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In this paper, we deal with the so-called multi-shot network coding, meaning that the network is used several times (shots) to propagate the information. The framework we present is slightly more general than the one which can be found in the literature. We study and introduce the notion of column rank distance of rank metric convolutional codes for any given rate and finite field. Within this new framework we generalize previous results on column distances of Hamming and rank metric convolutional codes [3, 8]. This contribution can be considered as a continuation follow-up of the work presented in [10].

Paper is a persistent element of financial advisory encounters, despite the increasing digitisation of the financial industry. We seek to understand the reasons behind the resilience of paper-based encounters and advisors’ resistance to change by understanding the paper’s roles in financial advisory encounters. While applying multimodal analysis to a set of field and experimental data, we point to a range of prevalent advisory practices that rely on the use of paper documents and hand-written notes. We focus on the choreography of paper and how this intersects with the participants’ institutional identities and goals. Specifically, we show how advisors’ paper-oriented actions seek to convey a positive impression about the advisor and about the bank to the client, i.e. how they engage in seemingly mundane practices to impress their clients. Paper is far more than a medium for saving and presenting information: it is an interaction resource, a semiotic resource and an institutional resource; all these aspects of paper come into play during a financial advisory encounter. The manuscript concludes with suggestions on the design of technologies that may potentially replace the paper in financial advisory encounters and assesses the likelihood of this in light of the results.

Federated querying, the idea to execute queries over several distributed knowledge bases, lies at the core of the semantic web vision. To accommodate this vision, SPARQL provides the SERVICE keyword that allows one to allocate sub-queries to servers. In many cases, however, data may be available from multiple sources resulting in a combinatorially growing number of alternative allocations of subqueries to sources. Running a federated query on all possible sources might not be very lucrative from a user’s point of view if extensive execution times or fees are involved in accessing the sources’ data. To address this shortcoming, federated join-cardinality approximation techniques have been proposed to narrow down the number of possible allocations to a few most promising (or results-yielding) ones.

Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization – participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research.

We investigate political parties´ social media strategies, their perceived effectiveness, and how social media campaigns are internally organized. Our study focuses on Austria and Switzerland, coun...

Neuromorphic engineering takes inspiration from biology to solve engineering problems using the organizing principles of biological neural computation. This field has demonstrated success in sensor based applications (vision and audition) as well in cognition and actuators. This paper is focused on mimicking an interesting functionality of the retina that is computed by one type of Retinal Ganglion Cell (RGC). It is the early detection of approaching (expanding) dark objects. This paper presents the software and hardware logic FPGA implementation of this approach sensitivity cell. It can be used in later cognition layers as an attention mechanism. The input of this hardware modeled cell comes from an asynchronous spiking Dynamic Vision Sensor, which leads to an end-to-end event based processing system. The software model has been developed in Java, and computed with an average processing time per event of 370 ns on a NUC embedded computer. The output firing rate for an approaching object depends on the cell parameters that represent the needed number of input events to reach the firing threshold. For the hardware implementation on a Spartan6 FPGA, the processing time is reduced to 160 ns/event with the clock running at 50 MHz. Ministerio de Economía y Competitividad TEC2016-77785-P Unión Europea FP7-ICT-600954

A major challenge of the contemporary information age is the overwhelming and increasing data amount, especially when looking for specific information. Searching for relevant information is no longer manually possible, but has to rely on automatic methods, specifically, similarity search. From a formal perspective, similarity search can be seen as the problem of finding entities, which are considered to be similar to a query with respect to certain describing features. The question which features or which weighted combination of features to use for a given query creates a need for semi-automatic methods to address the needs of diverse users. Furthermore, the quality of the results of a similarity search is more than effectiveness, measured by precision and recall. The user ideally needs to trust the results and understand how they were computed. We propose to apply Visual Analytics methodologies, for synergistic cooperation of user and algorithms, to integrate three key dimensions of similarity search: users, tasks, and data for effective search. However, there exists a gap in knowledge how user, task as well as the available data influence each other and the similarity search. In this concept paper, we envision how Visual Analytics can be used to tackle current challenges of similarity search.

Part 2: Contributed Papers; International audience; We say that a Turing machine has periodic support if there is an infinitely repeated word to the left of the input and another infinitely repeated word to the right. In the search for the smallest universal Turing machines, machines that use periodic support have been significantly smaller than those for the standard model (i.e. machines with the usual blank tape on either side of the input). While generalising the model allows us to construct smaller universal machines it makes proving decidability results for the various state-symbol products that restrict program size more difficult. Here we show that given an arbitrary 2-state 2-symbol Turing machine and a configuration with periodic support the set of reachable configurations is regular. Unlike previous decidability results for 2-state 2-symbol machines, here we include in our consideration machines that do not reserve a transition rule for halting, which further adds to the difficulty of giving decidability results.

Long-Term Evolution (LTE) is a new communication standard developed by the Third Generation Partnership Project (3GPP). Currently, LTE is becoming a 4G reference architecture due to its widespread adoption among leading operators of mobile telecommunications. LTE is therefore foreseen as an important foundation for future 5G networks. In the shift towards 5G, several open issues have to be worked out in LTE. They emerge due to severe requirements put on the infrastructure of the future networks. First, mobile users will expect high capacity channels, in which capacity is measured in several Gbps. Second, new applications will be considered with high densities of connected devices. Third, 5G networks will have to accommodate new types of connected devices such as household appliances, meters and connected cars. Fourth, direct device-to-device (D2D) communication will have to be formulated for sharing information in a local context. In the broader view, network-based communication in the licensed band can provide enhanced Quality of Service (QoS) for D2D scenarios. Fifth, extreme reliability (e.g. medical applications) and ultra-low latencies (e.g. VANET applications) have to be considered. Sixth, for Internet of Things (IoT) applications, communication with high energy efficiency is required. Finally, in current mobile networks, we are approaching Shannon’s capacity limit. Therefore, an enhanced channel capacity shall be provided through the adoption of a new spectrum range. According to the aforementioned picture, 5G will be a holistic ecosystem providing connectivity in a wide range of application use cases. It is therefore natural to seamlessly integrate Public Safety (PS) applications with 5G using LTE as a starting point.

The current Web of Data contains a large amount of interlinked data. However, there is still a limited understanding about the quality of the links connecting entities of different and distributed data sets. Our goal is to provide a collection of indicators that help assess existing interlinking. In this paper, we present a framework for the intrinsic evaluation of RDF links, based on core principles of Web data integration and foundations of Information Retrieval.We measurethe extent to which links facilitate the discovery of an extended description of entities, and the discovery of other entities in other data sets. We also measure the use of different vocabularies. We analysed links extracted from a set of data sets from the Linked Data Crawl 2014 using these measures.

The Council of Europe is the only international organization to have issued recommendations on the regulation of the use of e-voting. The 2004 Recommendation to member States, Rec(2004)11 and the two 2010 Guidelines on certification and on transparency were recently repealed and replaced by Rec(2017)5 on Standards for e-voting and the associated Guidelines on its implementation. We discuss the 2017 Recommendation and the main novelties introduced by it. The Recommendation extends the definition of e-voting to include pure e-counting. It enlists 49 standards which set objectives that e-voting should fulfill to comply with the principles and conditions for democratic elections of the European electoral heritage. Detailed guidelines for the implementation of the objectives are collected in a lower level document, the Guidelines on the implementation of the provisions of Rec(2017)5. The guidelines are expected to be completed through further work. The main differences between the old and the new Council of Europe standards on e-voting are outlined. Correlations are illustrated. The expected use, impact and evolution of the Recommendation and Guidelines are briefly explained.

Background Code review is a cognitively demanding and time-consuming process. Previous qualitative studies hinted at how decomposing change sets into multiple yet internally coherent ones would improve the reviewing process. So far, literature provided no quantitative analysis of this hypothesis. Aims (1) Quantitatively measure the effects of change decomposition on the outcome of code review (in terms of number of found defects, wrongly reported issues, suggested improvements, time, and understanding); (2) Qualitatively analyze how subjects approach the review and navigate the code, building knowledge and addressing existing issues, in large vs. decomposed changes. Method Controlled experiment using the pull-based development model involving 28 software developers among professionals and graduate students. Results Change decomposition leads to fewer wrongly reported issues, influences how subjects approach and conduct the review activity (by increasing context-seeking), yet impacts neither understanding the change rationale nor the number of found defects. Conclusions Change decomposition reduces the noise for subsequent data analyses but also significantly supports the tasks of the developers in charge of reviewing the changes. As such, commits belonging to different concepts should be separated, adopting this as a best practice in software engineering.

Processing data streams is increasingly gaining momentum, given the need to process these flows of information in real-time and at Web scale. In this context, RDF Stream Processing (RSP) and Stream Reasoning (SR) have emerged as solutions to combine semantic technologies with stream and event processing techniques. Research in these areas has proposed an ecosystem of solutions to query, reason and perform real-time processing over heterogeneous and distributed data streams on the Web. However, so far one basic building block has been missing: a mechanism to disseminate and exchange RDF streams on the Web. In this work we close this gap, proposing TripleWave, a reusable and generic tool that enables the publication of RDF streams on the Web. The features of TripleWave were selected based on requirements of real use-cases, and support a diverse set of scenarios, independent of any specific RSP implementation. TripleWave can be fed with existing Web streams (e.g. Twitter and Wikipedia streams) or time-annotated RDF datasets (e.g. the Linked Sensor Data dataset). It can be invoked through both pull- and push-based mechanisms, thus enabling RSP engines to automatically register and receive data from TripleWave.

Consider $ m $ copies of an irreducible, aperiodic Markov chain $ Y $ taking values in a finite state space. The asymptotics as $ m $ tends to infinity, of the first time from which on the trajectories of the $ m $ copies differ, have been studied by Szpankowski (1991) in the setting of tries. We use a different approach and model the $ m $ trajectories by a variant of the occupancy scheme, where we consider a nested sequence of boxes. This approach will enable us to extend the result to the case when the transition probabilities are random. We moreover use the same techniques to study the asymptotics as $ m $ tends to infinity of the time up to which we have observed all the possible trajectories of $ Y $ in random and nonrandom scenery.

In this paper, we report on the development of a web application that displays Swiss German Sign Language (DSGS) signs for places with train stations in Switzerland in synthesized form, i.e., by means of a signing avatar. Ours is the first platform to make DSGS place name signs accessible in geolocalized form, i.e., by linking them to a map, and to use synthesized signing. The latter mode of display is advantageous over videos of human signers, since place name signs for any sign language are subject to language change. Our web application targets both deaf and hearing DSGS users. The underlying programming code is freely available. The application can be extended to display any kind of geolocalized data in any sign language.

Intelligent tutoring systems are adapting the curriculum to the needs of the student. The integration of stealth assessments of student traits into tutoring systems, i.e. the automatic detection of student characteristics has the potential to refine this adaptation. We present a pipeline for integrating automatic assessment seamlessly into a tutoring system and apply the method to the case of developmental dyscalculia (DD). The proposed classifier is based on user inputs only, allowing non-intrusive and unsupervised, universal screening of children. We demonstrate that interaction logs provide enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91% after 11 minutes on average.

We are witnessing a growing interest for Web applications that (i) require to continuously combine highly dynamic data stream with background data and (ii) have reactivity as key performance indicator. The Semantic Web community showed that RDF Stream Processing (RSP) is an adequate framework to develop this type of applications.

The current state of the art in RDF Stream Processing (RSP) proposes several models and implementations to combine Semantic Web technologies with Data Stream Management System (DSMS) operators like windows. Meanwhile, only a few solutions combine Semantic Web and Complex Event Processing (CEP), which includes relevant features, such as identifying sequences of events in streams. Current RSP query languages that support CEP features have several limitations: EP-SPARQL can identify sequences, but its selection and consumption policies are not all formally defined, while C-SPARQL offers only a naive support to pattern detection through a timestamp function. In this work, we introduce an RSP query language, called RSEP-QL, which supports both DSMS and CEP operators, with a special interest in formalizing CEP selection and consumption policies. We show that RSEP-QL captures EP-SPARQL and C-SPARQL, and offers features going beyond the ones provided by current RSP query languages.

Benchmarks like LSBench, SRBench, CSRBench and, more recently, CityBench satisfy the growing need of shared datasets, ontologies and queries to evaluate window-based RDF Stream Processing RSP engines. However, no clear winner emerges out of the evaluation. In this paper, we claim that the RSP community needs to adopt a Systematic Comparative Research Approach SCRA if it wants to move a step forward. To this end, we propose a framework that enables SCRA for window based RSP engines. The contributions of this paper are: ii?źthe requirements to satisfy for tools that aim at enabling SCRA; ii the architecture of a facility to design and execute experiment guaranteeing repeatability, reproducibility and comparability; iii $$\mathcal {H}$$eaven --- a proof of concept implementation of such architecture that we released as open source ---; iv two RSP engine implementations, also open source, that we propose as baselines for the comparative research i.e., they can serve as terms of comparison in future works. We prove $$\mathcal {H}$$eaven effectiveness using the baselines by: i showing that top-down hypothesis verification is not straight forward even in controlled conditions and ii providing examples of bottom-up comparative analysis.

Laughter is everywhere. So much so that we often do not even notice it. First, laughter has a strong connection with humour. Most of us seek out laughter and people who make us laugh, and it is what we do when we gather together as groups relaxing and having a good time. But laughter also plays an important role in making sure we interact with each other smoothly. It provides social bonding signals that allow our conversations to flow seamlessly between topics; to help us repair conversations that are breaking down; and to end our conversations on a positive note.

Research on persuasive technologies PT focuses, primarily, on the design and development of IT for inducing change of individual's behavior and attitude through computer-human and computer-mediated influence. The issue of practices in co-located human-human persuasive encounters remained unattended in the PT community. This study uses the notion of persuasive practices to understand the course of events in face-to-face home security advisory sessions --- it specifies and illustrates such practices and discusses their impact on the persuasiveness of the encounter. Furthermore, it presents potential of IT to support such persuasive practices thus opening new research possibilities of PT research.

In the context of testing of Object-Oriented (OO) software systems, researchers have recently proposed search based approaches to automatically generate whole test suites by considering simultaneously all targets (e.g., branches) defined by the coverage criterion (multi-target approach). The goal of whole suite approaches is to overcome the problem of wasting search budget that iterative single-target approaches (which iteratively generate test cases for each target) can encounter in case of infeasible targets. However, whole suite approaches have not been implemented and experimented in the context of procedural programs. In this paper we present OCELOT (Optimal Coverage sEarch-based tooL for sOftware Testing), a test data generation tool for C programs which implements both a state-of-the-art whole suite approach and an iterative single-target approach designed for a parsimonious use of the search budget. We also present an empirical study conducted on 35 open-source C programs to compare the two approaches implemented in OCELOT. The results indicate that the iterative single-target approach provides a higher efficiency while achieving the same or an even higher level of coverage than the whole suite approach.

We present a new platform, "Regulus Lite", which supports rapid development and web deployment of several types of phrasal speech translation systems using a minimal formalism. A distinguishing feature is that most development work can be performed directly by domain experts. We motivate the need for platforms of this type and discuss three specific cases: medical speech translation, speech-to-sign-language translation and voice questionnaires. We briefly describe initial experiences in developing practical systems.

The 2016 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), aims at providing a challenging image analysis opportunity including multitemporal, multiresolution, and multisensor fusion. The 2016 contest involves two data modalities acquired over the city of Vancouver, Canada (49?15?N 123?6?W): a very high-resolution multitemporal sequence and an ultrahigh definition (UHD) video from space acquired from the International Space Station (ISS). The data were acquired and provided by Deimos Imaging and UrtheCast (Figure 1).

Services computing is both an academic field of study looking back at close to 15 years of fundamental research and a vibrant area of industrial software engineering. Industrial practice in this area is notorious for its ever-changing nature, with the state of the art changing almost on a yearly basis based on the ebb and flow of various hypes and trends (e.g., microservices). In this paper, we provide a look “across the wall” into industrial services computing. We conducted an empirical study based on the service ecosystem of 42 companies, and report, among other aspects, how service-to-service communication is implemented, how service discovery works in practice, what Quality-of-Service metrics practitioners are most interested in, and how services are deployed and hosted. We argue that not all assumptions that are typical in academic papers in the field are justified based on industrial practice, and conclude the paper with recommendations for future research that is more aligned with the services industry.

Feature sensitive simplification and re-sampling of point set surfaces is an important and challenging issue for many computer graphics and geometric modeling applications. Based on the regular sampling of the Gaussian sphere and the surface normals mapping onto the Gaussian sphere, an adaptive re-sampling framework for point set surfaces is presented in this paper, which includes a naive sampling step by index propagation and a novel cluster optimization step by normalized rectification. Our proposed re-sampling scheme can generate non-uniformly distributed discrete sample points for the underlying point sets in a feature sensitive manner. The intrinsic geometric features of the underlying point set surfaces can be preserved efficiently due to our adaptive re-sampling scheme. A novel splat rendering technique is adopted to illustrate the efficiency of our re-sampling scheme. Moreover, a numerical error statistics and surface reconstruction for simplified models are also given to demonstrate the effectiveness of our algorithm in term of the simplified quality of the point set surfaces.

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses., VLDB2012

Among the many applications in social science for the entry and management of data, there are only a few software packages that apply natural language processing to identify semantic concepts such as issue categories or political statements by actors. Although these procedures usually allow efficient data collection, most have difficulty in achieving sufficient accuracy because of the high complexity and mutual relationships of the variables used in the social sciences. To address these flaws, we suggest a (semi-) automatic annotation approach that implements an innovative coding method (Core Sentence Analysis) by computational linguistic techniques (mainly entity recognition, concept identification, and dependency parsing). Although such computational linguistic tools have been readily available for quite a long time, social scientists have made astonishingly little use of them. The principal aim of this article is to gather data on party-issue relationships from newspaper articles. In the first...

Telecommunication economics has evolved into an area of research, which includes technical aspects, social issues, economic and business factors, and regulation demands. The combination of those four dimensions is becoming critical for a suitable and viable understanding of communication needs in today’s society. Therefore, this report on the Dagstuhl Perspectives Seminar ‘‘Telecommunication Economics’’summarizes a number of key aspects of this field, it develops a set of selected and detailed recommendations, and outlines respective perspectives, which are being worked on partially already today and which need a much closer attention in the mid-term future.

This article describes a multiloop design approach, demonstrating two concatenated build-and-evaluate loops of a project that aims at enhancing and improving tele-counseling at travel agency call-centers. The socio-technical system design intends to implement and support a collaborative travel counseling concept which equalizes travel agents and customers within a value co-created service encounter to resolve the specific problems in travel agency call-centers. The design is finally guided by four instrumental goals: (1) increase transparency, (2) improve information quality, (3) support joint problem solving, and (4) create advisory experience. While the first build-and-evaluate loop mainly enhanced the workplace picture, the second build-and-evaluate loop primarily revealed organizational demands. This indicates that the proposed design approach enables sequentially broadening the problem space for design and supports iteratively moving forward the utility of the emerging artifact. Design is informed by concatenating insights from the previous loops which enrich understanding of the instrumental goals. The presented goals as well as the design approach are encouraging candidates for additional testing as a base for general design principles.

Despite the intense interest towards realizing the Semantic Web vision, most existing RDF data management schemes are constrained in terms of efficiency and scalability. Still, the growing popularity of the RDF format arguably calls for an effort to offset these drawbacks. Viewed from a relational-database perspective, these constraints are derived from the very nature of the RDF data model, which is based on a triple format. Recent research has attempted to address these constraints using a vertical-partitioning approach, in which separate two-column tables are constructed for each property. However, as we show, this approach suffers from similar scalability drawbacks on queries that are not bound by RDF property value. In this paper, we propose an RDF storage scheme that uses the triple nature of RDF as an asset. This scheme enhances the vertical partitioning idea and takes it to its logical conclusion. RDF data is indexed in six possible ways, one for each possible ordering of the three RDF elements. Each instance of an RDF element is associated with two vectors; each such vector gathers elements of one of the other types, along with lists of the third-type resources attached to each vector element. Hence, a sextuple-indexing scheme emerges. This format allows for quick and scalable general-purpose query processing; it confers significant advantages (up to five orders of magnitude) compared to previous approaches for RDF data management, at the price of a worst-case five-fold increase in index space. We experimentally document the advantages of our approach on real-world and synthetic data sets with practical queries.

The emerging field of visual analytics changes the way we model, gather, and analyze data. Current data analysis approaches suggest to gather as much data as possible and then focus on goal and process oriented data analysis techniques. Visual analytics changes this approach and the methodology to interpret the results becomes the key issue. This paper contributes with a method to interpret visual hierarchical heavy hitters (VHHHs). We show how to analyze data on the general level and how to examine specific areas of the data. We identify five common patterns that build the interpretation alphabet of VHHHs. We demonstrate our method on three different real world datasets and show the effectiveness of our approach.

This paper proposes the nearest neighbor join, r x T [G, Θ] s, with similarity on T, and integrated support for grouping attributes G and selection predicates Θ. The corresponding valuation algorithm, roNNJ, is robust and does not suffer from redundant fetches and index false hits, which are major performance bottlenecks in nearest neighbour joins that do not support grouping attributes and selection predicates. Our solution does not compute redundant fetches since it accesses the fact table only once, and uses the groups of the outer relation to limit the fact table to its relevant portions. We experimentally evaluate our solution using a data warehouse that manages analyses of animal feeds, and the TPC-H.

In recent years, search engines have started presenting semantically relevant entity information together with document search results. Entity ranking systems are used to compute recommendations for related entities that a user might also be interested to explore. Typically, this is done by ranking relationships between entities in a semantic knowledge graph using signals found in a data source as well as type annotations on the nodes and links of the graph. However, the process of producing these rankings can take a substantial amount of time. As a result, entity ranking systems typically lag behind real-world events and present relevant entities with outdated relationships to the search term or even outdated entities that should be replaced with more recent relations or entities. This paper presents a study using a real-world stream-processing based implementation of an entity ranking system, to understand the effect of data timeliness on entity rankings. We describe the system and the data it processes in detail. Using a longitudinal case-study, we demonstrate i that low-latency, large-scale entity relationship ranking is feasible using moderate resources and ii that stream-based entity ranking improves the freshness of related entities while maintaining relevance.

Part 3: Services, Processes and Infrastructure; International audience; This article introduces and explores the potential of an active electronic data safe (AEDS) serving as an infrastructure to achieve transformational government. An AEDS connects individuals and organizations from the private and the public sector to exchange information items related to business processes following the user-managed access paradigm. To realize the transformational government’s vision of user-centricity, fundamental changes in the service provision and collaboration of public and private sector organizations are needed. Findings of a user study with a prototype of an AEDS are used to identify four barriers for the adoption of an AEDS in the light of transformational government: (1) offering citizens unfamiliar services having the character of experience-goods; (2) failing to fulfil common service expectations of the customers; (3) failing to establish contextual integrity for data sharing, and, (4) failing to establish and run an AEDS as a multi-sided platform providing an attractive business model.

Past research has suggested that innovation processes in schools are more successful when they are participatory and voluntary. To examine this notion, we categorized schools into one of four different innovation-process types, based on group interviews with school staff: complementary bottom-up and top-down development (type 1), top-down development that is not supported bottom-up (type 2), bottom-up development that is not supported top-down (type 3) and optional development with neither strong bottom-up nor top-down initiatives (type 4). Based on this typology, analysis of variance was then conducted on survey response data from 357 teachers and 1051 9th grade students from these schools. In contrast with some of our expectations, we found that teachers in schools with a complementary top-down and bottom-up strategy as well as schools with a top-down strategy only showed better ICT-resources and a more intensive use of educational technology than those in bottom-up- or optional-innovation-type schools. Additionally, teachers' ICT-use in type 1 and 2 schools is predicted to a higher degree by the number of computers in the classroom than in schools where ICT-integration is bottom-up or optional. Our findings suggest that bottom-up innovation strategies are likely to fall short without top-down support, especially when funds for technology installations are missing. We examine the impact of top-down and bottom-up innovation processes on school ICT adoption.ICT is used more often when top-down and bottom-up processes are complementary.Teachers from both complementary and top-down schools have better infrastructure.Teachers from entirely bottom-up innovative schools show weakest ICT integration.Availability of computers and teachers skills are best predictors of ICT use in complementary and top down schools.

[Context and motivation] Requirements engineers create large numbers of artifacts when eliciting and documenting requirements. They need to navigate through these artifacts and display information details at points of interest for reviewing or editing information. [Question/problem] Traditional visualization mechanisms such as scrolling and opening multiple windows lose context when navigating and can be cumbersome to use, hence. On the other hand, focus+context approaches can display details in context, but they distort the data shown (e.g., fisheye views) or result in a large display canvas which again requires scrolling (e.g., zooming in Adora). [Principal ideas/results] We are developing a novel method for displaying just the information needed to perform an intended task. Our method partitions the available screen space into regions. The boundaries of regions are simulated with a model consisting of virtual magnetic balls and springs that behaves like a physical system. This model supports the requirements engineer in selecting how the relevant information should be displayed. [Contribution] In this paper, we present preliminary results on how our conceptual solution works and what benefits are expected.