462 research outputs found
Requirements engineering for explainable systems
Information systems are ubiquitous in modern life and are powered by evermore complex algorithms that are often difficult to understand. Moreover, since systems are part of almost every aspect of human life, the quality in interaction and communication between humans and machines has become increasingly important. Hence the importance of explainability as an essential element of human-machine communication; it has also become an important quality requirement for modern information systems.
However, dealing with quality requirements has never been a trivial task. To develop quality systems, software professionals have to understand how to transform abstract quality goals into real-world information system solutions. Requirements engineering provides a structured approach that aids software professionals in better comprehending, evaluating, and operationalizing quality requirements. Explainability has recently regained prominence and been acknowledged and established as a quality requirement; however, there is currently no requirements engineering recommendations specifically focused on explainable systems.
To fill this gap, this thesis investigated explainability as a quality requirement and how it relates to the information systems context, with an emphasis on requirements engineering. To this end, this thesis proposes two theories that delineate the role of explainability and establish guidelines for the requirements engineering process of explainable systems. These theories are modeled and shaped through five artifacts. These theories and artifacts should help software professionals 1) to communicate and achieve a shared understanding of the concept of explainability; 2) to comprehend how explainability affects system quality and what role it plays; 3) in translating abstract quality goals into design and evaluation strategies; and 4) to shape the software development process for the development of explainable systems.
The theories and artifacts were built and evaluated through literature studies, workshops, interviews, and a case study. The findings show that the knowledge made available helps practitioners understand the idea of explainability better, facilitating the creation of explainable systems. These results suggest that the proposed theories and artifacts are plausible, practical, and serve as a strong starting point for further extensions and improvements in the search for high-quality explainable systems
Airborne study of a multi-layer aerosol structure in the eastern Mediterranean observed with the airborne polarized lidar ALEX during a STAAARTE campaign (7 June 1997)
We present a case study of tropospheric aerosol transport in the eastern Mediterranean, based on airborne measurements obtained south of Greece on 7 June 1997. Airborne observations (backscattering lidar at 0.532 <font face='Symbol'>m</font>m with polarization measurements, in situ particle counters/sizers, and standard meteorological measurements) are complemented by monitoring with Meteosat visible and infrared images and a ground-based sun-photometer, air-mass back-trajectory computations, and meteorological analyses. As already observed from ground-based lidars in the Mediterranean region, the vertical structure of the lower troposphere appears complex, with a superposition of several turbid layers from the surface up to the clean free troposphere which is found here above 2 to 4 km in altitude. The aircraft observations also reveal an important horizontal variability. We identify the presence of depolarising dust from northern Africa in the most elevated turbid layer, which is relatively humid and has clouds embedded. The lowermost troposphere likely contains pollution water-soluble aerosols from eastern continental Greece, and an intermediate layer is found with a probable mixture of the two types of particles. The column optical depth at 0.55 <font face='Symbol'>m</font>m estimated from Meteosat is in the range 0.15-0.35. It is used to constrain the aerosol backscattering-to-extinction ratio needed for the backscattering lidar data inversion. The column value of 0.017 sr <sup>-1</sup> is found applicable to the various aerosol layers and allows us to derive the aerosol extinction vertical profile. The aerosol extinction coefficient ranges from 0.03 km<sup>-1</sup> in the lower clean free troposphere to more than 0.25 km<sup>-1</sup> in the marine boundary layer. Values are <0.1 km<sup>-1</sup> in the elevated dust layer but its thickness makes it dominate the aerosol optical depth at some places
Explainability as a non-functional requirement: challenges and recommendations
Software systems are becoming increasingly complex. Their ubiquitous presence makes users more dependent on their correctness in many aspects of daily life. As a result, there is a growing need to make software systems and their decisions more comprehensible, with more transparency in software-based decision making. Transparency is therefore becoming increasingly important as a non-functional requirement. However, the abstract quality aspect of transparency needs to be better understood and related to mechanisms that can foster it. The integration of explanations into software has often been discussed as a solution to mitigate system opacity. Yet, an important first step is to understand user requirements in terms of explainable software behavior: Are users really interested in software transparency and are explanations considered an appropriate way to achieve it? We conducted a survey with 107 end users to assess their opinion on the current level of transparency in software systems and what they consider to be the main advantages and disadvantages of embedded explanations. We assess the relationship between explanations and transparency and analyze its potential impact on software quality. As explainability has become an important issue, researchers and professionals have been discussing how to deal with it in practice. While there are differences of opinion on the need for built-in explanations, understanding this concept and its impact on software is a key step for requirements engineering. Based on our research results and on the study of existing literature, we offer recommendations for the elicitation and analysis of explainability and discuss strategies for the practice. © 2020, The Author(s)
Explainable software systems: from requirements analysis to system evaluation
The growing complexity of software systems and the influence of software-supported decisions in our society sparked the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. Accordingly, software engineers need means to assist them in incorporating this NFR into systems. This requires an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. However, explainability is currently under-researched in the domain of requirements engineering, and there is a lack of artifacts that support the requirements engineering process and system design. In this work, we remedy this deficit by proposing four artifacts: a definition of explainability, a conceptual model, a knowledge catalogue, and a reference model for explainable systems. These artifacts should support software and requirements engineers in understanding the definition of explainability and how it interacts with other quality aspects. Besides that, they may be considered a starting point to provide practical value in the refinement of explainability from high-level requirements to concrete design choices, as well as on the identification of methods and metrics for the evaluation of the implemented requirements
Explainable software systems: from requirements analysis to system evaluation
The growing complexity of software systems and the influence of software-supported decisions in our society sparked the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. Accordingly, software engineers need means to assist them in incorporating this NFR into systems. This requires an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. However, explainability is currently under-researched in the domain of requirements engineering, and there is a lack of artifacts that support the requirements engineering process and system design. In this work, we remedy this deficit by proposing four artifacts: a definition of explainability, a conceptual model, a knowledge catalogue, and a reference model for explainable systems. These artifacts should support software and requirements engineers in understanding the definition of explainability and how it interacts with other quality aspects. Besides that, they may be considered a starting point to provide practical value in the refinement of explainability from high-level requirements to concrete design choices, as well as on the identification of methods and metrics for the evaluation of the implemented requirements
Comparison of cloud statistics from spaceborne lidar systems
The distribution of clouds in a vertical column is assessed on the global scale through analysis of lidar measurements obtained from three spaceborne lidar systems: LITE (Lidar In-space Technology Experiment, NASA), GLAS (Geoscience Laser Altimeter System, NASA), and CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization). Cloud top height (CTH) is obtained from the LITE profiles based on a simple algorithm that accounts for multilayer cloud structures. The resulting CTH results are compared to those obtained by the operational algorithms of the GLAS and CALIOP instruments. Based on our method, spaceborne lidar data are analyzed to establish statistics on the cloud top height. The resulting columnar results are used to investigate the inter-annual variability in the lidar cloud top heights. Statistical analyses are performed for a range of CTH (high, middle, low) and latitudes (polar, middle latitude and tropical). Probability density functions of CTH are developed. Comparisons of CTH developed from LITE, for 2 weeks of data in 1994, with ISCCP (International Satellite Cloud Climatology Project) cloud products show that the cloud fraction observed from spaceborne lidar is much higher than that from ISCCP. Another key result is that ISCCP products tend to underestimate the CTH of optically thin cirrus clouds. Significant differences are observed between LITE-derived cirrus CTH and both GLAS and CALIOP-derived cirrus CTH. Such a difference is due primarily to the lidar signal-to-noise ratio that is approximately a factor of 3 larger for the LITE system than for the other lidars. A statistical analysis for a full year of data highlights the influence of both the Inter-Tropical Convergence Zone and polar stratospheric clouds
Aerosol chemical and optical properties over the Paris area within ESQUIF project
Aerosol chemical and optical properties are extensively investigated for the first time over the Paris Basin in July 2000 within the ESQUIF project. The measurement campaign offers an exceptional framework to evaluate the performances of the chemistry-transport model CHIMERE in simulating concentrations of gaseous and aerosol pollutants, as well as the aerosol-size distribution and composition in polluted urban environments against ground-based and airborne measurements. A detailed comparison of measured and simulated variables during the second half of July with particular focus on 19 and 31 pollution episodes reveals an overall good agreement for gas-species and aerosol components both at the ground level and along flight trajectories, and the absence of systematic biases in simulated meteorological variables such as wind speed, relative humidity and boundary layer height as computed by the MM5 model. A good consistency in ozone and NO concentrations demonstrates the ability of the model to reproduce the plume structure and location fairly well both on 19 and 31 July, despite an underestimation of the amplitude of ozone concentrations on 31 July. The spatial and vertical aerosol distributions are also examined by comparing simulated and observed lidar vertical profiles along flight trajectories on 31 July and confirm the model capacity to simulate the plume characteristics. The comparison of observed and modeled aerosol components in the southwest suburb of Paris during the second half of July indicates that the aerosol composition is rather correctly reproduced, although the total aerosol mass is underestimated by about 20%. The simulated Parisian aerosol is dominated by primary particulate matter that accounts for anthropogenic and biogenic primary particles (40%), and inorganic aerosol fraction (40%) including nitrate (8%), sulfate (22%) and ammonium (10%). The secondary organic aerosols (SOA) represent 12% of the total aerosol mass, while the mineral dust accounts for 8%. The comparison demonstrates the absence of systematic errors in the simulated sulfate, ammonium and nitrates total concentrations. However, for nitrates the observed partition between fine and coarse mode is not reproduced. In CHIMERE there is a clear lack of coarse-mode nitrates. This calls for additional parameterizations in order to account for the heterogeneous formation of nitrate onto dust particles. Larger discrepancies are obtained for the secondary organic aerosols due to both inconsistencies in the SOA formation processes in the model leading to an underestimation of their mass and large uncertainties in the determination of the measured aerosol organic fraction. The observed mass distribution of aerosols is not well reproduced, although no clear explanation can be given
Observing the Forest Canopy with a New Ultra-Violet Compact Airborne Lidar
We have developed a new airborne UV lidar for the forest canopy and deployed it in the Landes forest (France). It is the first one that: (i) operates at 355 nm for emitting energetic pulses of 16 mJ at 20 Hz while fulfilling eye-safety regulations and (ii) is flown onboard an ultra-light airplane for enhanced flight flexibility. Laser footprints at ground level were 2.4 m wide for a flying altitude of 300 m. Three test areas of ∼500 × 500 m2 with Maritime pines of different ages were investigated. We used a threshold method adapted for this lidar to accurately extract from its waveforms detailed forest canopy vertical structure: canopy top, tree crown base and undergrowth heights. Good detection sensitivity enabled the observation of ground returns underneath the trees. Statistical and one-to-one comparisons with ground measurements by field foresters indicated a mean absolute accuracy of ∼1 m. Sensitivity tests on detection threshold showed the importance of signal to noise ratio and footprint size for a proper detection of the canopy vertical structure. This UV-lidar is intended for future innovative applications of simultaneous observation of forest canopy, laser-induced vegetation fluorescence and atmospheric aerosols
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