EU Data Protection Law and Targeted Advertising: Consent and the Cookie Monster - Tracking the crumbs of online user behaviour

This article provides a holistic legal analysis of the use of cookies in Online Behavioural Advertising. The current EU legislative framework is outlined in detail, and the legal obligations are examined. Consent and the debates surrounding its implementation form a large portion of the analysis. The article outlines the current difficulties associated with the reliance on this requirement as a condition for the placing and accessing of cookies. Alternatives to this approach are explored, and the implementation of solutions based on the application of the Privacy by Design and Privacy by Default concepts are presented. This discussion involves an analysis of the use of code and, therefore, product architecture to ensure adequate protections.

GPS-only gravity field determination from GOCE data

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) is now in orbit for more than four years. This is longer than the originally planned lifetime of the satellite and after three years on the same altitude the satellite has been lowered to 235 km in several steps. In the frame of the GOCE High-level Processing Facility the Astronomical Institute of the University of Bern (AIUB) is responsible for the determination of the official Precise Science Orbit (PSO) product. Kinematic GOCE orbits are part of this product and are used by several institutions in- and outside the HPF for determining the low degrees of the Earth’s gravity field. AIUB GOCE GPS-only gravity field solutions using the Celestial Mechanics Approach and covering the Release 4 period as well as a more recent time interval at the lower orbit altitude are shown and discussed. Special attention is paid to the impact of systematic deficiencies in the kinematic orbits on the resulting gravity fields, e.g., related to the geomagnetic equator, and on possibilities to get rid of them.

Precise Orbit Determination of Low Earth Satellites at AIUB using GPS and SLR data

An ever increasing number of low Earth orbiting (LEO) satellites is, or will be, equipped with retro-reflectors for Satellite Laser Ranging (SLR) and on-board receivers to collect observations from Global Navigation Satellite Systems (GNSS) such as the Global Positioning Sys- tem (GPS) and the Russian GLONASS and the European Galileo systems in the future. At the Astronomical Insti- tute of the University of Bern (AIUB) LEO precise or- bit determination (POD) using either GPS or SLR data is performed for a wide range of applications for satellites at different altitudes. For this purpose the classical numeri- cal integration techniques, as also used for dynamic orbit determination of satellites at high altitudes, are extended by pseudo-stochastic orbit modeling techniques to effi- ciently cope with potential force model deficiencies for satellites at low altitudes. Accuracies of better than 2 cm may be achieved by pseudo-stochastic orbit modeling for satellites at very low altitudes such as for the GPS-based POD of the Gravity field and steady-state Ocean Circula- tion Explorer (GOCE).

Time-variable gravity signal in Greenland revealed by high-low satellite-to-satellite tracking

[1] In the event of a termination of the Gravity Recovery and Climate Experiment (GRACE) mission before the launch of GRACE Follow-On (due for launch in 2017), high-low satellite-to-satellite tracking (hl-SST) will be the only dedicated observing system with global coverage available to measure the time-variable gravity field (TVG) on a monthly or even shorter time scale. Until recently, hl-SST TVG observations were of poor quality and hardly improved the performance of Satellite Laser Ranging observations. To date, they have been of only very limited usefulness to geophysical or environmental investigations. In this paper, we apply a thorough reprocessing strategy and a dedicated Kalman filter to Challenging Minisatellite Payload (CHAMP) data to demonstrate that it is possible to derive the very long-wavelength TVG features down to spatial scales of approximately 2000 km at the annual frequency and for multi-year trends. The results are validated against GRACE data and surface height changes from long-term GPS ground stations in Greenland. We find that the quality of the CHAMP solutions is sufficient to derive long-term trends and annual amplitudes of mass change over Greenland. We conclude that hl-SST is a viable source of information for TVG and can serve to some extent to bridge a possible gap between the end-of-life of GRACE and the availability of GRACE Follow-On.

Homogeneous reprocessing of GPS, GLONASS and SLR observations

The International GNSS Service (IGS) provides operational products for the GPS and GLONASS constellation. Homogeneously processed time series of parameters from the IGS are only available for GPS. Reprocessed GLONASS series are provided only by individual Analysis Centers (i. e. CODE and ESA), making it difficult to fully include the GLONASS system into a rigorous GNSS analysis. In view of the increasing number of active GLONASS satellites and a steadily growing number of GPS+GLONASS-tracking stations available over the past few years, Technische Universität Dresden, Technische Universität München, Universität Bern and Eidgenössische Technische Hochschule Zürich performed a combined reprocessing of GPS and GLONASS observations. Also, SLR observations to GPS and GLONASS are included in this reprocessing effort. Here, we show only SLR results from a GNSS orbit validation. In total, 18 years of data (1994–2011) have been processed from altogether 340 GNSS and 70 SLR stations. The use of GLONASS observations in addition to GPS has no impact on the estimated linear terrestrial reference frame parameters. However, daily station positions show an RMS reduction of 0.3 mm on average for the height component when additional GLONASS observations can be used for the time series determination. Analyzing satellite orbit overlaps, the rigorous combination of GPS and GLONASS neither improves nor degrades the GPS orbit precision. For GLONASS, however, the quality of the microwave-derived GLONASS orbits improves due to the combination. These findings are confirmed using independent SLR observations for a GNSS orbit validation. In comparison to previous studies, mean SLR biases for satellites GPS-35 and GPS-36 could be reduced in magnitude from −35 and −38 mm to −12 and −13 mm, respectively. Our results show that remaining SLR biases depend on the satellite type and the use of coated or uncoated retro-reflectors. For Earth rotation parameters, the increasing number of GLONASS satellites and tracking stations over the past few years leads to differences between GPS-only and GPS+GLONASS combined solutions which are most pronounced in the pole rate estimates with maximum 0.2 mas/day in magnitude. At the same time, the difference between GLONASS-only and combined solutions decreases. Derived GNSS orbits are used to estimate combined GPS+GLONASS satellite clocks, with first results presented in this paper. Phase observation residuals from a precise point positioning are at the level of 2 mm and particularly reveal poorly modeled yaw maneuver periods.

Time Variable Gravity: Contributions of GOCE Satellite Data to Monthly and Bi-monthly GRACE Gravity Estimates

A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

Doppler Orbit Determination of Deep Space Probes by the Bernese GNSS Software: First Results of the Combined Orbit Determination from DSN and Inter-Satellite Ka-Band Data from the Grail Mission

Navigation of deep space probes is most commonly operated using the spacecraft Doppler tracking technique. Orbital parameters are determined from a series of repeated measurements of the frequency shift of a microwave carrier over a given integration time. Currently, both ESA and NASA operate antennas at several sites around the world to ensure the tracking of deep space probes. Just a small number of software packages are nowadays used to process Doppler observations. The Astronomical Institute of the University of Bern (AIUB) has recently started the development of Doppler data processing capabilities within the Bernese GNSS Software. This software has been extensively used for Precise Orbit Determination of Earth orbiting satellites using GPS data collected by on-board receivers and for subsequent determination of the Earth gravity field. In this paper, we present the currently achieved status of the Doppler data modeling and orbit determination capabilities in the Bernese GNSS Software using GRAIL data. In particular we will focus on the implemented orbit determination procedure used for the combined analysis of Doppler and intersatellite Ka-band data. We show that even at this earlier stage of the development we can achieve an accuracy of few mHz on two-way S-band Doppler observation and of 2 µm/s on KBRR data from the GRAIL primary mission phase.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.