This paper aims to contribute to the discussion on 360° video storytelling. It describes the 'Virtual Director' concept, an enabling technology that was developed to personalize video presentation in applications where multiple live streams are available at the same time. Users are supported in dynamically changing viewpoints, as the Virtual Director essentially automates the tasks of a human director. As research prototypes on a proof-of-concept maturity level, this approach has been evaluated for personalized live event broadcast, group video communication and distributed theatre performances. While on the capture side a 180° high-resolution panoramic video feed has been used in one of these application scenarios, so far, only traditional 2D video screen were investigated for playout. The research question this paper aims to contribute to is how technology in general, and an adaptation of the Virtual Director concept in particular, could assist users in their needs when consuming 360° content, both live and recorded. In contexts when users do not want to enjoy the freedom to look into any direction, or when content creators want them to look in a certain direction, how could the interaction with and intervention of a Virtual Director be applied from a storytelling point of view?

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2018

Ross-Hellauer Anthony, Kowald Dominik, Lex Elisabeth

Recommender Systems as Enabling Technology to Interlink Scholarly Information

Scholarly Communication Workshop co-located with WWW'2018, Lyon, 2018

Konferenz

Link

2018

Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria

Exploring challenges in data-driven business model innovation from Austrian enterprises

Proceedings in XXIX ISPIM Innovation Conference, Stockholm, 2018

Konferenz

The increasing amount of generated data and advances in technology and data analytics and are enablers and drivers for new business models with data as a key resource. Currently established organisations struggle with identifying the value and benefits of data and have a lack of know-how, how to develop new products and services based on data. There is very little research that is narrowly focused on data-driven business model innovation in established organisations. The aim of this research is to investigate existing activities within Austrians enterprises with regard to exploring data-driven business models and challenges encountered in this endeavour. The outcome of the research in progress paper are categories of challenges related to organisation, business and technology, established organisations in Austria face during data-driven business model innovation

2018

Cuder Gerald, Breitfuß Gert, Kern Roman

The International Water Association, 2018

Konferenz

Link

2018

Neuhold Robert, Gursch Heimo, Kern Roman, Cik Michael

Driver's Dashboard - Using Social Media Data as additional Information for Motorway Operators

Proceedings of the ITS World Congress 2018, Intelligent Transportation Society, Copenhagen, Denmark, 2018

Konferenz

Data collection on motorways for traffic management operations is traditionally based on local measurements points and camera monitoring systems. This work looks into social media as additional data source for the Austrian motorway operator ASFINAG. A system called Driver´s Dashboard was developed collecting incident descriptions from Facebook and RSS feeds, filtering relevant messages, and fusing them with traffic data. All collected texts were analysed for concepts describing road situations linking the texts from the web and social media with traffic messages and traffic data. Driver´s Dashboard was designed to examine the potential of social media for traffic monitoring with respect to Austrian characteristics in social media use and road transportation with only very few messages are available compared to other studies. Of 3,586 messages collected within a five-week period only 7.1% were automatically annotated as traffic relevant. Further, the traffic relevant messages for the motorway operator were analysed more in detail to identify correlations between message text and traffic data characteristics. A correlation of message text and traffic data was found in nine of eleven messages by comparing the speed profiles and traffic state data with the message text.

2018

Lacic Emanuel, Kowald Dominik, Reiter-Haas Markus, Slawicek Valentin, Lex Elisabeth

Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendation

In Proceedings of the International Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP'2018) co-located with the 11th ACM International Conference on Web Search and Data Mining, WSDM'2018, ACM, Los Angeles, USA, 2018

Konferenz

In this work, we address the problem of recommending jobs touniversity students. For this, we explore the impact of using itemembeddings for a content-based job recommendation system. Fur-thermore, we utilize a model from human memory theory to integratethe factors of frequency and recency of job posting interactions forcombining item embeddings. We evaluate our job recommendationsystem on a dataset of the Austrian student job portal Studo usingprediction accuracy, diversity as well as adapted novelty, which isintroduced in this work. We find that utilizing frequency and recencyof interactions with job postings for combining item embeddingsresults in a robust model with respect to accuracy and diversity, butalso provides the best adapted novelty results

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2018

Luzhnica Granit, Veas Eduardo Enrique

Investigating Interactions for Text Recognition using a Vibrotactile Wearable Display

ACM International Conference on Intelligent User Interfaces , Tokyo, 2018

Konferenz

Vibrotactile skin-reading uses wearable vibrotactile displays to convey dynamically generated textual information. Such wearable displays have potential to be used in a broad range of applications. Nevertheless, the reading process is passive, and users have no control over the reading flow. To compensate for such drawback, this paper investigates what kind of interactions are necessary for vibrotactile skin reading and the modalities of such interactions. An interaction concept for skin reading was designed by taking into account the reading as a process. We performed a formative study with 22 participants to assess reading behaviour in word and sentence reading using a six-channel wearable vibrotactile display. Our study shows that word based interactions in sentence reading are more often used and preferred by users compared to character-based interactions and that users prefer gesture-based interaction for skin reading. Finally, we discuss how such wearable vibrotactile displays could be extended with sensors that would enable recognition of such gesture-based interaction. This paper contributes a set of guidelines for the design of wearable haptic displays for text communication.

2018

Lovric Mario, Krebs Sarah, Cemernek David, Kern Roman

BIG DATA IN INDUSTRIAL APPLICATION

XII Meeting of Young Chemical Engineers, Zagreb, Kroatien, 2018

SAC 2018, 2018

Konferenz

On the web, massive amounts of information are available, includingwrong (or conflicting) information. This spreading of erroneous or fake contentsmakes it hard for users to distinguish between what is true and what is not. Factfinding algorithms represent a means to validate information. Yet, these algorithmsrequire an already existing, structured data set to validate a single fact; anad-hoc validation is thus not supported making them impractical for usage in realworld applications. This work presents an approach to generate these data setson-the-fly. For three facts, we generate respective data sets and apply six state-ofthe-art fact finding algorithms for evaluation purposes. In addition, our approachcontributes to comparing fact finding algorithms in a more objective way.

2018

Cuder Gerald, Baumgartner Christian

A data mining strategy for the search and classification of gene expression data in cancer

ÖGBMT - Jahrestagung 201, ÖGBMT - Österreichische Gesellschaft für Biomedizinische Techni, Hall in Tirol, 2018

Konferenz

Cancer is one of the most uprising diseases in our modern society and is defined by an uncontrolled growth of tissue. This growth is caused by mutation on the cellular level. In this thesis, a data-mining workflow was developed to find these responsible genes among thousands of irrelevant ones in three microarray datasets of different cancer types by applying machine learning methods such as classification and gene selection. In this work, four state-of-the-art selection algorithms are compared with a more sophisticated method, termed Stacked-Feature Ranking (SFR), further increasing the discriminatory ability in gene selection.

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2018

Cicchinelli Analia, Veas Eduardo Enrique, Pardo Abelardo, Pammer-Schindler Viktoria, Fessl Angela, Barreiros Carla, Lindstaedt Stefanie

Finding traces of self-regulated learning in activity streams

ACM Conference on Learning Analytics and Knowledge, LAK , ACM, ACM, 2018

Konferenz

This paper aims to identify self-regulation strategies from students' interactions with the learning management system (LMS). We used learning analytics techniques to identify metacognitive and cognitive strategies in the data. We define three research questions that guide our studies analyzing i) self-assessments of motivation and self regulation strategies using standard methods to draw a baseline, ii) interactions with the LMS to find traces of self regulation in observable indicators, and iii) self regulation behaviours over the course duration. The results show that the observable indicators can better explain self-regulatory behaviour and its influence in performance than preliminary subjective assessments.

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2018

Dennerlein_Bildungskarenz Sebastian, Kowald Dominik, Lex Elisabeth, Ley Tobias, Pammer-Schindler Viktoria

KF Uni Graz, Institut of System Sciences, Innovation and Sustainability, Graz, 2017

Konferenz

Nowadays digitalization is on everyone’s mind and affecting all areas of life. The rapid development of information technology and the increasing pervasiveness of digitalization represent new challenges to the business world. The emergence of the so-called fourth industrial revolution and the Internet of Things (IoT) confronts existing firms with changes in numerous aspects of doing business. Not only information and communication technologies are changing production processes through increasing automation. Digitalization can affect products and services itself. This could lead to major changes in a company’s value chain and as a consequence affects the company’s business model. In the age of digitalization, it is no longer sufficient to change single aspects of a firm’s business strategy, the business model itself needs to be the subject of innovation. This paper presents how digitalization affects business models of well-established companies in Austria. The results are demonstrated by means of two best practice case studies. The case studies were identified within an empirical research study funded by the Austrian Ministry for Transport, Innovation and Technology (BMVIT). The selected best practice cases presents how digitalization affects a firm’s business model and demonstrates the transformation of the value creation process by simultaneously contributing to sustainable development.

2017

de Reuver Mark, Tarkus Astrid, Haaker Timber, Breitfuß Gert, Roelfsema Melissa, Kosman Ruud, Heikkilä Marikka

Designing an ICT tooling platform to support the needs of SMEs in business model innovation

Unversity of Maribor, Faculty of Organizational Sciences, Andreja Pucihar, Ph.D., Mirjana Kljajić Borštnar, Ph.D., Christian Kittl, Ph.D., Pascal Ravesteijn, Ph.D., Roger Clarke, Ph.D., Roger Bons, Ph.D, University of Maribor Press, Maribor, 2017

Konferenz

In this paper, we present two design cycles for an online platform with ICT-enabled tooling that supports business model innovation by SMEs. The platform connects the needs of the SMEs regarding BMI with tools that can help to solve those needs and questions. The needs are derived from our earlier case study work (Heikkilä et al. 2016), showing typical BMI patterns of the SMEs needs - labelled as ‘I want to’s - about what an entrepreneur wants to achieve with business model innovation. The platform provides sets of integrated tools that can answer the typical ‘I want to’ questions that SMEs have with innovating their business models.

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2017

Pammer-Schindler Viktoria, Fessl Angela, Wiese Michael, Thalmann Stefan

Improving Search Strategies of Auditors – A Focus Group on Reflection Interventions

ARTEL Workshop at EC-TEL 2017, Tallin, Estland, 2017

Konferenz

Financial auditors routinely search internal as well as public knowledge bases as part of the auditing process. Efficient search strategies are crucial for knowledge workers in general and for auditors in particular. Modern search technology quickly evolves; and features beyond keyword search like fac-etted search or visual overview of knowledge bases like graph visualisations emerge. It is therefore desirable for auditors to learn about new innovations and to explore and experiment with such technologies. In this paper, we present a reflection intervention concept that intends to nudge auditors to reflect on their search behaviour and to trigger informal learning in terms of by trying out new or less frequently used search features. The reflection intervention concept has been tested in a focus group with six auditors using a mockup. Foremost, the discussion centred on the timing of reflection interventions and how to raise mo-tivation to achieve a change in search behaviour.

2017

Dennerlein_Bildungskarenz Sebastian, Ginthör Robert, Breitfuß Gert, Pammer-Schindler Viktoria, Stern Hermann

Bringing Big Data to Adolescence - Specifying Business Models by Practice

Institute of Systems Sciences, Innovation and Sustainability Research , Merangasse 18 /I , A - 8010 Graz, Austria, Baumgartner, R.J., Fuellsack, M., Gelbmann, U., Rauter, R, Graz, Austria, 2017

Konferenz

To specify the current understanding of business models in the realm of Big Data, we used a qualitative approach analysing 25 Big Data projects spread over the domains of Retail, Energy, Production, and Life Sciences, and various company types (SME, group, start-up, etc.). All projects have been conducted in the last two years at Austria’s competence center for Data-driven Business and Big Data Analytics, the Know-Center.

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2017

Open Science Conference 2017, Berlin, 2017

Konferenz

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2017

Kowald Dominik, Kopeinik Simone , Lex Elisabeth

The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems

International Conference on User Modeling, Adaptation and Personalization 2017, UMAP'2017, ACM, Bratislava, 2017

Konferenz

Recommender systems have become important tools to supportusers in identifying relevant content in an overloaded informationspace. To ease the development of recommender systems, a numberof recommender frameworks have been proposed that serve a widerange of application domains. Our TagRec framework is one of thefew examples of an open-source framework tailored towards developingand evaluating tag-based recommender systems. In this paper,we present the current, updated state of TagRec, and we summarizeand reect on four use cases that have been implemented withTagRec: (i) tag recommendations, (ii) resource recommendations,(iii) recommendation evaluation, and (iv) hashtag recommendations.To date, TagRec served the development and/or evaluation processof tag-based recommender systems in two large scale Europeanresearch projects, which have been described in 17 research papers.us, we believe that this work is of interest for both researchersand practitioners of tag-based recommender systems.

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2017

Görögh Edit, Vignoli Michela, Gauch Stephan, Blümel Clemens, Kraker Peter, Hasani-Mavriqi Ilire, Luzi Daniela , Walker Mappet, Toli Eleni, Sifacaki Electra

Opening up new channels for scholarly review, dissemination, and assessment

OpenSym 2017 International Symposium on Open Collaboration, Lorraine Morgan, ACM, Galway, Ireland, 2017

Konferenz

The growing dissatisfaction with the traditional scholarly communication process and publishing practices as well as increasing usage and acceptance of ICT and Web 2.0 technologies in research have resulted in the proliferation of alternative review, publishing and bibliometric methods. The EU-funded project OpenUP addresses key aspects and challenges of the currently transforming science landscape and aspires to come up with a cohesive framework for the review-disseminate-assess phases of the research life cycle that is fit to support and promote open science. The objective of this paper is to present first results and conclusions of the landscape scan and analysis of alternative peer review, altmetrics and innovative dissemination methods done during the first project year.

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2017

Görögh Edit, Toli Eleni, Kraker Peter

TIR @ DEXA International Conference on Database and Expert Systems Applications, 2017

Konferenz

The combination of different knowledge bases in thefield of information retrieval is called federated or aggregated search. It has several benefits over single source retrieval but poses some challenges as well. This work focuses on the challenge of result aggregation; especially in a setting where the final result list should include a certain degree of diversity and serendipity. Both concepts have been shown to have an impact on how user perceive an information retrieval system. In particular, we want to assess if common procedures for result list aggregation can be utilized to introduce diversity and serendipity. Furthermore, we study whether a blocking or interleaving for result aggregation yields better results. In a cross vertical aggregated search the so-called verticalscould be news, multimedia content or text. Block ranking is one approach to combine such heterogeneous result. It relies on the idea that these verticals are combined into a single result list as blocks of several adjacent items. An alternative approach for this is interleaving. Here the verticals are blended into one result list on an item by item basis, i.e. adjacent items in the result list may come from different verticals. To generate the diverse and serendipitous results we reliedon a query reformulation technique which we showed to be beneficial to generate diversified results in previous work. To conduct this evaluation we created a dedicated dataset. This dataset served as a basis for three different evaluation settings on a crowd sourcing platform, with over 300 participants. Our results show that query based diversification can be adapted to generate serendipitous results in a similar manner. Further, we discovered that both approaches, interleaving and block ranking, appear to be beneficial to introduce diversity and serendipity. Though it seems that queries either benefit from one approach or the other but not from both.

2017

Toller Maximilian, Kern Roman

Proceedings of the 2017 ACM International Symposium on Wearable Computers, ACM, Maui, Hawai, USA, 2017

Konferenz

This paper investigates sensitivity based prioritisation in the construction of tactile patterns. Our evidence is obtained by three studies using a wearable haptic display with vibrotactile motors (tactors). Haptic displays intended to transmit symbols often suffer the tradeoff between throughput and accuracy. For a symbol encoded with more than one tactor simultaneous onsets (spatial encoding) yields the highest throughput at the expense of the accuracy. Sequential onset increases accuracy at the expense of throughput. In the desire to overcome these issues, we investigate aspects of prioritisation based on sensitivity applied to the encoding of haptics patterns. First, we investigate an encoding method using mixed intensities, where different body locations are simultaneously stimulated with different vibration intensities. We investigate whether prioritising the intensity based on sensitivity improves identification accuracy when compared to simple spatial encoding. Second, we investigate whether prioritising onset based on sensitivity affects the identification of overlapped spatiotemporal patterns. A user study shows that this method significantly increases the accuracy. Furthermore, in a third study, we identify three locations on the hand that lead to an accurate recall. Thereby, we design the layout of a haptic display equipped with eight tactors, capable of encoding 36 symbols with only one or two locations per symbol.

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2017

Data Market Austria - Austria's First Digital Ecosystem for Data, Businesses, and Innovation

Exploring a changing view on organizing value creation: Developing New Business Models. Contributions to the 2nd International Conference on New Business Models, Institute of Systems Sciences, Innovation and Sustainability Research, Merangasse 18, 8010 Graz, Austria, Graz, 2017

Konferenz

New business opportunities in the digital economy are established when datasets describing a problem, data services solving the said problem, the required expertise and infrastructure come together. For most real-word problems finding the right data sources, services consulting expertise, and infrastructure is difficult, especially since the market players change often. The Data Market Austria (DMA) offers a platform to bring datasets, data services, consulting, and infrastructure offers to a common marketplace. The recommender systems included in DMA analyses all offerings, to derive suggestions for collaboration between them, like which dataset could be best processed by which data service. The suggestions should help the costumers on DMA to identify new collaborations reaching beyond traditional industry boundaries to get in touch with new clients or suppliers in the digital domain. Human brokers will work together with the recommender system to set up data value chains matching different offers to create a data value chain solving the problems in various domains. In its final expansion stage, DMA is intended to be a central hub for all actors participating in the Austrian data economy, regardless of their industrial and research domain to overcome traditional domain boundaries.

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2017

Lukas Sabine, Pammer-Schindler Viktoria, Almer Alexander, Schnabel Thomas

Process optimization based on a multi-level management system for forest fire situations.

Workshop Data-Driven Decision Support in Digitized Work Environments - i-Know Workshop 2017, 2017

Konferenz

Link

2017

Köfler Armin, Pammer-Schindler Viktoria, Almer Alexander, Schnabel Thomas

Supporting decision making in security forces’ command centre at large-scale events via videobased situation monitoring and base data supply - Extended Abstract

Workshop on Data-Driven Decision Support in Digitized Work Environments - i-Know Workshop 2017, Graz, 2017

Konferenz

Link

2017

d'Aquin Mathieu , Adamou Alessandro , Dietze Stefan , Fetahu Besnik , Gadiraju Ujwal , Hasani-Mavriqi Ilire, Holz Peter, Kümmerle Joachim, Kowald Dominik, Lex Elisabeth, Lopez Sola Susana, Mataran Ricardo, Sabol Vedran, Troullinou Pinelopi, Veas Eduardo, Veas Eduardo Enrique

AFEL: Towards Measuring Online Activities Contributions to Self-Directed Learning

7th Workshop on Awareness and Reflection in Technology Enhanced Learning (ARTEL 2017), Kravcik M., Mikroyannidis A., Pammer-Schindler V., Prilla M., CEUR-WS, Tallinn, Estonia, 2017

Konferenz

More and more learning activities take place online in a self-directed manner. Therefore, just as the idea of self-tracking activities for fitness purposes has gained momentum in the past few years, tools and methods for awareness and self-reflection on one's own online learning behavior appear as an emerging need for both formal and informal learners. Addressing this need is one of the key objectives of the AFEL (Analytics for Everyday Learning) project. In this paper, we discuss the different aspects of what needs to be put in place in order to enable awareness and self-reflection in online learning. We start by describing a scenario that guides the work done. We then investigate the theoretical, technical and support aspects that are required to enable this scenario, as well as the current state of the research in each aspect within the AFEL project. We conclude with a discussion of the ongoing plans from the project to develop learner-facing tools that enable awareness and self-reflection for online, self-directed learners. We also elucidate the need to establish further research programs on facets of self-tracking for learning that are necessarily going to emerge in the near future, especially regarding privacy and ethics.

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2017

Müller-Putz G. R., Ofner P., Schwarz Andreas, Pereira J., Luzhnica Granit, di Sciascio Maria Cecilia, Veas Eduardo Enrique, Stein Sebastian, Williamson John, Murray-Smith Roderick, Escolano C., Montesano L., Hessing B., Schneiders M., Rupp R.

Konferenz

Knowledge work such as summarizing related research inpreparation for writing, typically requires the extraction ofuseful information from scientific literature. Nowadays theprimary source of information for researchers comes fromelectronic documents available on the Web, accessible throughgeneral and academic search engines such as Google Scholaror IEEE Xplore. Yet, the vast amount of resources makesretrieving only the most relevant results a difficult task. Asa consequence, researchers are often confronted with loadsof low-quality or irrelevant content. To address this issuewe introduce a novel system, which combines a rich, inter-active Web-based user interface and different visualizationapproaches. This system enables researchers to identify keyphrases matching current information needs and spot poten-tially relevant literature within hierarchical document collec-tions. The chosen context was the collection and summariza-tion of related work in preparation for scientific writing, thusthe system supports features such as bibliography and citationmanagement, document metadata extraction and a text editor.This paper introduces the design rationale and components ofthe PaperViz. Moreover, we report the insights gathered in aformative design study addressing usability

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2017

Strohmaier David, di Sciascio Maria Cecilia, Errecalde Marcelo, Veas Eduardo Enrique

WikiLyzer: Interactive Information Quality Assessment in Wikipedia

ACM Intelligent User Interfaces, 2017

Konferenz

Innovations in digital libraries and services enable users to access large amounts of data on demand. Yet, quality assessment of information encountered on the Internet remains an elusive open issue. For example, Wikipedia, one of the most visited platforms on the Web, hosts thousands of user-generated articles and undergoes 12 million edits/contributions per month. User-generated content is undoubtedly one of the keys to its success, but also a hindrance to good quality: contributions can be of poor quality because everyone, even anonymous users, can participate. Though Wikipedia has defined guidelines as to what makes the perfect article, authors find it difficult to assert whether their contributions comply with them and reviewers cannot cope with the ever growing amount of articles pending review. Great efforts have been invested in algorith-mic methods for automatic classification of Wikipedia articles (as featured or non-featured) and for quality flaw detection. However, little has been done to support quality assessment of user-generated content through interactive tools that allow for combining automatic methods and human intelligence. We developed WikiLyzer, a toolkit comprising three Web-based interactive graphic tools designed to assist (i) knowledge discovery experts in creating and testing metrics for quality measurement , (ii) users searching for good articles, and (iii) users that need to identify weaknesses to improve a particular article. A case study suggests that experts are able to create complex quality metrics with our tool and a report in a user study on its usefulness to identify high-quality content.

2016

Thalmann Stefan, Manhart Markus

IEEEVis - Proc. IEEE Conference on Information Visualization, Baltimore, Maryland, USA, 2016

Konferenz

We present a new open-source prototype framework to exploreand visualize eye-tracking experiments data. Firstly, standard eyetrackersare used to record raw eye gaze data-points on user experiments.Secondly, the analyst can configure gaze analysis parameters,such as, the definition of areas of interest, multiple thresholdsor the labeling of special areas, and we upload the data to a searchserver. Thirdly, a faceted web interface for exploring and visualizingthe users’ eye gaze on a large number of areas of interest isavailable. Our framework integrates several common visualizationsand it also includes new combined representations like an eye analysisoverview and a clustered matrix that shows the attention timestrength between multiple areas of interest. The framework can bereadily used for the exploration of eye tracking experiments data.We make available the source code of our prototype framework foreye-tracking data analysis.

2016

Silva Nelson, Shao Lin, Schreck Tobias, Eggeling Eva, Fellner Dieter W.

Visual Exploration of Hierarchical Data Using Degree-of-Interest Controlled by Eye-Tracking

FMT 2016 : 9th Forum Media Technology 2016, Wolfgang Aigner , Grischa Schmiedl , Kerstin Blumenstein , Matthias Zeppelzauer , Michael Iber, St. Pölten, 2016

Konferenz

Effective visual exploration of large data sets is an important problem. A standard tech- nique for mapping large data sets is to use hierarchical data representations (trees, or dendrograms) that users may navigate. If the data sets get large, so do the hierar- chies, and effective methods for the naviga- tion are required. Traditionally, users navi- gate visual representations using desktop in- teraction modalities, including mouse interac- tion. Motivated by recent availability of low- cost eye-tracker systems, we investigate ap- plication possibilities to use eye-tracking for controlling the visual-interactive data explo- ration process. We implemented a proof-of- concept system for visual exploration of hier- archic data, exemplified by scatter plot dia- grams which are to be explored for grouping and similarity relationships. The exploration includes usage of degree-of-interest based dis- tortion controlled by user attention read from eye-movement behavior. We present the basic elements of our system, and give an illustra- tive use case discussion, outlining the applica- tion possibilities. We also identify interesting future developments based on the given data views and captured eye-tracking information. (13) Visual Exploration of Hierarchical Data Using Degree-of-Interest Controlled by Eye-Tracking. Available from: https://www.researchgate.net/publication/309479681_Visual_Exploration_of_Hierarchical_Data_Using_Degree-of-Interest_Controlled_by_Eye-Tracking [accessed Oct 3, 2017].

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2016

Berndt Rene, Silva Nelson, Edtmayr Thomas, Sunk Alexander, Krispel Ulrich, Caldera Christian, Eggeling Eva, Fellner Dieter W., Sihn Wilfried

Konferenz

Models describing human travel patterns are indispensable to plan and operate road, rail and public transportation networks. For most kind of analyses in the field of transportation planning, there is a need for origin-destination (OD) matrices, which specify the travel demands between the origin and destination zones in the network. The preparation of OD matrices is traditionally a time consuming and cumbersome task. The presented system, QZTool, reduces the necessary effort as it is capable of generating OD matrices automatically. These matrices are produced starting from floating phone data (FPD) as raw input. This raw input is processed by a Hadoop-based big data system. A graphical user interface allows for an easy usage and hides the complexity from the operator. For evaluation, we compare a FDP-based OD matrix to an OD matrix created by a traffic demand model. Results show that both matrices agree to a high degree, indicating that FPD-based OD matrices can be used to create new, or to validate or amend existing OD matrices.

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2016

Lindstaedt Stefanie , Ley Tobias, Klamma Ralf, Wild Fridolin

E-Learning Tag 2016, 2016

Konferenz

2016

Kern Roman, Klampfl Stefan, Rexha Andi

Identifying Referenced Text in ScientificPublications by Summarisation andClassification Techniques

BIRNDL 2016 Joint Workshop on Bibliometric-enhanced Information Retrieval and NLP for Digital Libraries, G. Cabanac, Muthu Kumar Chandrasekaran, Ingo Frommholz , Kokil Jaidka, Min-Yen Kan, Philipp Mayr, Dietmar Wolfram, ACM, New Jersey, USA, 2016

Konferenz

This report describes our contribution to the 2nd ComputationalLinguistics Scientific Document Summarization Shared Task (CLSciSumm2016), which asked to identify the relevant text span in a referencepaper that corresponds to a citation in another document that citesthis paper. We developed three different approaches based on summarisationand classification techniques. First, we applied a modified versionof an unsupervised summarisation technique, TextSentenceRank, to thereference document, which incorporates the similarity of sentences tothe citation on a textual level. Second, we employed classification to selectfrom candidates previously extracted through the original TextSentenceRankalgorithm. Third, we used unsupervised summarisation of therelevant sub-part of the document that was previously selected in a supervisedmanner.

Link

2016

Santos Tiago, Kern Roman

A Literature Survey of Early Time Series Classification and Deep Learning

SamI40 workshop at i-KNOW'16, 2016

Konferenz

This paper provides an overview of current literature on timeseries classification approaches, in particular of early timeseries classification.A very common and effective time series classification ap-proach is the 1-Nearest Neighbor classifier, with differentdistance measures such as the Euclidean or dynamic timewarping distances. This paper starts by reviewing thesebaseline methods.More recently, with the gain in popularity in the applica-tion of deep neural networks to the field of computer vision,research has focused on developing deep learning architec-tures for time series classification as well. The literature inthe field of deep learning for time series classification hasshown promising results.Early time series classification aims to classify a time se-ries with as few temporal observations as possible, whilekeeping the loss of classification accuracy at a minimum.Prominent early classification frameworks reviewed by thispaper include, but are not limited to, ECTS, RelClass andECDIRE. These works have shown that early time seriesclassification may be feasible and performant, but they alsoshow room for improvement

2016

Trattner Christoph, Kuśmierczyk Tomasz, Rokicki Markus, Herder Eelco

European Conference on Knowledge Management, Dr. Sandra Moffett and Dr. Brendan Galbraith, Academic Conferences and Publishing International Limited, Belfast, Northern Ireland, UK, 2016

Konferenz

Monitoring (social) media represents one means for companies to gain access to knowledge about, for instance, competitors, products as well as markets. As a consequence, social media monitoring tools have been gaining attention to handle amounts of data nowadays generated in social media. These tools also include summarisation services. However, most summarisation algorithms tend to focus on (i) first and last sentences respectively or (ii) sentences containing keywords.In this work we approach the task of summarisation by extracting 4W (who, when, where, what) information from (social)media texts. Presenting 4W information allows for a more compact content representation than traditional summaries. Inaddition, we depart from mere named entity recognition (NER) techniques to answer these four question types by includingnon-rigid designators, i.e. expressions which do not refer to the same thing in all possible worlds such as “at the main square”or “leaders of political parties”. To do that, we employ dependency parsing to identify grammatical characteristics for each question type. Every sentence is then represented as a 4W block. We perform two different preliminary studies: selecting sentences that better summarise texts by achieving an F1-measure of 0.343, as well as a 4W block extraction for which we achieve F1-measures of 0.932; 0.900; 0.803; 0.861 for “who”, “when”, “where” and “what” category respectively. In a next step the 4W blocks are ranked by relevance. The top three ranked blocks, for example, then constitute a summary of the entire textual passage. The relevance metric can be customised to the user’s needs, for instance, ranked by up-to-dateness where the sentences’ tense is taken into account. In a user study we evaluate different ranking strategies including (i) up-todateness,(ii) text sentence rank, (iii) selecting the firsts and lasts sentences or (iv) coverage of named entities, i.e. based on the number of named entities in the sentence. Our 4W summarisation method presents a valuable addition to a company’s(social) media monitoring toolkit, thus supporting decision making processes.

2016

Rexha Andi, Klampfl Stefan, Kröll Mark, Kern Roman

Towards a more fine grained analysis of scientific authorship: Predicting the number of authors using stylometric features

BIR 2016 Workshop on Bibliometric-enhanced Information Retrieval, Atanassova, I.; Bertin, M.; Mayr, P., Springer, Padova, Italy, 2016

Konferenz

To bring bibliometrics and information retrieval closer together, we propose to add the concept of author attribution into the pre-processing of scientific publications. Presently, common bibliographic metrics often attribute the entire article to all the authors affecting author-specific retrieval processes. We envision a more finegrained analysis of scientific authorship by attributing particular segments to authors. To realize this vision, we propose a new feature representation of scientific publications that captures the distribution of tylometric features. In a classification setting, we then seek to predict the number of authors of a scientific article. We evaluate our approach on a data set of ~ 6100 PubMed articles and achieve best results by applying random forests, i.e., 0.76 precision and 0.76 recall averaged over all classes.

Link

2016

Kowald Dominik, Lex Elisabeth, Kopeinik Simone

Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL

European Conference on Technology Enhanced Learning, EC-TEL'2016, Springer, Toledo, Spain, 2016

Konferenz

In recent years, a number of recommendation algorithmshave been proposed to help learners find suitable learning resources online.Next to user-centered evaluations, offline-datasets have been usedto investigate new recommendation algorithms or variations of collaborativefiltering approaches. However, a more extensive study comparinga variety of recommendation strategies on multiple TEL datasets ismissing. In this work, we contribute with a data-driven study of recommendationstrategies in TEL to shed light on their suitability forTEL datasets. To that end, we evaluate six state-of-the-art recommendationalgorithms for tag and resource recommendations on six empiricaldatasets: a dataset from European Schoolnets TravelWell, a dataset fromthe MACE portal, which features access to meta-data-enriched learningresources from the field of architecture, two datasets from the socialbookmarking systems BibSonomy and CiteULike, a MOOC dataset fromthe KDD challenge 2015, and Aposdle, a small-scale workplace learningdataset. We highlight strengths and shortcomings of the discussed recommendationalgorithms and their applicability to the TEL datasets.Our results demonstrate that the performance of the algorithms stronglydepends on the properties and characteristics of the particular dataset.However, we also find a strong correlation between the average numberof users per resource and the algorithm performance. A tag recommenderevaluation experiment reveals that a hybrid combination of a cognitiveinspiredand a popularity-based approach consistently performs best onall TEL datasets we utilized in our study.

Link

2016

Stanisavljevic Darko, Hasani-Mavriqi Ilire, Lex Elisabeth, Strohmaier M., Helic Denis

Semantic Stability in Wikipedia

Complex Networks and their Applications, Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A., Springer International Publishing AG, Cham, Switzerland, 2016

Konferenz

In this paper we assess the semantic stability of Wikipedia by investigat-ing the dynamics of Wikipedia articles’ revisions over time. In a semantically stablesystem, articles are infrequently edited, whereas in unstable systems, article contentchanges more frequently. In other words, in a stable system, the Wikipedia com-munity has reached consensus on the majority of articles. In our work, we measuresemantic stability using the Rank Biased Overlap method. To that end, we prepro-cess Wikipedia dumps to obtain a sequence of plain-text article revisions, whereaseach revision is represented as a TF-IDF vector. To measure the similarity betweenconsequent article revisions, we calculate Rank Biased Overlap on subsequent termvectors. We evaluate our approach on 10 Wikipedia language editions includingthe five largest language editions as well as five randomly selected small languageeditions. Our experimental results reveal that even in policy driven collaborationnetworks such as Wikipedia, semantic stability can be achieved. However, there aredifferences on the velocity of the semantic stability process between small and largeWikipedia editions. Small editions exhibit faster and higher semantic stability than large ones. In particular, in large Wikipedia editions, a higher number of successiverevisions is needed in order to reach a certain semantic stability level, whereas, insmall Wikipedia editions, the number of needed successive revisions is much lowerfor the same level of semantic stability.

Link

2016

Dennerlein_Bildungskarenz Sebastian, Gutounig Robert, Goldgruber Eva , Schweiger Stefan

Web 2.0 Messaging Tools for Knowledge Management? Exploring the Potentials of Slack

Proceedings of the 17th European Conference on Knowledge Management, Academic Conferences International Limited, Ulster University, Northern Ireland, 2016

Konferenz

There are many web-based tools like social networks, collaborative writing, or messaging tools that connectorganizations in accordance with web 2.0 principles. Slack is such a web 2.0 instant messaging tool. As per developer, itintegrates the entire communication, file-sharing, real-time messaging, digital archiving and search at one place. Usage inline with these functionalities would reflect expected appropriation, while other usage would account for unexpectedappropriation. We explored which factors of web 2.0 tools determine actual usage and how they affect knowledgemanagement (KM). Therefore, we investigated the relation between the three influencing factors, proposed tool utility fromdeveloper side, intended usage of key implementers, and context of application, to the actual usage in terms of knowledgeactivities (generate, acquire, organize, transfer and save knowledge). We conducted episodic interviews with keyimplementers in five different organizational contexts to understand how messaging tools affect KM by analyzing theappropriation of features. Slack was implemented with the intention to enable exchange between project teams, connectingdistributed project members, initiate a community of learners and establish a communication platform. Independent of thecontext, all key implementers agreed on knowledge transfer, organization and saving in accordance with Slack’s proposedutility. Moreover, results revealed that a usage intention of internal management does not lead to acquisition of externalknowledge, and usage intention of networking not to generation of new knowledge. These results suggest that it is not thecontext of application, but the intended usage that mainly affects the tool's efficacy with respect to KM: I.e. intention seemsto affect tool selection, first, explaining commonalities with respect to knowledge activities (expected appropriation) and,subsequently, intention also affects unexpected appropriation beyond the developers’ tool utility. A messaging tool is, hence,not only a messaging tool, but it is ‘what you make of it!’

2016

Gutounig Robert, Goldgruber Eva, Dennerlein_Bildungskarenz Sebastian, Schweiger Stefan

Mehr als ein Kommunikationstool. Wissensmanagement-Potenziale von Social Software am Beispiel von Slack

Kremser Wissensmanagement-Tagen 2016, Edition Donau-Universität Krems , Krems, 2016

Konferenz

2016

Kern Roman, Ziak Hermann

Query Splitting For Context-Driven Federated Recommendations

Database and Expert Systems Applications (DEXA), 2016 27th International Workshop on, IEEEE, Porto, Portugal, 2016

Konferenz

Context-driven query extraction for content-basedrecommender systems faces the challenge of dealing with queriesof multiple topics. In contrast to manually entered queries, forautomatically generated queries this is a more frequent problem. For instances if the information need is inferred indirectly viathe user's current context. Especially for federated search systemswere connected knowledge sources might react vastly differentlyon such queries, an algorithmic way how to deal with suchqueries is of high importance. One such method is to split mixedqueries into their individual subtopics. To gain insight how amulti topic query can be split into its subtopics we conductedan evaluation where we compared a naive approach against amore complex approaches based on word embedding techniques:One created using Word2Vec and one created using GloVe. Toevaluate these two approaches we used the Webis-QSeC-10 queryset, consisting of about 5,000 multi term queries. Queries of thisset were concatenated and passed through the algorithms withthe goal to split those queries again. Hence the naive approach issplitting the queries into several groups, according to the amountof joined queries, assuming the topics are of equal query termcount. In the case of the Word2Vec and GloVe based approacheswe relied on the already pre-trained datasets. The Google Newsmodel and a model trained with a Wikipedia dump and theEnglish Gigaword newswire text archive. The out of this datasetsresulting query term vectors were grouped into subtopics usinga k-Means clustering. We show that a clustering approach basedon word vectors achieves better results in particular when thequery is not in topical order. Furthermore we could demonstratethe importance of the underlying dataset.

Link

2016

Rexha Andi, Dragoni Mauro, Kern Roman, Kröll Mark

Proceedings of the 17th European Conference on Knowledge Management (ECKM), Dr. Sandra Moffett and Dr. Brendan Galbraith, Academic Conferences and Publishing International Limited, Belfast, Northern Ireland, UK, 2016

Konferenz

Modern knowledge workers need to interact with a large number of different knowledge sources with restricted or public access. Knowledge workers are thus burdened with the need to familiarise and query each source separately. The EEXCESS (Enhancing Europe’s eXchange in Cultural Educational and Scientific reSources) project aims at developing a recommender system providing relevant and novel content to its users. Based on the user’s work context, the EEXCESS system can either automatically recommend useful content, or support users by providing a single user interface for a variety of knowledge sources. In the design process of the EEXCESS system, recommendation quality, scalability and security where the three most important criteria. This paper investigates the scalability aspect achieved by federated design of the EEXCESS recommender system. This means that, content in different sources is not replicated but its management is done in each source individually. Recommendations are generated based on the context describing the knowledge worker’s information need. Each source offers result candidates which are merged and re-ranked into a single result list. This merging is done in a vector representation space to achieve high recommendation quality. To ensure security, user credentials can be set individually by each user for each source. Hence, access to the sources can be granted and revoked for each user and source individually. The scalable architecture of the EEXCESS system handles up to 100 requests querying up to 10 sources in parallel without notable performance deterioration. The re-ranking and merging of results have a smaller influence on the system's responsiveness than the average source response rates. The EEXCESS recommender system offers a common entry point for knowledge workers to a variety of different sources with only marginally lower response times as the individual sources on their own. Hence, familiarisation with individual sources and their query language is not necessary.

2015

Seitlinger Paul, Kowald Dominik, Kopeinik Simone, Hasani-Mavriqi Ilire, Ley Tobias, Lex Elisabeth

Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics

In 24rd International World Wide Web Conference, Web-Science Track, Aldo Gangemi, Stefano Leonardi and Alessandro Panconesi, ACM, Florence, 2015

Konferenz

Classic resource recommenders like Collaborative Filtering(CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and inter-pretation. In this paper, we propose a novel hybrid rec-ommendation strategy that re nes CF by capturing thesedynamics. The evaluation results reveal that our approachsubstantially improves CF and, depending on the dataset,successfully competes with a computationally much moreexpensive Matrix Factorization variant.

Link

2015

Veas Eduardo Enrique, Mutlu Belgin, di Sciascio Maria Cecilia, Tschinkel Gerwald, Sabol Vedran

Visual Recommendations for Scientific and Cultural Content

IVAPP 2015, Berlin, 2015

Konferenz

Supporting individuals who lack experience or competence to evaluate an overwhelming amout of informationsuch as from cultural, scientific and educational content makes recommender system invaluable to cope withthe information overload problem. However, even recommended information scales up and users still needto consider large number of items. Visualization takes a foreground role, letting the user explore possiblyinteresting results. It leverages the high bandwidth of the human visual system to convey massive amounts ofinformation. This paper argues the need to automate the creation of visualizations for unstructured data adaptingit to the user’s preferences. We describe a prototype solution, taking a radical approach considering bothgrounded visual perception guidelines and personalized recommendations to suggest the proper visualization.

Link

2015

Kraker Peter, Lex Elisabeth, Gorraiz Juan, Gumpenberger Christian, Peters Isabella

European Conference on Technology Enhanced Learning, Springer International Publishing, 2015

Konferenz

Sensemaking at the workplace and in educational contexts has beenextensively studied for decades. Interestingly, making sense out of the own wealthof learning experiences at the workplace has been widely ignored. To tackle thisissue, we have implemented a novel sensemaking interface for healthcare professionalsto support learning at the workplace. The proposed prototype supportsremembering of informal experiences from episodic memory followed by sensemakingin semantic memory. Results from an initial study conducted as part ofan iterative co-design process reveal the prototype is being perceived as usefuland supportive for informal sensemaking by study participants from the healthcaredomain. Furthermore, we find first evidence that re-evaluation of collectedinformation is a potentially necessary process that needs further exploration tofully understand and support sensemaking of informal learning experiences.

2015

Trattner Christoph, Parra Denis, Brusilovsky Peter, Marinho Leandro

Proceedings of 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) , London, 2015

Konferenz

Synchronisation algorithms are central components of collab- orative editing software. The energy efficiency for such algo- rithms becomes of interest to a wide community of mobile application developers. In this paper we explore the differen- tial synchronisation (diffsync) algorithm with respect to en- ergy consumption on mobile devices.We identify three areas for optimisation: a.) Empty cycles where diffsync is executed although no changes need to be processed b.) tail energy by adapting cycle intervals and c.) computational complexity. We propose a push-based diffsync strategy in which synchronisation cycles are triggered when a device connects to the network or when a device is notified of changes. Discussions within this paper are based on real usage data of PDF annotations via the Mendeley iOS app.

Link

2015

Die Informationsflut überblicken: Visualisierung von Wissensdomänen auf Basis von Co-Readership

IEEE STCSN-E-Letter, 2015

Konferenz

2015

The Social Semantic Server: A Flexible Framework to Support Informal Learning at the Workplace

ACM, In Proceeding of 15th International Conference on Knowledge Technologies and Data-driven Business, 2015

Konferenz

Informal learning at the workplace includes a multitude of processes. Respective activities can be categorized into multiple perspectives on informal learning, such as reflection, sensemaking, help seeking and maturing of collective knowledge. Each perspective raises requirements with respect to the technical support, this is why an integrated solution relying on social, adaptive and semantic technologies is needed. In this paper, we present the Social Semantic Server, an extensible, open-source application server that equips client-side tools with services to support and scale informal learning at the workplace. More specifically, the Social Semantic Server semantically enriches social data that is created at the workplace in the context of user-to-user or user-artifact interactions. This enriched data can then in turn be exploited in informal learning scenarios to, e.g., foster help seeking by recommending collaborators, resources, or experts. Following the design-based research paradigm, the Social Semantic Server has been implemented based on design principles, which were derived from theories such as Distributed Cognition and Meaning Making. We illustrate the applicability and efficacy of the Social Semantic Server in the light of three real-world applications that have been developed using its social semantic services. Furthermore, we report preliminary results of two user studies that have been carried out recently.

2015

Warum eine off ene Wissenschaft eine bürgerfreundliche Wissenschaft ist

oead.news, OeAD (Ã–sterreichische Austauschdienst), 2015

Konferenz

Proceedings of the 38th International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval, ACM, 2015

Konferenz

Link

2015

Hasani-Mavriqi Ilire, Geigl Florian, Pujari Subhash Chandra, Lex Elisabeth, Helic Denis

Influence of Status Social on Consensus Building in Collaboration Networks

In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), Jian Pei, Fabrizio Silvestri and Jie Tang, ACM/IEEE, Paris, France, 2015

Konferenz

In this paper, we analyze the influence of socialstatus on opinion dynamics and consensus building in collaborationnetworks. To that end, we simulate the diffusion of opinionsin empirical collaboration networks by taking into account boththe network structure and the individual differences of peoplereflected through their social status. For our simulations, weadapt a well-known Naming Game model and extend it withthe Probabilistic Meeting Rule to account for the social statusof individuals participating in a meeting. This mechanism issufficiently flexible and allows us to model various situations incollaboration networks, such as the emergence or disappearanceof social classes. In this work, we concentrate on studyingthree well-known forms of class society: egalitarian, ranked andstratified. In particular, we are interested in the way these societyforms facilitate opinion diffusion. Our experimental findingsreveal that (i) opinion dynamics in collaboration networks isindeed affected by the individuals’ social status and (ii) thiseffect is intricate and non-obvious. In particular, although thesocial status favors consensus building, relying on it too stronglycan slow down the opinion diffusion, indicating that there is aspecific setting for each collaboration network in which socialstatus optimally benefits the consensus building process.

Link

2015

Dennerlein_Bildungskarenz Sebastian, Kaiser René, Barreiros Carla, Gutounig Robert , Rauter Romana

Knowledge Strategies in Organisations – a Case for the Barcamp Format

Proceedings of the 16th European Conference on Knowledge Management, ACPI, Udine, Italy, 2015

Konferenz

Barcamps are events for open knowledge exchange. They are generally open to everyone, irrespective of background or discipline, and request no attendance fee. Barcamps are structured by only a small set of common rules and invite participants to an interactive and interdisciplinary discourse on an equal footing. In contrast to scientific conferences, the program is decided by the participants themselves on-site. Barcamps are often called un-conferences or ad-hoc conferences. Since barcamps are typically attended by people in their spare time, their motivation to actively engage and benefit from participating is very high. This paper presents a case study conducted at the annual Barcamp Graz in Austria. Within the case study, two field studies (quantitative and qualitative) and a parallel participant observation were carried out between 2010 and 2014. In these investigations we elaborated on the differences of the barcamp to scientific conferences, inferred characteristics of barcamps for knowledge generation, sharing and transfer in organizations and propose three usages of barcamps in organizations: further education of employees, internal knowledge transfer and getting outside knowledge in. Barcamps can be used as further education for employees enabling not only knowledge sharing, generation and transfer via the participating employees, but also for informally promoting a company’s competences. With respect to internal knowledge transfer, hierarchical boundaries can be temporarily broken by allowing informal and interactive discussion. This can lead to the elicitation of ‘hidden’ knowledge, knowledge transfer resulting in more efficient teamwork and interdepartmental cooperation. Finally, external stakeholders such as customers and partners can be included in this process to get outside knowledge in and identify customer needs, sketch first solutions and to start concrete projects. As a result of the case study, we hypothesise as a step towards further research that organisations can benefit from utilising this format as knowledge strategy.

Link

2015

Pammer-Schindler Viktoria, Bratic Marina, Feyertag Sandra, Faltin Nils

Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on, IEEE, 2015

Konferenz

uRankis a Web-based tool combining lightweight text analyticsand visual methods for topic-wise exploration of document sets.It includes a view summarizing the content of the document setin meaningful terms, a dynamic document ranking view and a de-tailed view for further inspection of individual documents. Its ma-jor strength lies in how it supports users in reorganizing documentson-the-fly as their information interests change. We present a pre-liminary evaluation showing that uRank helps to reduce cognitiveload compared to a traditional list-based representation.

2015

Scherer Reinhold, Schwarz Andreas , Müller-Putz G. R. , Pammer-Schindler Viktoria, Lloria Garcia Mariano

Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play (CHI Play 2015), 2014

Konferenz

Brain-computer interface (BCI) technology translatesbrain activity to machine-intelligible patterns, thusserving as input “device” to computers. BCI traininggames make the process of acquiring training data forthe machine learning more engaging for the users. Inthis work, we discuss the design space for BCI traininggames based on existing literature, and a traininggame in form of a Jigsaw Puzzle. The game wastrialled with four cerebral palsy patients. All patientswere very acceptant of the involved technology, which,we argue, relates back to the concept of BCI traininggames plus the adaptations we made. On the otherhand, the data quality was unsatisfactory. Hence, infuture work both concept and implementation need tobe finetuned to achieve a balance between useracceptance and data quality.

2014

Sabol Vedran, Tschinkel, Veas Eduardo Enrique, Mutlu Belgin, Granitzer Michael

Discovery and visual analysis of linked data for humans

International Semantic Web Conference, Springer, Cham, 2014

Konferenz

Linked Data has grown to become one of the largest availableknowledge bases. Unfortunately, this wealth of data remains inaccessi-ble to those without in-depth knowledge of semantic technologies. Wedescribe a toolchain enabling users without semantic technology back-ground to explore and visually analyse Linked Data. We demonstrateits applicability in scenarios involving data from the Linked Open DataCloud, and research data extracted from scientific publications. Our fo-cus is on the Web-based front-end consisting of querying and visuali-sation tools. The performed usability evaluations unveil mainly positiveresults confirming that the Query Wizard simplifies searching, refiningand transforming Linked Data and, in particular, that people using theVisualisation Wizard quickly learn to perform interactive analysis taskson the resulting Linked Data sets. In making Linked Data analysis ef-fectively accessible to the general public, our tool has been integratedin a number of live services where people use it to analyse, discover anddiscuss facts with Linked Data.

2014

Tschinkel Gerwald, Veas Eduardo Enrique, Mutlu Belgin, Sabol Vedran

Using semantics for interactive visual analysis of linked open data

Proceedings of the 2014 International Conference on Posters & Demonstrations Track-Volume 1272, CEUR-WS. org, 2014

Konferenz

Providing easy to use methods for visual analysis of LinkedData is often hindered by the complexity of semantic technologies. Onthe other hand, semantic information inherent to Linked Data providesopportunities to support the user in interactively analysing the data. Thispaper provides a demonstration of an interactive, Web-based visualisa-tion tool, the “Vis Wizard”, which makes use of semantics to simplify theprocess of setting up visualisations, transforming the data and, most im-portantly, interactively analysing multiple datasets using brushing andlinking method

2014

Granitzer MIchael, Veas Eduardo Enrique, Seifert C.

Linked Data Query Wizard: A Novel Interface for Accessing SPARQL Endpoints.

LDOW, 2014

Konferenz

In an interconnected world, Linked Data is more importantthan ever before. However, it is still quite di cult to accessthis new wealth of semantic data directly without havingin-depth knowledge about SPARQL and related semantictechnologies. Also, most people are currently used to consumingdata as 2-dimensional tables. Linked Data is by de -nition always a graph, and not that many people are used tohandle data in graph structures. Therefore we present theLinked Data Query Wizard, a web-based tool for displaying,accessing, ltering, exploring, and navigating Linked Datastored in SPARQL endpoints. The main innovation of theinterface is that it turns the graph structure of Linked Datainto a tabular interface and provides easy-to-use interactionpossibilities by using metaphors and techniques from currentsearch engines and spreadsheet applications that regular webusers are already familiar with.

2014

Silva Nelson, Settgast Volker, Eggeling Eva, Grill Florian, Zeh Theodor, Fellner Dieter W.

Sixth Sense - Air Traffic Control Prediction Scenario Augmented by Sensors

I-Know 2014, 2014

Konferenz

2014

Silva Nelson

The Sixth Sense in Air Traffic Control - Automated error detection through sensor augmentation, while keeping the humans in the main decision loop of ATC

I-Know 2014, 2014

Konferenz

2014

Mutlu Belgin, Tschinkel Gerwald, Veas Eduardo Enrique, Sabol Vedran, Stegmaier Florian, Granitzer Michael

Suggesting visualisations for published data

Information Visualization Theory and Applications (IVAPP), 2014 International Conference on, IEEE, 2014

Konferenz

Research papers are published in various digital libraries, which deploy their own meta-models and tech-nologies to manage, query, and analyze scientific facts therein. Commonly they only consider the meta-dataprovided with each article, but not the contents. Hence, reaching into the contents of publications is inherentlya tedious task. On top of that, scientific data within publications are hardcoded in a fixed format (e.g. tables).So, even if one manages to get a glimpse of the data published in digital libraries, it is close to impossibleto carry out any analysis on them other than what was intended by the authors. More effective querying andanalysis methods are required to better understand scientific facts. In this paper, we present the web-basedCODE Visualisation Wizard, which provides visual analysis of scientific facts with emphasis on automatingthe visualisation process, and present an experiment of its application. We also present the entire analyticalprocess and the corresponding tool chain, including components for extraction of scientific data from publica-tions, an easy to use user interface for querying RDF knowledge bases, and a tool for semantic annotation ofscientific data set

2014

Silva Nelson

ESWC 2013, LNCS 7882, P. Cimiano et al., Springer, Heidelberg, 2013

Konferenz

Linked Data has become an essential part of the Semantic Web. A lot of Linked Data is already available in the Linked Open Data cloud, which keeps growing due to an influx of new data from research and open government activities. However, it is still quite difficult to access this wealth of semantically enriched data directly without having in-depth knowledge about SPARQL and related semantic technologies. In this paper, we present the Linked Data Query Wizard, a prototype that provides a Linked Data interface for non-expert users, focusing on keyword search as an entry point and a tabular interface providing simple functionality for filtering and exploration.

Link

2013

Silva Nelson

The 6th Sense of an Air Traffic Controller Increasing Fault Tolerance of Human Machine Interfaces

SID 2013, 2013

Konferenz

2013

Tatzgern Markus, Grasset Raphael, Veas Eduardo Enrique, Kalkofen Denis, Schmalstieg Dieter

Exploring Distant Objects with Augmented Reality.

EGVE/EuroVR, 2013

Konferenz

Augmented reality (AR) enables users to retrieve additional information about the real world objects and locations.Exploring such location-based information in AR requires physical movement to different viewpoints, which maybe tiring and even infeasible when viewpoints are out of reach. In this paper, we present object-centric explorationtechniques for handheld AR that allow users to access information freely using a virtual copy metaphor to explorelarge real world objects. We evaluated our interfaces in controlled conditions and collected first experiences in areal world pilot study. Based on our findings, we put forward design recommendations that should be consideredby future generations of location-based AR browsers, 3D tourist guides, or in situated urban plannin

2011

Kraker Peter, Wagner Claudia, Jeanquartier Fleur, Lindstaedt Stefanie

On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection

Sixth European Conference on Technology Enhanced Learning (EC-TEL 2011), Springer, 2011

Konferenz

This paper presents an adaptable system for detecting trends based on the micro-blogging service Twitter, and sets out to explore to what extent such a tool can support researchers. Twitter has high uptake in the scientific community, but there is a need for a means of extracting the most important topics from a Twitter stream. There are too many tweets to read them all, and there is no organized way of keeping up with the backlog. Following the cues of visual analytics, we use visualizations to show both the temporal evolution of topics, and the relations between different topics. The Twitter Trend Detection was evaluated in the domain of Technology Enhanced Learning (TEL). The evaluation results indicate that our prototype supports trend detection but reveals the need for refined preprocessing, and further zooming and filtering facilities.

Link

2011

Kump Barbara, Knipfer Kristin, Pammer-Schindler Viktoria, Schmidt Andreas, Maier Ronald, Kunzmann Christine, Cress Ulrike, Lindstaedt Stefanie

The role of Reflection in Maturing Organizational Know-how

Proceedings of the 1st European Workshop on Awareness and Reflection in Learning Networks, Palermo, Italy, September 21, 2011, Reinhardt, W., Ullmann, T. D., Scott, P., Pammer, V., Conlan, O., Berlanga, A., 2011

Konferenz

The Knowledge Maturing Phase Model has been presented as a model aligning knowledge management and organizational learning. The core argument underlying the present paper is that maturing organizational knowhow requires individual and collaborative reflection at work. We present an explorative interview study that analyzes reflection at the workplace in four organizations in different European countries. Our qualitative findings suggest that reflection is not equally self-evident in different settings. A deeper analysis of the findings leads to the hypothesis that different levels of maturity of processes come along with different expectations towards the workers with regard to compliance and flexibility, and to different ways of how learning at work takes place. Furthermore, reflection in situations where the processes are in early maturing phases seems to lead to consolidation of best practice, while reflection in situations where processes are highly standardized may lead to a modification of these standard processes. Therefore, in order to support the maturing of organizational know-how by providing reflection support, one should take into account the degree of standardisation of the processes in the target group.

2011

Automatic detection of accommodation steps as an indicator of knowledge maturing (in-press)

Interacting with computers: the interdisciplinary journal of human-computer interaction, Murray, D. M., Elsevier B.V., 2011

Konferenz

Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants’ micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed.

Link

2010

Granitzer Michael, Kienreich Wolfgang

Konferenz

Link

2009

Pammer-Schindler Viktoria, Serafini L., Lindstaedt Stefanie

Highlighting assertional effects of ontology editing activities in OWL

Proceedings of the 3rd International Workshop on Ontology Dynamics, (IWOD 2009), collocated with the 8th International Semantic Web Conference (ISWC-2009), d'Acquin, M., Antoniou, G., CEUR Workshop Proceedings, 2009

Konferenz

Link

2009

Beham Günter, Lindstaedt Stefanie , Kump Barbara, Resanovic D.

GeoVisualization of Dynamics, Movement and Change Workshop at the AGILE 2008 Conference, Spain, 2008

Konferenz

Link

2008

Scharl A., Stern Hermann, Weichselbraun A.

Annotating and Visualizing Location Data in Geospatial Web Applications

17th International World Wide Web Conference (WWW-2008), Proceedings of the First International Workshop on Location and the Web (LocWeb 2008), 2008

Konferenz

This paper presents the IDIOM Media Watch on Climate Change (www.ecoresearch.net/climate), a prototypical implementation of an environmental portal that emphasizes the importance of location data for advanced Web applications. The introductory section outlines the process of retrofitting existing knowledge repositories with geographical context information, a process also referred to as geotagging. The paper then describes the portal’s functionality, which aggregates, annotates and visualizes environmental articles from 150 Anglo-American news media sites. From 300,000 news media articles gathered in weekly intervals, the system selects about 10,000 focusing on environmental issues. The crawled data is indexed and stored in a central repository. Geographic location represents a central aspect of the application, but not the only dimension used to organize and filter content. Applying the concepts of location and topography to semantic similarity, the paper concludes with discussing information landscapes as alternative interface metaphor for accessing large Web repositories.

Link

2008

Stocker A., Höfler Patrick, Granitzer Gisela, Willfort R., Köck Anna Maria, Pammer-Schindler Viktoria

Towards a Framework for Social Web Platforms: The Neurovation Case

Proceedings of the Third International Conference on Internet and Web Applications and Services (ICIW 2008), IEEE Computer Society Press, 2008

Konferenz

Social web platforms have become very popular in the so-called Web 2.0, and there is no end in sight. However, very few systematic models for the constitution of such sociotechnical infrastructures exist in the scientific literature. We therefore present a generic framework for building social web platforms based on the creation of value for individuals, communities and social networks. We applied this framework in the Neurovation project, aiming to establish a platform for creative knowledge workers. This paper describes work in progress and the lessons we have learned so far.

Link

2007

Strohmaier M., Lux M., Granitzer Michael, Scheir Peter, Liaskos S., Yu E.

How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search

We Know 07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE 07, , Nancy, France, 2007

Konferenz

Link

2006

Rath Andreas S., Kröll Mark, Andrews K., Lindstaedt Stefanie , Granitzer Michael

Synergizing Standard and Ad-Hoc Processes

Lecture Notes in Computer Science LNAI 4333, Springer Berlin, Berlin Heidelberg, 2006

Konferenz

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2005

Ley Tobias, Lindstaedt Stefanie , Albert D.

Supporting Competency Development in Informal Workplace Learning

Lecture Notes in Artificial Intelligence, Althoff, K.-D., Dengel, A., Bergmann, R., Nick, M., Roth-Berghofer, T., Springer, Heidelberg, 2005

Konferenz

This paper seeks to suggest ways to support informal, self-directed, work-integrated learning within organizations. We focus on a special type of learning in organizations, namely on competency development, that is a purposeful development of employee capabilities to perform well in a large array of situations. As competency development is inherently a self-directed development activity, we seek to support these activities primarily in an informal learning context. AD-HOC environments which allow employees context specific access to documents in a knowledge repository have been suggested to support learning in the workplace. In this paper, we suggest to use the competence performance framework as a means to enhance the capabilities of AD HOC environments to support competency development. The framework formalizes the tasks employees are working in and the competencies needed to perform the tasks. Relating tasks and competencies results in a competence performance structure, which structures both tasks and competencies in terms of learning prerequisites. We conclude with two scenarios that make use of methods established in informal learning research. The scenarios show how competence performance structures enhance feedback mechanisms in a coaching process between supervisor and employee and provide assistance for self directed learning from a knowledge repository.

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2004

Ley Tobias, Albert D.

Quality Criteria for Competency Assignments: Examples from a Project Management Case Study

Proceedings of Informatik 2004 - 34. Jahrestagung der Gesellschaft für Informatik, Gesellschaft für Informatik, Ulm/Germany, 2004

Konferenz

2004

Gissing B.

How to Develop a Knowledge Based Region?

Proceedings I-Know 2004, 4th International Conference on Knowledge Management, Springer, Graz, Austria, 2004

Konferenz

2004

Göstinger G., Puntschart I.

Proceedings of Electronic Imaging 2004, Internet Imaging V, San Jose, CA, USA, 2004

., Vienna Austria, 2002

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2002

Wissensretrieval und Wissensvisualisierung

to be Published in TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

Konferenz

2002

Riekert W.

Hypermedia im Umweltschutz: Ein Thema kommt an im Fachausschuss Informatik im Umweltschutz

Proceedings of the International Symposium on Environmental Informatics, Vienna Austria, 2002

Konferenz

2002

Ulbrich Armin, Ausserhofer A., Dietinger T., Raback W., Hoitsch P.

Presentational and Interactive Elements for eLearning Courses Considering Behavioral and Constructivist Learning Models

Poster/Demo at ED-Media 2002, Association for the Advancement of Computing in Education (AACE), Denver,USA, 2002

Konferenz

2002

Ley Tobias, Rollett H., Dösinger G., Bruhnsen K., Droschl G.

Proc. of Second International Workshop on User Interfaces to Data Intensive Systems (UIDIS 2001),, Zuric, Switzerland, 2001

Konferenz

The xFIND gatherer-broker architecture provides a wealth of metadata, which can be used to provide sophisticated search functionality. Local or remote documents are indexed and summaries and metadata are stored on an xFIND broker (server). An xFIND client can search a particular broker and access rich metadata for search result presentation, without having to fetch the original documents themselves. Search result sets are not only presented as a traditional ranked list, but also in an interactive scatterplot (Search Result Explorer) and using dynamic thematic clustering (VisIslands)

2001

Rollett H., Ley Tobias

Supporting knowledge creation: Towards a tool for explicating and sharing mental models

In D. Remenyi, editor, Proceedings of the Second European Conference on Knowledge Management, IEDC-Bled School of Management, Management Centre International Limited, Bled, Slovenia, 2001

Konferenz

2001

Ley Tobias, Rollett H.

Wissensmanagement, Management intellektuellen Kapitals und eLearning: Alleinstellungsmerkmale und Zusammenhänge

In Kurt Bauknecht, Wilfried Brauer, and Thomas Mück, editors, Informatik 2001, Tagungsband der GI/OCG-Jahrestagung, Ã–sterreichische Computer Gessellschaft, Wien, Austria, 2001

Konferenz

2000

Lindstaedt Stefanie

Globales Netz - Eine Revolution fuer alle Geschaeftsprozesse

Wirtschaftsforum, 2000

Konferenz

Fessl Angela, Thalmann Stefan

How to Manage Projects in a Foreign Language within Two Months: A Case Study

Konferenz

In times of globalization, also workforce needs to be able to go global. This holds true especially for technical experts holding an exclusive expertise. Together with a global manufacturing company, we addressed the challenge of being able to send staff into foreign countries for managing technical projects in the foreign language. We developed a socio-technical language learning concept that combines an online language learning platform with gamification features and conventional individual but virtually conducted coaching sessions. We report from a project we conducted with an international manufacturing company in which native Spanish speakers learned English within two months. The approach was tested in a four weeks trial with 10 participants. The target audience for this talk are HR-professionals, educational technologists and all people interested in language learning. We expect that our talk will spark discussions about the combination of ICT mediated learning and f-to-f learning in language learning and also about the role of gamification in this process.

Fessl Angela, Wertner Alfred, Pammer-Schindler Viktoria

Digging for Gold: Motivating Users to Explore Alternative Search Interfaces

Konferenz

In this demonstration paper, we describe a prototype that visualizes usage of different search interfaces on a single search platform with the goal to motivate users to explore alternative search interfaces. The underlying rationale is, that by now the one-line-input to search engines is so standard, that we can assume users’ search behavior to be operationalized. This means, that users may be reluctant to explore alternatives even though these may be suited better to their context of use / search task.

Divitini Monica, Lindstaedt Stefanie , Pammer-Schindler Viktoria, Ley Tobias

ECTEL meets ECSCW: Computer-Support for Integrated Working and Learning

ECSCW 2013 Adjunct Proceedings

Konferenz

With this workshop, we intend to bring together the European communities of technology-enhanced learning, which typically meets at the ECTEL, and of computersupported cooperative work, which typically meets at the ECSCW. While the ECTEL community has traditionally focused on technology support for learning, be it in formal learning environments like schools, universities, etc. or in informal learning environments like workplaces, the ECSCW community has traditionally investigated how computers can and do mediate and influence collaborative work, in settings as diverse as the typical “gainful employment” situations, project work within university courses, volunteer settings in NGOs etc. Despite overlapping areas of concerns, the two communities are also exploiting different theories and methodological approaches. Within this workshop, we discuss issues that are relevant for both communities, and have the potential to contribute to a more lively communication between both communities.

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