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The dynamics and speed of change in corporate environments have increased. At the front-end of innovation, firms are challenged to evaluate growing amounts of information within shorter time frames in order to stay competitive. Either they spend significant time on structured data analysis, at the risk of delayed market launch, or they follow their intuition, at the risk of not meeting market trends. Both scenarios constitute a significant risk for a firm’s continued existence. Motivated by this, a conceptual model is presented in this paper that aims at remediating these risks. Grounded on design science methodology, it concentrates on previous assessments of innovation search fields. These innovation search fields assist in environmental scanning and lay the foundation for deciding which opportunities to pursue. The model applies a novel AI-based approach, which draws on natural language processing and information retrieval. To provide decision support, the approach includes market-, technology-, and firm-related criteria. This allows us to replace intuitive decision-making by fact-based considerations. In addition, an often-iterative approach for environmental scanning is replaced by a more straightforward process. Early testing of the conceptual model has shown results of increased quality and speed of decision-making. Further testing and feedback is still required to enhance and calibrate the AI-functionality. Applied in business environments, the approach can contribute to remediate fuzziness in early front-end activities, thus helping direct innovation managers to “do the right things”.

The Spectrometer/Telescope for Imaging X-rays (STIX) is the HXR instrument onboard Solar Orbiter designed to observe solar flares over a broad range of flare sizes, between 4-150 keV. We report the first STIX observations of microflares recorded during the instrument commissioning phase in order to investigate the STIX performance at its detection limit. This first result paper focuses on the temporal and spectral evolution of STIX microflares occuring in the AR12765 in June 2020, and compares the STIX measurements with GOES/XRS, SDO/AIA, and Hinode/XRT. For the observed microflares of the GOES A and B class, the STIX peak time at lowest energies is located in the impulsive phase of the flares, well before the GOES peak time. Such a behavior can either be explained by the higher sensitivity of STIX to higher temperatures compared to GOES, or due to the existence of a nonthermal component reaching down to low energies. The interpretation is inconclusive due to limited counting statistics for all but the largest flare in our sample. For this largest flare, the low-energy peak time is clearly due to thermal emission, and the nonthermal component seen at higher energies occurs even earlier. This suggests that the classic thermal explanation might also be favored for the majority of the smaller flares. In combination with EUV and SXR observations, STIX corroborates earlier findings that an isothermal assumption is of limited validity. Future diagnostic efforts should focus on multi-wavelength studies to derive differential emission measure distributions over a wide range of temperatures to accurately describe the energetics of solar flares. Commissioning observations confirm that STIX is working as designed. As a rule of thumb, STIX detects flares as small as the GOES A class. For flares above the GOES B class, detailed spectral and imaging analyses can be performed., Comment: 19 pages, 11 figures

The EU funded the FLARECAST project, that ran from Jan 2015 until Feb 2018. FLARECAST had a R2O focus, and introduced several innovations into the discipline of solar flare forecasting. FLARECAST innovations were: first, the treatment of hundreds of physical properties viewed as promising flare predictors on equal footing, extending multiple previous works; second, the use of fourteen (14) different ML techniques, also on equal footing, to optimize the immense Big Data parameter space created by these many predictors; third, the establishment of a robust, three-pronged communication effort oriented toward policy makers, space-weather stakeholders and the wider public. FLARECAST pledged to make all its data, codes and infrastructure openly available worldwide. The combined use of 170+ properties (a total of 209 predictors are now available) in multiple ML algorithms, some of which were designed exclusively for the project, gave rise to changing sets of best-performing predictors for the forecasting of different flaring levels. At the same time, FLARECAST reaffirmed the importance of rigorous training and testing practices to avoid overly optimistic pre-operational prediction performance. In addition, the project has (a) tested new and revisited physically intuitive flare predictors and (b) provided meaningful clues toward the transition from flares to eruptive flares, namely, events associated with coronal mass ejections (CMEs). These leads, along with the FLARECAST data, algorithms and infrastructure, could help facilitate integrated space-weather forecasting efforts that take steps to avoid effort duplication. In spite of being one of the most intensive and systematic flare forecasting efforts to-date, FLARECAST has not managed to convincingly lift the barrier of stochasticity in solar flare occurrence and forecasting: solar flare prediction thus remains inherently probabilistic., Comment: 67 pages, 14 figures; submitted

Aims. The Spectrometer Telescope for Imaging X-rays (STIX) on Solar Orbiter is a hard X-ray imaging spectrometer, which covers the energy range from 4 to 150 keV. STIX observes hard X-ray bremsstrahlung emissions from solar flares and therefore provides diagnostics of the hottest (⪆10 MK) flare plasma while quantifying the location, spectrum, and energy content of flare-accelerated nonthermal electrons. Methods. To accomplish this, STIX applies an indirect bigrid Fourier imaging technique using a set of tungsten grids (at pitches from 0.038 to 1 mm) in front of 32 coarsely pixelated CdTe detectors to provide information on angular scales from 7 to 180 arcsec with 1 keV energy resolution (at 6 keV). The imaging concept of STIX has intrinsically low telemetry and it is therefore well-suited to the limited resources available to the Solar Orbiter payload. To further reduce the downlinked data volume, STIX data are binned on board into 32 selectable energy bins and dynamically-adjusted time bins with a typical duration of 1 s during flares. Results. Through hard X-ray diagnostics, STIX provides critical information for understanding the acceleration of electrons at the Sun and their transport into interplanetary space and for determining the magnetic connection of Solar Orbiter back to the Sun. In this way, STIX serves to link Solar Orbiter’s remote and in-situ measurements.

The Spectrometer/Telescope for Imaging X-rays (STIX) is a remote sensing instrument on Solar Orbiter that observes the hard X-ray bremsstrahlung emission of solar flares. This paper describes the STIX Aspect System (SAS), a subunit that measures the pointing of STIX relative to the Sun with a precision of $\pm 4''$ , which is required to accurately localize the reconstructed X-ray images on the Sun. The operating principle of the SAS is based on an optical lens that images the Sun onto a plate that is perforated by small apertures arranged in a cross-shaped configuration of four radial arms. The light passing through the apertures of each arm is detected by a photodiode. Variations of spacecraft pointing and of distance from the Sun cause the solar image to move over different apertures, leading to a modulation of the measured lightcurves. These signals are used by ground analysis to calculate the locations of the solar limb, and hence the pointing of the telescope.

In data science, interactive data analysis allows to very efficiently interpret what information is in the data. However, with increasing amounts of data available, the data crunching and data presentation becomes a more complex and resource-demanding task. Array databases allow to mitigate this difficulty by distributing the workload on a cluster. But there are two major challenges. Firstly, they rely on CPUs to process the data. Secondly, it is difficult to represent complex scientific algorithms in terms of native database operations. A way to integrate GPU accelerated algorithms is needed. In this paper, we study and test how to run scientific algorithms on GPUs entirely as native array database operators. We present the implementation of a specific scientific algorithm as exemplary use case. The computation of the Differential Emission Measure (DEM) calculates the distribution of plasma density in the solar corona at specific temperatures. DEM uses image series of the NASA spacecraft Solar Dynamic Observatory (SDO). We stack these images in a 3-dimensional array and process the data on GPUs, distributed in an array database cluster. For our algorithm, we measure a decrease of the overall runtime by a factor of 10700. We discuss different strategies used to minimize the overhead of GPUs and parameters used to scale the array database to a cluster.

The behavior of filaments and prominences during the Solar Cycle is a signature of Sun's activity. It is therefore important to follow their evolution during the cycle, in order to be able to associate it with the various phases of the Solar Cycle as well as with other Solar features or events. The virtual observatory HELIO provides information that can be used for such studies, especially its Heliophysics Feature Catalogue gives a unique access to the description of various features during around one cycle. Features available are: filaments, prominences, photospheric and coronal active regions, coronal radio emission, type III radio bursts, coronal holes and sunspots. Web interfaces allow the user to query data for these features. Useful information can also be shared with other HELIO services, such as Heliophysics Event Catalogue, which provides access to dozens of tables of events such as flares, CMEs, . . .

Context. Solar observatories are providing the world-wide community with a wealth of data, covering large time ranges, multiple viewpoints, and returning large amounts of data. In particular, the large volume of SDO data presents challenges: it is available only from a few repositories, and full-disk, full-cadence data for reasonable durations of scientific interest are difficult to download practically due to their size and download data rates available to most users. From a scientist's perspective this poses three problems: accessing, browsing and finding interesting data as efficiently as possible. Aims. To address these challenges, we have developed JHelioviewer, a visualisation tool for solar data based on the JPEG2000 compression standard and part of the open source ESA/NASA Helioviewer Project. Since the first release of JHelioviewer, the scientific functionality of the software has been extended significantly, and the objective of this paper is to highlight these improvements. Methods. The JPEG2000 standard offers useful new features that facilitate the dissemination and analysis of high-resolution image data and offers a solution to the challenge of efficiently browsing petabyte-scale image archives. The JHelioviewer software is open source, platform independent and extendable via a plug-in architecture. Results. With JHelioviewer, users can visualise the Sun for any time period between September 1991 and today. They can perform basic image processing in real time, track features on the Sun and interactively overlay magnetic field extrapolations. The software integrates solar event data and a time line display. As a first step towards supporting science planning of the upcoming Solar Orbiter mission, JHelioviewer offers a virtual camera model that enables users to set the vantage point to the location of a spacecraft or celestial body at any given time., 13 pages, 12 figures, accepted for publication in Astronomy & Astrophysics

Pydron, a system that bridges the gap between interactive data analysis and scalable computing, enables astronomers to process large datasets with Python without the complexities of managing parallel processing code.

Array databases are well suited for storing and processing large multidimensional data. However, they usually run rather simple operations which only represent single steps of scientific algorithms. A way to run more complex logic is needed. In this paper, we study and test how to run entire scientific algorithms as native array database operators in a SciDB cluster. We present as use case our implementation of an iterative algorithm that reconstructs the distribution of plasma density in the solar corona at specific temperatures. This algorithm uses images series of the NASA spacecraft Solar Dynamic Observatory (SDO), which we stack in a 3-dimensional array. We measure for our use case a decrease of the overall runtime by an order of magnitude. We discuss different parameters used to scale up the array database cluster.

We study the benefits and limits of parallelised Markov chain Monte Carlo (MCMC) sampling in cosmology. MCMC methods are widely used for the estimation of cosmological parameters from a given set of observations and are typically based on the Metropolis–Hastings algorithm. Some of the required calculations can however be computationally intensive, meaning that a single long chain can take several hours or days to calculate. In practice, this can be limiting, since the MCMC process needs to be performed many times to test the impact of possible systematics and to understand the robustness of the measurements being made. To achieve greater speed through parallelisation, MCMC algorithms need to have short autocorrelation times and minimal overheads caused by tuning and burn-in. The resulting scalability is hence influenced by two factors, the MCMC overheads and the parallelisation costs. In order to efficiently distribute the MCMC sampling over thousands of cores on modern cloud computing infrastructure, we developed a Python framework called CosmoHammer which embeds emcee, an implementation by Foreman-Mackey et al. (2012) of the affine invariant ensemble sampler by Goodman and Weare (2010). We test the performance of CosmoHammer for cosmological parameter estimation from cosmic microwave background data. While Metropolis–Hastings is dominated by overheads, CosmoHammer is able to accelerate the sampling process from a wall time of 30 h on a dual core notebook to 16 min by scaling out to 2048 cores. Such short wall times for complex datasets open possibilities for extensive model testing and control of systematics., Astronomy and Computing, 2, ISSN:2213-1337

The Heliophysics Integrated Observatory (HELIO) is a software infrastructure involving a collection of web services, heliospheric data sources (e.g., solar, planetary, etc.), and event catalogues – all of which are accessible through a unified front end. In this paper we use the HELIO infrastructure to perform three case studies based on solar events that propagate through the heliosphere. These include a coronal mass ejection that intersects both Earth and Mars, a solar energetic particle event that crosses the orbit of Earth, and a high-speed solar wind stream, produced by a coronal hole, that is observed in situ at Earth (L1). A ballistic propagation model is run as one of the HELIO services and used to model these events, predicting if they will interact with a spacecraft or planet and determining the associated time of arrival. The HELIO infrastructure streamlines the method used to perform these kinds of case study by centralising the process of searching for and visualising data, indicating interesting features on the solar disk, and finally connecting remotely observed solar features with those detected by in situ solar wind and energetic particle instruments. HELIO represents an important leap forward in European heliophysics infrastructure by bridging the boundaries of traditional scientific domains.

We present a new method to automatically track filaments over the solar disk. The filaments are first detected on Meudon Spectroheliograph H{\alpha} images of the Sun, applying the technique developed by Fuller, Aboudarham, and Bentley (Solar phys. 227, 61, 2005). This technique combines cleaning processes, image segmentation based on region growing, and morphological parameter ex- traction, including the determination of filament skeletons. The coordinates of the skeleton pixels, given in a heliocentric system, are then converted to a more appropriate reference frame that follows the rotation of the Sun surface. In such a frame, a co-rotating filament is always located around the same position, and its skeletons (extracted from each image) are thus spatially close, forming a group of adjacent features. In a third step, the shape of each skeleton is compared with its neighbours using a curve-matching algorithm. This step will permit us to define the probability [P ] that two close filaments in the co-rotating frame are actually the same one observed on two different images. At the end, the pairs of features, for which the corresponding probability is greater than a threshold value, are associated using tracking identification indexes.On a representative sample of filaments, the good agreement between automated and manual tracking confirms the reliability of the technique to be applied on large data sets. Especially, this code is already used in the framework of the Heliophysics Integrated Observatory (HELIO) to populate a catalogue dedicated to solar and heliospheric features (HFC). An extension of this method to others filament observations, and possibly the sunspots, faculae, and coronal holes tracking can be also envisaged.

RHESSI is the sixth in the NASA line of Small Explorer (SMEX) missions and the first managed in the Principal Investigator mode, where the PI is responsible for all aspects of the mission except the launch vehicle. RHESSI is designed to investigate particle acceleration and energy release in solar flares, through imaging and spectroscopy of hard X-ray/gamma-ray continua emitted by energetic electrons, and of gamma-ray lines produced by energetic ions. The single instrument consists of an imager, made up of nine bi-grid rotating modulation collimators (RMCs), in front of a spectrometer with nine cryogenically-cooled germanium detectors (GeDs), one behind each RMC. It provides the first high-resolution hard X-ray imaging spectroscopy, the first high-resolution gamma-ray line spectroscopy, and the first imaging above 100 keV including the first imaging of gamma-ray lines. The spatial resolution is as fine as ~ 2.3 arc sec with a full-Sun (≳ 1°) field of view, and the spectral resolution is ~ 1–10 keV FWHM over the energy range from soft X-rays (3 keV) to gamma-rays (17 MeV). An automated shutter system allows a wide dynamic range (> 107) of flare intensities to be handled without instrument saturation. Data for every photon is stored in a solid-state memory and telemetered to the ground, thus allowing for versatile data analysis keyed to specific science objectives. The spin-stabilized (~ 15 rpm) spacecraft is Sun-pointing to within ~ 0.2° and operates autonomously. RHESSI was launched on 5 February 2002, into a nearly circular, 38° inclination, 600-km altitude orbit and began observations a week later. The mission is operated from Berkeley using a dedicated 11-m antenna for telemetry reception and command uplinks. All data and analysis software are made freely and immediately available to the scientific community.

The Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) observes solar hard X-rays and gamma-rays from 3 keV to 17 MeV with spatial resolution as high as 2.3 arc sec. Instead of focusing optics, imaging is based on nine rotating modulation collimators that time-modulate the incident flux as the spacecraft rotates. Starting from the arrival time of individual photons, ground-based software then uses the modulated signals to reconstruct images of the source. The purpose of this paper is to convey both an intuitive feel and the mathematical basis for this imaging process. Following a review of the relevant hardware, the imaging principles and the basic back-projection method are described, along with their relation to Fourier transforms. Several specific algorithms (Clean, MEM, Pixons and Forward-Fitting) applicable to RHESSI imaging are briefly described. The characteristic strengths and weaknesses of this type of imaging are summarized.

Extracting and indexing relevant information with computer vision algorithms in very large solar image archives allows investigating solar activity from a new perspective. Using computer vision algorithms, we have developed methods that work with very compact and concise descriptions of images. We apply our method to images from the Solar Dynamics Observatory (SDO) and present a proof-of-concept Query by Example (QBE) system. In addition we introduce a benchmark dataset, on one hand to evaluate our system, and on the other hand to allow comparisons of our results with other QBE systems in this domain.

Solar Orbiter is a Sun-observing mission led by the European Space Agency, addressing the interaction between the Sun and the heliosphere. It will carry ten instruments, among them the X-ray imaging spectrometer STIX. STIX will determine the intensity, spectrum, timing, and location of thermal and accelerated electrons near the Sun through their bremsstrahlung X-ray emission. This report gives a brief overview of the STIX scientific goals and covers in more detail the instrument design and challenges.

Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information should be summarized and indexed for this specific kind of images. The method we present first summarizes the image information content by partitioning the image in regions with same texture. We call this process texture summarization. Second, indexing features are generated by examining the distribution of parameters describing image regions. Indexing features can be associated with global or local image characteristics. Both kinds of indexing features are evaluated on the retrieval system of the Zurich archive of solar radio spectrograms. The evaluation shows that generating local indexing features using self-organizing maps yields the best effectiveness of all tested methods.

We present a method to access efficiently and effectively images in large astronomical archives. This method allows users to interactively participate in the retrieval process. They may virtually 'navigate' through the archive for choosing images that are relevant for their purposes. The navigation process is performed by switching back and forth between three retrieval-system modes: a query mode, a browse mode and an inspection mode. The method has been applied to an image retrieval system to access solar radio spectrograms archived at ETH in Zurich. The system, called ASPECT, allows access to over 50 000 data sets on-line. 1. Overview

The Spectrometer Telescope for Imaging X-rays (STIX) is one of 10 instruments on-board Solar Orbiter mission of the European Space Agency (ESA) scheduled to be launched in 2017. STIX is aimed to provide imaging spectroscopy of solar thermal and non-thermal hard X-ray emissions from 4 keV to 150 keV using a Fourier-imaging technique. The instrument employs a set of tungsten grids in front of 32 pixelized CdTe detectors. These detectors are source of data collected and analyzed in real time by Instrument Data Processing Unit (IDPU). In order to support development and implementation of on-board algorithms a dedicated detector hardware simulator is designed and manufactured as a part of Electrical Ground Support Equipment (EGSE) for STIX instrument. Complementary to the hardware simulator is data analysis software which is used to generate input data and to analyze output data. The simulator will allow sending strictly defined data from all detectors’ pixels at the input of the IDPU for further analysis of instrument response. Particular emphasis is given here to the simulator hardware design.

Heliophysics is the study of highly energetic events that originate on the Sun and propagate through the solar system. Such events can cause critical and possibly fatal disruption of the electromagnetic systems on spacecraft and on ground-based structures such as electric power grids, so there is a clear need to understand the events in their totality as they propagate through space and time. The e-Science challenge posed is that the data was gathered by many observatories and communities that have hitherto not needed to work together. Firstly, this involves the problem of helping users to more easily find and understand the relevance of data, especially data from outside their domain. Secondly, it involves solving challenges of data integration. We describe the design of the HELIO infrastructure, based on the use of Web services linked together by workflows and accessible via portal-based user interfaces. We also discuss current progress in the implementation of this infrastructure and the feedback from the user community. © 2012 Elsevier B.V. All rights reserved.

Observations recorded by telescopes are ususally stored in large, multidimensional archives, composed nowadays often of images. As these archives constantly grow in size, a content-based information retrieval system must be developed to allow queries by browsing or comparing. However, fast browsing requires transforming the images into smaller representations, or icons, which can be stored on fast access devices, displayed efficiently, and be used also for searching similarities between images. To this end, the information content of images must be extracted, selected, and stored in a compressed format. Its visualization must subsequently only evidence the most relevant parts of the observations when browsing.

The rapid development of world-wide networking during the last two years, due partly to the simple concept of addressing with uniform resource locators (URLs), has drastically simplified information exchange. This expanding communication media has created new possibilities in the access of large databases, and has therefore found a particular interest in astronomy. The most used means of information transfer is text. If large sets of multi-dimensional data, commonly images, have to be accessed, longer transfer times compared with text urge the data manager to find more efficient solutions. Modern tools are not as efficient at browsing among images through a network compared with browsing text. Either the images being browsed are too large to be transferred quickly, or the image size is reduced so much that the interesting information is lost during the data reduction. In this article, an alternative to the transfer of plain images is investigated, based on the fact that only a part of an image's information content is needed for browsing. Images may therefore be reduced to icons which only symbolically represent the information content. Such image icons are used to browse solar radio spectrograms in the Zurich Radio Astronomy Group archive.

The Spectrometer Telescope for Imaging X-rays (STIX) is one of 10 instruments on board Solar Orbiter, a confirmed Mclass mission of the European Space Agency (ESA) within the Cosmic Vision program scheduled to be launched in 2017. STIX applies a Fourier-imaging technique using a set of tungsten grids (at pitches from 0.038 to 1 mm) in front of 32 pixelized CdTe detectors to provide imaging spectroscopy of solar thermal and non-thermal hard X-ray emissions from 4 to 150 keV. The status of the instrument reviewed in this paper is based on the design that passed the Preliminary Design Review (PDR) in early 2012. Particular emphasis is given to the first light of the detector system called Caliste-SO.

International audience; Heliophysics is a new research field that explores the Sun-Solar System Connection; it requires the joint exploitation of solar, heliospheric, magnetospheric and ionospheric observations.HELIO, the Heliophysics Integrated Observatory, will facilitate this study by creating an integrated e-Infrastructure that has no equivalent anywhere else. It will be a key component of a worldwide effort to integrate heliophysics data and will coordinate closely with international organizations to exploit synergies with complementary domains.HELIO was proposed under a Research Infrastructure call in the Capacities Programme of the European Commission's 7th Framework Programme (FP7). The project was selected for negotiation in January 2009; following a successful conclusion to these, the project started on 1 June 2009 and will last for 36 months.

The Heterodyne Instrument for the Far Infrared (HIFI) onboard the Herschel Space Observatory allows the first observations of light diatomic molecules at high spectral resolution and in multiple transitions. Here, we report deep integrations using HIFI in different lines of hydrides towards the high-mass star forming region AFGL 2591. Detected are CH, CH+, NH, OH+, H2O+, while NH+ and SH+ have not been detected. All molecules except for CH and CH+ are seen in absorption with low excitation temperatures and at velocities different from the systemic velocity of the protostellar envelope. Surprisingly, the CH(JF,P = 3/2_2,- - 1/2_1,+) and CH+(J = 1 - 0, J = 2 - 1) lines are detected in emission at the systemic velocity. We can assign the absorption features to a foreground cloud and an outflow lobe, while the CH and CH+ emission stems from the envelope. The observed abundance and excitation of CH and CH+ can be explained in the scenario of FUV irradiated outflow walls, where a cavity etched out by the outflow allows protostellar FUV photons to irradiate and heat the envelope at larger distances driving the chemical reactions that produce these molecules., Comment: Accepted for publication in Astronomy and Astrophysics (HIFI first results issue)

We present SphereViz, a novel 3D user interface for the visual exploration of multi-dimensional data sets in virtual reality environments. SphereViz builds on known visualization and search concepts like RadViz and RelevanceSphere. It combines them with 3D-interaction techniques like World in Miniature for projection in virtual environments. A prototype implementation of SphereViz allows to study, on one hand, the visualization methods of images in 3D space, and on the other hand, intuitive search methods and adequate interaction techniques.

The European Grid of Solar Observations (EGSO) is a Solar virtual observatory (see Hill et al., 2002). It has been funded through the 5th Framework Program of the European Community. A dozen of laboratories, mixing Solar Physics and Information Technology, in Great Britain, France, Italy and Swiss have been involved in this project during 3 years. A grid accessing several dozens of databases and archives scattered all around the world has been developped as well as a Solar Event Catalogue and a Solar Feature Catalogue. The original aspect of this work consists in the possibility not only to search through the characteristics of observations, but also search for available data corresponding to specific kinds of events. So it is now very important to be able to follow the Sun 24 hours a day in order to enrich the events database for future queries. More informations on EGSO, catalogues and user interface can be accessd through the web site: http://www.egso.org/

The European Grid of Solar Observations (EGSO) is a Grid test-bed that will change the way users analyze solar data. One of the major hurdles in the analysis of solar data is finding what data are available and retrieving those required. EGSO is integrating the access to solar data by building a Grid including solar archives around the world. The Grid relies on metadata and tools for selecting, processing and retrieving distributed and heterogeneous solar data. EGSO is also creating a solar feature catalogue giving for the first time the ability to select solar data based on phenomena and events. In essence, EGSO is providing the fabric of a virtual observatory. Since the first release of EGSO in September 2003, members of the solar community have been involved in product testing. The constant testing and feedback allows us to assure the usability of the system. The capabilities of the latest release will be described, and the scientific problems that it addresses discussed. EGSO is funded under the IST (Information Society Technologies) thematic priority of the European Commission's Fifth Framework Programme (FP5) – it started in March 2002 and will last for three years. The EGSO Consortium comprises 11 institutes from Europe and the US and is led by the Mullard Space Science Laboratory of University College London. EGSO is collaborating with other groups in the US who are working on similar virtual observatory projects for solar and heliospheric data with the objective of providing integrated access to these data.

The European Grid of Solar Observations (EGSO) is a project to develop a virtual observatory for the solar physics community. Like in all such projects, a vital component is a schema that adequately describes the data in the distributed data sets. Here, we discuss the schema in general terms, and present a draft example of a portion of a possible XML schema.

The primary scientific objective of the High Energy Solar Spectroscopic Imager (HESSI) Small Explorer mission selected by NASA is to investigate the physics of particle acceleration and energy release in solar flares. Observations will be made of x-rays and (gamma) rays from approximately 3 keV to approximately 20 MeV with an unprecedented combination of high resolution imaging and spectroscopy. The HESSI instrument utilizes Fourier- transform imaging with 9 bi-grid rotating modulation collimators and cooled germanium detectors. The instrument is mounted on a Sun-pointed spin-stabilized spacecraft and placed into a 600 km-altitude, 38 degrees inclination orbit.It will provide the first imaging spectroscopy in hard x-rays, with approximately 2 arcsecond angular resolution, time resolution down to tens of ms, and approximately 1 keV energy resolution; the first solar (gamma) ray line spectroscopy with approximately 1-5 keV energy resolution; and the first solar (gamma) -ray line and continuum imaging,with approximately 36-arcsecond angular resolution. HESSI is planned for launch in July 2000, in time to detect the thousands of flares expected during the next solar maximum.

We report on high-resolution optical and hard X-ray observations of solar flare ribbons seen during the GOES X6.5 class white-light flare of 2006 December 6. The data consist of imaging observations at 430 nm (the Fraunhofer G band) taken by the Hinode Solar Optical Telescope with the hard X-rays observed by the Reuven Ramaty High Energy Solar Spectroscopic Imager. The two sets of data show closely similar ribbon structures, strongly suggesting that the flare emissions in white light and in hard X-rays have physically linked emission mechanisms. While the source structure along the ribbons is resolved at both wavelengths (length ~ 30''), only the G-band observations resolve the width of the ribbon, with values between ~05 and ~18. The unresolved hard X-ray observations reveal an even narrower ribbon in hard X-rays (the main footpoint has a width perpendicular to the ribbon of 5 × 1012 erg s–1 cm–2 provided by an electron flux of 1 × 1020 electrons s–1 cm–2 above 18 keV. This requires that the beam density of electrons above 18 keV be at least 1 × 1010 cm–3. Even if field lines converge toward the chromospheric footpoints, the required beam in the corona has too high a density to be described as a dilute tail population on top of a Maxwellian core. We discuss this issue and others associated with this extreme event, which poses serious questions to the standard thick target beam interpretation of solar flares.