published articles into three main categories: clinical sciences, basic sciences, and editorials. We also identified and highlighted the studies related to COVID-19.

What is the Thermal Conductivity of Copper? The Production of a Fact Through Scientific Forgetting

AbstractWhat is the thermal conductivity of copper? This straightforward question leads to a fascinating instance of the production of scientific facts through documentation practices. Ho, Powell and Liley's 1974 The Thermal Conductivity of the Elements: A Comprehensive Review is examined as an artifact of scientific reference data production, and its answer to the initial question is traced to modern‐day search engine results. A short history of the Center that produced the book and some initial research into its authors is provided.Kuhn's concepts of normal science and normic lexical structures are utilized to clarify the Comprehensive Review's functioning within the broader scientific fields in which it is utilized. Bowker's concepts of memory practices and the jussive Archive help identify the forgetting embedded in the production of reference data, producing what Star called global certainty. Far from impugning the internal validity of these scientific facts, this forgetting is shown to be licensed by scientific rigor.This paper presents a novel historically informed investigation of how documentation practices produce scientific facts, and connect these activities to modern‐day knowledge graph information retrieval. The theoretical analyses provided show how scientifically licensed forgetting is a key mechanism of fact production, what Hayles termed constrained constructivism.