Independent Software Research Articles

Left atrial strain evaluation and prognostic value in constrictive pericarditis patients undergoing pericardiectomy

Abstract Background Left Atrial (LA) phasic volumes analyses is flawed with geometrical assumption requiring high endocardial border definition. LA strain analysis is an emergent technique that overcome some of these technical limitations. Prior studies of LA mechanics in pericardiectomy patients found improvement in LA strain at follow-up and manifested as symptomatic improvement, however their relationships with survival have not been investigated. Purpose We assessed LA strain before and after pericardiectomy and its association with all- cause mortality. Methods Consecutive patients with constrictive pericarditis who underwent pericardiectomy from 2000–2017 were retrospectively analyzed, analyzing pre-operative and post-operative (at 12 months) echocardiography. Exclusion criteria included atrial fibrillation, previous left sided valve surgery, concomitant valvular surgery at the index pericardiectomy, more than mild left sided valvulopathy and poor echocardiographic windows. Strain analyses was performed with Vector velocity imaging independent software. Univariate and multivariable analyses were utilized to identify factors associated with reduced survival. Results Amongst 190 patients included in the analyses, mean age was 58.5±12.7 years and 37 (19.5%) were female. The etiology of constriction was deemed idiopathic in 61.6% of the cases, median time interval surgery-postoperative echo was 67 days (IQR 6, 312 days). During median follow up of 3.3 years (IQR 0.73, 5.9 years) there were 37 deaths. After surgery, there was a significant decrease in LA reservoir, conduit and regional wall strains. (Table 1). Multivariable analysis demonstrated that postoperative 4C AL strain reservoir was independently associated with all-cause mortality (Table 2). Conclusions In pericardiectomy patients, postoperative 4C LA strain reservoir is independently associated with all-cause mortality. Perhaps, compensatory changes of septal and antero-posterior walls during constriction explain why after surgery these walls become less dynamic, negatively impacting the overall function. Overall, LA quantification and strains may become a useful clinical tool for risk stratification in pericardiectomy patients Funding Acknowledgement Type of funding sources: None. Table 1. Left atrial variables.Table 2. All-cause mortality predictors

Software Design of a Data Acquisition System for the Hydraulic Fracturing Experiment of Rock at Tongkuangyu Copper Mine

To cooperate with the research on the fragmentation pre-conditioning technology of large hard rock in natural caving mining, we perform a large flow hydraulic fracturing test in Tongkuangyu Copper Mine to investigate the relationship between the occurrence and expansion of fractures in ore bodies and the pressure and flow of water injection. Five sensors of four different types are used in the test. Each sensor uses independent acquisition software. The operation is cumbersome and complex, and data synchronization is difficult and can be easily lost. Therefore, an integrated data acquisition software is needed. The pressure sensor used in the test adopts a non-standard communication protocol, which cannot be used in secondary development by configuration software. Thus, a primary development under the Windows platform using C++ is adopted. The data acquisition module is developed and deployed in background service mode and automatically runs after the acquisition computer OS started. Each communication link establishes an independent data read thread, which reads and analyses the data stream according to the protocol and pushes it to the data processing thread. Such a thread saves the data and provides data service to the data display unit through a TCP/IP service port. All threads in the data acquisition module are synchronized by event signals, and the data read threads have high priority in them to avoid data loss. Multiple data display units are allowed to be connected to the data acquisition module at the same time, which is conducive to the coordination among the field staff. The data display unit shows the field pressure, flow, temperature, and water level. Key data are also developed using multi-thread technology to keep a friendly operation. Such data can be deployed in any computer connected with the acquisition module to assist the staff in performing any operation in the test. Through the field work in a complex environment, this software for data acquisition system can manage types of sensors, with flexible configuration, reliable operation, and convenient expansion and provide further support for the field investigation work.

Alteration in surface roughness of reciprocating endodontic instruments

Background: Surface roughness is one of the most important characteristics of endodontic instruments, correlating to instrument fracture. The purpose of this study was to measure the surface roughness values of these instruments before and after resin root canal preparation without previous glide path preparation, with the new method. Data was obtained from field emission scanning electron microscopes (FE-SEM) combined with independent ImageJ software (NIH, Bethesda, MD, USA). Methods: A total of 20 simulated J-shape resin blocks with a radius of 4.5 mm, length of 16 mm, and angle of inflection of 600 were chosen and distributed into two equal groups. Each group was prepared by the WaveOne Gold Primary (Dentsply Sirona, Maillefer, Ballaigues, Switzerland) or the Reciproc Blue R25 (VDW, Munich, Germany) instruments, without glide path preparation. Special molds were used to confirm the same areas on the cutting blade at 3 mm and the instruments’ tips were scanned by FE-SEM, at different observed times. The parameters of Ra, Rq, and Rz in each sample were collected using the ImageJ software for analyses. The data was processed using the paired t-test with a significance level of 0.05. Results: Right after the first resin canal instrumentation, the surface roughness parameters of the two reciprocating investigated instruments were decreased. Conclusions: The FE-SEM images processed using the ImageJ software offered a trustworthy and suitable method for assessment of the NiTi endodontic file surface roughness.

Edge Strategies in Industry: Overview and Challenges

This paper discusses some details from the 2020 NetSoft conference DEP panel. This panel consisted of industry experts, and as such the perspective presented here is biased with an industry view of Edge Computing. In sharing this discussion and further expanding on the discussion in this paper the hope is to provide the research community with guidance on opportunities to advance and possibly accelerate the rate of Edge adoption (Tiwari et al., 2021). There is no avoiding the Edge discussion; today in industry Communication Service Providers see this is an avenue to monetize their 5G investment, the cloud providers, also known as the `hyperscalers', see this as providing an ingress point into new markets, and finally enterprises themselves see this as an opportunity to modernize and gain business advantages through insights and better process management. Two U.S. based mobile network operators have edge portfolios (AT&T Edge Solutions, 2021 and Verizon, 2021). Many examples exist around the globe with other network service providers, an exhaustive list would consume this paper. In addition, 2020 saw Microsoft acquire two Independent Software Vendors (ISV's), Metaswitch and Affirmed. This clearly is intended to bring edge capability into their Azure product line.

Molly McCarthy, MBA, BSN, RN, RN-BC

Molly McCarthy, MBA, BSN, RN, RN-BC

Effect of 8 Weeks of Endurance Training on S6K1 and 4EBP1 Proteins Content in the Left Ventricle of the Heart of Diabetic Rats Induced by Streptozotocin and Nicotinamide

Introduction: Physiological hypertrophy of the heart is dependent on cellular pathways and important proteins such as the ribosomal protein S6 kinase beta-1 (S6K1) and eukaryotic translation initiation factor 4E-binding protein-1 (4EBP1). The aim of this study was to investigate the effect of 8 weeks of endurance training on ribosomal protein S6 kinase beta-1 and eukaryotic translation initiation factor 4E-binding protein-1 in the left ventricle of the heart of diabetic rats induced by streptozotocin and nicotinamide. Methods: In this experimental study, 12 two-month-old Sprague-Dawley rats with a mean weight of 270±20 g were selected. After diabetic induction with streptozotocin and Nicotinamide, rats were randomly assigned to two groups, training diabetic and control diabetic (6 heads in group each). The training group performed endurance training 4 days a week for 8 weeks according to the training program; while the control group did not have any training program. Also, rats did not receive any insulin treatment during the study period. Protein content was measured using the Western blot method. The Independent t-test and SPSS software version 16 was used to analyze the data. Results: Eight weeks of endurance training resulted in a significant increase in S6K1 protein content (P=0.001); There was also a significant increase in 4EBP1 protein content in the endurance training group compared to the control (P=0.0001). Conclusion: Eight weeks of endurance training resulted in a significant increase in S6K1 and 4EBP1 proteins in the hearts of diabetic subjects; activation of these proteins may regulate protein synthesis and cardiac hypertrophy.

A CALCULATION METHOD OF ECOSYSTEM SERVICE VALUE BASED ON PRODUCT OF NATIONAL GEOGRAPHIC CONDITIONS MONITORING IN CHINA

Abstract. By 2015, Chinese government had completed the project of China's First National Geographic Conditions Census. In this project, high resolution land cover product all over the country had been generated, and would be updated continuously every year. On the basis of this excellent data source, a big data calculating method of land’s ecosystem service value was proposed, in which many other remote sensing information were used too, such as EVI (Enhanced Vegetation Index), NPP (Net Primary Productivity), vegetation growing season data derived from MODIS product. It analyzed the characters of data type, data time phase, and data structure for all the remote sensing information, also the big data’s engendering background and process. A revised ecosystem service value assessment model was used for calculating. Combining the classification system of terrestrial ecosystem in China and the equivalent value factor per unit ecosystem area, the big data calculating algorithm was designed. Shiyan city, Hubei province, China was selected as the study area for validating the calculating method. The results showed that the total ecosystem service value in Shiyan city in 2015 was 1.97 × 1011 CNY, and the per capita ecosystem service value was 5.69 × 104 CNY. Specially, forest supplied the most ecosystem service value which accounted for 78.54 %, followed by water, grassland, farmland, and desert. The research shows that on the basis of multi-source of remote sensing information mainly the high resolution land cover product obtained in the project of China's First National Geographic Conditions Census, high-precision quantification and spatialization ecosystem service value can be calculated and obtained; multi scale spatial display of the calculating results could be achieved to meet different spatial scaling demands; the big data calculating algorithm has solved the problems of design and computation of structured and unstructured big data computing models; the independent research and development software has solved the problem of software requirements, and the operational efficiency and performance can meet the calculating needs.

Suspect Face Depiction and Recognition

In forensic science, it's seen that hand-drawn face sketches are still very inadequate and time-consuming when it involves using them with the newest technologies used for the identification of criminals. Through this paper, we introduce an independent software that allows users to make composites suspect face sketch of the suspect without the assistance of forensic artists using the drag-drop feature inside the software and automatically match the suspect face sketch with the police database much faster and efficiently using deep learning and cloud infrastructure.

How to Create a Software Ecosystem? A Partnership Meta-Model and Strategic Patterns

Large keystone organizations use partnership models to manage their software ecosystem partners. Although several partnership models have been developed by platform owners, smaller companies willing to create a new ecosystem may experience difficulties to define the appropriate features of partnership models when switching from an independent software product to an ecosystem. This study proposes a partnership meta-model and four strategic patterns to operationalize it. We adopted the Design Science Research (DSR) method. The partnership meta-model was built in the first cycle of DSR, using a Systematic Mapping Study, and validated through case studies of SAP, Eclipse, and Microsoft Azure ecosystems. In the second cycle of DSR, the strategic patterns were defined through a Multivocal Literature Review and validated by using interviews with professionals. The meta-model presents the key characteristics to define partnership models for emerging software ecosystems. The strategic patterns aim to operationalize the meta-model and, consequently, assist the keystone in defining the features that the partnership model will have and select suitable strategies. The meta-model and the strategic patterns help managers creating and evolving software ecosystems from a software product considering the impact of that transition on the partnership model.

Combined automated screening for age-related macular degeneration and diabetic retinopathy in primary care settings.

Background:Age-related macular degeneration (AMD) and diabetic retinopathy (DR) are among the leading causes of blindness in the United States and other developed countries. Early detection is the key to prevention and effective treatment. We have built an artificial intelligence-based screening system which utilizes a cloud-based platform for combined large scale screening through primary care settings for early diagnosis of these diseases.Methods:iHealthScreen Inc., an independent medical software company, has developed automated AMD and DR screening systems utilizing a telemedicine platform based on deep machine learning techniques. For both diseases, we prospectively imaged both eyes of 340 unselected non-dilated subjects over 50 years of age. For DR specifically, 152 diabetic patients at New York Eye and Ear faculty retina practices, ophthalmic and primary care clinics in New York city with color fundus cameras. Following the initial review of the images, 308 images with other confounding conditions like high myopia and vascular occlusion, and poor quality were excluded, leaving 676 eligible images for AMD and DR evaluation. Three ophthalmologists evaluated each of the images, and after adjudication, the patients were determined referrable or non-referable for AMD DR. Concerning AMD, 172 were labeled referable (intermediate or late), and 504 were non-referable (no or early). Concurrently, regarding DR, 33 were referable (moderate or worse), and 643 were non-referable (none or mild). All images were uploaded to iHealthScreen’s telemedicine platform and analyzed by the automated systems for both diseases. The system performances are tested on per eye basis with sensitivity, specificity, accuracy, and kappa scores with respect to the professional graders.Results:In identifying referable DR, the system achieved a sensitivity of 97.0% and a specificity of 96.3%, and a kappa score of 0.70 on this prospective dataset. For AMD, the sensitivity was 86.6%, the specificity of 92.1%, and a kappa score of 0.76.Conclusions:The AMD and DR screening tools achieved excellent performance operating together to identify two retinal diseases prospectively in mixed datasets, demonstrating the feasibility of such tools in the early diagnosis of eye diseases. These early screening tools will help create an even more comprehensive system capable of being trained on other retinal pathologies, a goal within reach for public health deployment.

Defending IEEE Software Standards in Federal Criminal Court

IEEE's 1012 Standard for independent software and hardware verification and validation (IV&V) is under attack in U.S. federal criminal court. As software spreads through the criminal legal system, scientists, engineers, and IEEE have an essential role in ensuring courts understand and respect IEEE 1012 and IV&V. If scientists, engineers, and IEEE do not engage, courts will continue to allow unreliable scientific evidence to deprive people of their life and liberty.

Basin-Scale 3D Sedimentary Modelling: An Approach to Subdivide Baltic Sea Onshore Sediments for Land use and Construction

Understanding the local stratigraphy and geometry of sediment units is necessary for successful 3D modelling and the prediction of ground behaviour and engineering-geological properties for urban land use and construction. A detailed 3D model of the main sediment units for the Rastaala basin in southern coastal Finland was constructed, combining a conceptual geological model and information from local drill-hole logs and geotechnical drilling. The 3D modelling was based on a cross-section approach, where sediment units were defined on the basis of lithological boundaries that are of major geotechnical importance for land use and construction. The conceptual geological model was based on a sequence of events that characterize the late- and postglacial evolution of the Rastaala basin. The present study combines the allostratigraphy and lithostratigraphy of unconsolidated glacial, late-and postglacial sediment units in southern coastal Finland. It also investigates the appearance and distribution of sediment units in the Rastaala basin and compares modelling and visualization results for unit surfaces and solids using two independent modelling software packages. Finally, information on the geotechnical properties of different sediment units in the Rastaala basin is provided so that they can be applied to other onshore regions with similar geological settings in the coastal Baltic Sea Basin.

Research on Current Situation of Quality Management of Artificial Intelligence Medical Device Enterprises

To understand the current situation of artificial intelligence production enterprise quality management system, so as to provide reference basis for the research and standardization of Artificial Intelligence Medical Device (AIMD) product quality management. Based on YY/T 0287-2017 Medical Device Quality Management System for Regulatory Requirements, Medical Equipment Production and the Quality Control Standard for Independent Software Appendix and Xavier GMLP report, the relevant factors were screened and the questionnaire was designed by combining expert consultation and literature review. Then, a total of 32 representative AIMD enterprises were invited to fill in the questionnaire. Descriptive statistical analysis was performed on the data results using Excel 2016. Through in-depth analysis of the four themes in product planning and design, result output, product quality control and product change, it was found that it was necessary for enterprises participating in the survey to improve the quality management system of AIMD products to different degrees. This study is the first time to systematically investigate the status quo of quality management of AIMD enterprises. The result will be useful for the establishment and continuous improvement of product quality management system. It will also provide a reference for the research of AIMD product quality management and the establishment of the standard.

INVESTMENTS IN THE AREA OF CYBERSECURITY IN RUSSIANFEDERATION BETWEEN 2018 AND 2022

The study presents the level of financial investments made between 2018 and 2022 byRussian Federation authorities in the sector related to cybersecurity of the state.The text covers the following areas: expenses incurred for cybersecurity, projects"Digital economy" and "Independent Internet", funds to support Russian programmers,data security in rail transport, radio and TV, biometric security in passports,participation of commercial entities in the government program "Digital economy",expenses for independent test centers, software and hardware, as well as filteringinternet traffic among children and detecting any malicious activities related to it.

Периодограммная оценка спектральной плотности мощности на основе бинарно-знакового стохастического квантования сигналов с использованием оконных функций

Spectral analysis of signals is used as one of the main methods for studying systems and objects of various physical natures. Under conditions of a priori statistical uncertainty, the signals are subject to random changes and noise. Spectral analysis of such signals involves the estimation of the power spectral density (PSD). One of the classical methods for estimating PSD is the periodogram method. The algorithms that implement this method in digital form are based on the discrete Fourier transform. Digital multiplication operations are mass operations in these algorithms. The use of window functions leads to an increase in the number of these operations. Multiplication operations are among the most time consuming operations. They are the dominant factor in determining the computational capabilities of an algorithm and determine its multiplicative complexity. The paper deals with the problem of reducing the multiplicative complexity of calculating the periodogram estimate of the PSD using window functions. The problem is solved based on the use of binary-sign stochastic quantization for converting a signal into digital form. This two-level signal quantization is carried out without systematic error. Based on the theory of discrete-event modeling, the result of a binary-sign stochastic quantization in time is considered as a chronological sequence of significant events determined by the change in its values. The use of a discrete-event model for the result of binary-sign stochastic quantization provided an analytical calculation of integration operations during the transition from the analog form of the periodogram estimation of the SPM to the mathematical procedures for calculating it in discrete form. These procedures became the basis for the development of a digital algorithm. The main computational operations of the algorithm are addition and subtraction arithmetic operations. Reducing the number of multiplication operations decreases the overall computational complexity of the PSD estimation. Numerical experiments were carried out to study the algorithm operation. They were carried out on the basis of simulation modeling of the discrete-event procedure of binary-sign stochastic quantization. The results of calculating the PSD estimates are presented using a number of the most famous window functions as an example. The results obtained indicate that the use of the developed algorithm allows calculating periodogram estimates of PSD with high accuracy and frequency resolution in the presence of additive white noise at a low signal-to-noise ratio. The practical implementation of the algorithm is carried out in the form of a functionally independent software module. This module can be used as a part of complex metrologically significant software for operational analysis of the frequency composition of complex signals.

Impact of Increased Travel Speed of a Transportation Set on the Dynamic Parameters of a Mine Suspended Monorail

The method of increasing the efficiency of using one of the most common means of auxiliary transport in underground coal mines—suspended monorails—is presented. Increase of velocity is one of the key parameters to improve the efficiency and economical effect related with the underground auxiliary transport. On the other hand, increasing the velocity results in bigger value of force acting on the suspended monorail route and its suspensions. The most important issue during increasing the velocity is ensuring the required safety for the passengers and not overloading the infrastructure. In order to analyze how increasing velocity influences the level of loads of the route suspension and the steel arch loads, the computational model of suspended monorail was developed. The computational model included both the physical part (embedded in the program environment based on the Multi-Body System method) and the components of the monorail control system. Two independent software environments were cooperating with each other through the so-called co-simulation. This model was validated on the base of results obtained on the test stand. Then, the numerical simulations of emergency braking with different values of velocity were conducted, which was not possible with the use of physical objects. The presented study can be used by the suspended monorail’s producers during the designing process, and leads to increase the safety on underground transportation routes.

Automated estimation of ischemic core prior to thrombectomy: comparison of two current algorithms.

Endovascular thrombectomy (EVT) improves clinical outcomes in ischemic stroke with large vessel occlusion. Clinical benefits are inversely proportional to size of the pre-treatment ischemic core. This study compared estimated ischemic core volumes by two different CT perfusion (CTP) automated algorithms to the gold standard follow-up infarct volume using diffusion-weighted imaging (DWI) to assess for congruence, and thus eligibility for EVT. Retrospective, single-center cohort study of 102 patients presenting to a comprehensive stroke center between 2012 and 2018. Inclusion criteria were CT perfusion prior to EVT, successful EVT with mTIBI 2b-3 reperfusion, and DWI post-EVT. CTP data were retrospectively processed by two algorithms: "delay and dispersion insensitive deconvolution" (DISD, RAPID software) versus "delay and dispersion corrected single value decomposition" (ddSVD, Mistar software), using commercially available software. Core volumes were compared to follow up DWI using independent software (MRIcron). Agreement between each algorithm and DWI was estimated using Lin's concordance coefficient and analyzed using reduced major axis regression. We included 102 patients. Both algorithms had excellent agreement with DWI (Lin's concordance coefficients: DISD 0.8 (95% CI: 0.73; 0.87), ddSVD 0.92 (95% CI: 0.89; 0.95). Compared to ddSVD (reduced major axis slope = 0.95), DISD exhibited a larger extent of proportional bias (slope = 1.12). The ddSVD algorithm better correlates with DWI follow-up infarct volume than DISD processing. The DISD algorithm overestimated larger ischemic cores which may lead to patient exclusion from thrombectomy based on selection by core volume.

Vendor-independent software shows limited variability in speckle tracking strain measurements on images of different vendors

Abstract Funding Acknowledgements Type of funding sources: None. Background Vendors use proprietary speckle tracking software algorithms for echocardiographic strain measurements, which results in high inter-vendor variability. Little is known about potential advantages or disadvantages of using vendor-independent software in clinical practice. Purpose We therefore investigated the reproducibility, accuracy, and ability to identify scar of strain measurements on images from different vendors by using a vendor-independent software. Methods A vendor-independent software (TomTec Image Arena) was used to analyze datasets of 63 patients which were obtained on four ultrasound machines from different vendors (GE, Philips, Siemens, Toshiba). We measured the tracking feasibility, inter-vendor bias, the relative and absolute test-re-test variability of strain measurements and their ability to detect scar. Cardiac magnetic resonance delayed enhancement images were used as the reference standard of scar definition. Results Tracking feasibility differed depending on the image source (p < 0.05). Variability of global longitudinal strain (GLS) (Figure 1A) was similar (ANOVA p = 0.124) among the images of different vendors whereas variability of segmental longitudinal strain (SLS) (Figure 1B) showed modest difference (ANOVA- peak systolic strain (PS); p = 0.077, end-systolic strain (ES); p = 0.171, post-systolic strain (PSS); p = 0.020). Relative test-re-test variability of GLS showed no differences (ANOVA p = 0.360). Absolute test-re-test errors of SLS measurements showed modest differences among images of different vendors (ANOVA- PS; p = 0.018, ES; p = 0.001, PSS; p = 0.090). No relevant difference in scar detection capability was observed (Figure 1C). Conclusions Vendor independent software leads to low bias among strain measurements on images from different vendors. Likewise, measurement variability and the ability to identify scar becomes similar. Our findings suggest that a vendor independent speckle tracking software could help to overcome inter-vendor bias. To which extend such measurements would be more accurate compared to vendor specific software remains to be determined. Abstract Figure 1

Global longitudinal strain and mechanical dispersion at rest in exercise stress echocardiography for detecting obstructive coronary artery disease: a pilot study

Abstract Funding Acknowledgements Type of funding sources: None. BACKGROUND Exercise stress echocardiography (ESE) is a commonly used investigation for risk stratification in coronary artery disease (CAD). The added value of resting indices such as Global Longitudinal Strain (GLS) and Mechanical Dispersion (MD) to detect obstructive CAD is not well established and would be of significant clinical benefit. PURPOSE To evaluate the diagnostic value of GLS and MD at rest and post-exercise during ESE to detect obstructive CAD, defined by angiographic stenosis >70% in any major coronary artery. METHODS Retrospective cohort study of 80 consecutive patients who underwent ESE and had coronary angiography (invasive or CT) within 6 months. Retrospective speckle tracking strain analysis was performed on digitally archived video-loops, using vendor independent software. Data on demographics, medications, outcomes and ESE characteristics were collected and analysed. RESULTS In 49 (61.3%) patients with any CAD >70%, GLS at rest was lower (-13.9% ± 4.2 vs -16.1% ± 5.2, p-value = 0.04), and MD at rest was higher (81ms ± 43 vs 58ms ± 28, p-value = 0.008), when compared to patients without CAD >70%. GLS and MD measured post-exercise were not significantly different between groups. Ejection fraction (EF) and Wall Motion Score Index (WMSI) at rest and post-exercise were not significantly different between groups. A resting GLS cutpoint of -14% had a sensitivity and specificity of 57/68%, comparable to the development of new regional wall motion abnormalities (71/39%) and peak WMSI >1.2 (59/48%). Additionally, in 39 (48.8%) patients who had >70% stenosis in the left anterior descending (LAD) artery, LS in the LAD territory segments was lower (-16.2% ± 4.4 vs -18.3% ± 4.7, p-value = 0.04), when compared to patients without >70% stenosis in the LAD artery. CONCLUSION Resting GLS was lower and MD higher in patients undergoing ESE, who have any CAD >70% compared to patients who do not have any CAD >70%. Resting GLS and MD may increase diagnostic accuracy during ESE to predict obstructive CAD. Further prospective studies evaluating the utility of resting indices to predict functionally significant CAD are required.

Integrating data and analysis technologies within leading environmental research infrastructures: Challenges and approaches

When researchers analyze data, it typically requires significant effort in data preparation to make the data analysis ready. This often involves cleaning, pre-processing, harmonizing, or integrating data from one or multiple sources and placing them into a computational environment in a form suitable for analysis. Research infrastructures and their data repositories host data and make them available to researchers, but rarely offer a computational environment for data analysis. Published data are often persistently identified, but such identifiers resolve onto landing pages that must be (manually) navigated to identify how data are accessed. This navigation is typically challenging or impossible for machines.This paper surveys existing approaches for improving environmental data access to facilitate more rapid data analyses in computational environments, and thus contribute to a more seamless integration of data and analysis. By analysing current state-of-the-art approaches and solutions being implemented by world‑leading environmental research infrastructures, we highlight the existing practices to interface data repositories with computational environments and the challenges moving forward.We found that while the level of standardization has improved during recent years, it still is challenging for machines to discover and access data based on persistent identifiers. This is problematic in regard to the emerging requirements for FAIR (Findable, Accessible, Interoperable, and Reusable) data, in general, and problematic for seamless integration of data and analysis, in particular. There are a number of promising approaches that would improve the state-of-the-art. A key approach presented here involves software libraries that streamline reading data and metadata into computational environments. We describe this approach in detail for two research infrastructures. We argue that the development and maintenance of specialized libraries for each RI and a range of programming languages used in data analysis does not scale well.Based on this observation, we propose a set of established standards and web practices that, if implemented by environmental research infrastructures, will enable the development of RI and programming language independent software libraries with much reduced effort required for library implementation and maintenance as well as considerably lower learning requirements on users. To catalyse such advancement, we propose a roadmap and key action points for technology harmonization among RIs that we argue will build the foundation for efficient and effective integration of data and analysis.