2018

Lovric Mario, Draženka Stipaničev, Siniša Repec, Olga Malev, Göran Klobučar

Companion Proceedings of the 27th International World Wide Web Conference, ACM, Lyon, France, 2018

Konferenz

In this paper, we present the results of an online study with the aim to shed light on the impact that semantic context cues have on the user acceptance of tag recommendations. Therefore, we conducted a work-integrated social bookmarking scenario with 17 university employees in order to compare the user acceptance of a context-aware tag recommendation algorithm called 3Layers with the user acceptance of a simple popularity-based baseline. In this scenario, we validated and verified the hypothesis that semantic context cues have a higher impact on the user acceptance of tag recommendations in a collaborative tagging setting than in an individual tagging setting. With this paper, we contribute to the sparse line of research presenting online recommendation studies.

Link

2018

Hasani-Mavriqi Ilire, Kowald Dominik, Helic Denis, Lex Elisabeth

Consensus Dynamics in Online Collaboration Systems

Journal of Computational Social Networks , Ding-Zhu Du and My T. Thai, Springer Open, 2018

Journal

In this paper, we study the process of opinion dynamics and consensus building inonline collaboration systems, in which users interact with each other followingtheir common interests and their social pro les. Speci cally, we are interested inhow users similarity and their social status in the community, as well as theinterplay of those two factors inuence the process of consensus dynamics. Forour study, we simulate the di usion of opinions in collaboration systems using thewell-known Naming Game model, which we extend by incorporating aninteraction mechanism based on user similarity and user social status. Weconduct our experiments on collaborative datasets extracted from the Web. Our ndings reveal that when users are guided by their similarity to other users, theprocess of consensus building in online collaboration systems is delayed. Asuitable increase of inuence of user social status on their actions can in turnfacilitate this process. In summary, our results suggest that achieving an optimalconsensus building process in collaboration systems requires an appropriatebalance between those two factors.

Link

2018

Lovric Mario, Krebs Sarah, Cemernek David, Kern Roman

BIG DATA IN INDUSTRIAL APPLICATION

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

Konferenz

The use of big data technologies has a deep impact on today’s research (Tetko et al., 2016) and industry (Li et al., n.d.), but also on public health (Khoury and Ioannidis, 2014) and economy (Einav and Levin, 2014). These technologies are particularly important for manufacturing sites, where complex processes are coupled with large amounts of data, for example in chemical and steel industry. This data originates from sensors, processes. and quality-testing. Typical application of these technologies is related to predictive maintenance and optimisation of production processes. Media makes the term “big data” a hot buzzword without going to deep into the topic. We noted a lack in user’s understanding of the technologies and techniques behind it, making the application of such technologies challenging. In practice the data is often unstructured (Gandomi and Haider, 2015) and a lot of resources are devoted to cleaning and preparation, but also to understanding causalities and relevance among features. The latter one requires domain knowledge, making big data projects not only challenging from a technical perspective, but also from a communication perspective. Therefore, there is a need to rethink the big data concept among researchers and manufacturing experts including topics like data quality, knowledge exchange and technology required. The scope of this presentation is to present the main pitfalls in applying big data technologies amongst users from industry, explain scaling principles in big data projects, and demonstrate common challenges in an industrial big data project

Link

2018

Urak Günter, Ziak Hermann, Kern Roman

Source Selection of Long Tail Sources for Federated Search in an Uncooperative Setting

SAC, 2018

Konferenz

The task of federated search is to combine results from multiple knowledge bases into a single, aggregated result list, where the items typically range from textual documents toimages. These knowledge bases are also called sources, and the process of choosing the actual subset of sources for a given query is called source selection. A scenario wherethese sources do not provide information about their content in a standardized way is called uncooperative setting. In our work we focus on knowledge bases providing long tail content, i.e., rather specialized sources offering a low number of relevant documents. These sources are often neglected in favor of more popular knowledge sources, both by today’s Web users as well as by most of the existing source selection techniques. We propose a system for source selection which i) could be utilized to automatically detect long tail knowledge bases and ii) generates aggregated search results that tend to incorporate results from these long tail sources. Starting from the current state-of-the-art we developed components that allowed to adjust the amount of contribution from long tail sources. Our evaluation is conducted on theTREC 2014 Federated WebSearch dataset. As this dataset also favors the most popular sources, systems that include many long tail knowledge bases will yield low performancemeasures. Here, we propose a system where just a few relevant long tail sources are integrated into the list of more popular knowledge bases. Additionally, we evaluated the implications of an uncooperative setting, where only minimal information of the sources is available to the federated search system. Here a severe drop in performance is observed once the share of long tail sources is higher than 40%. Our work is intended to steer the development of federated search systems that aim at increasing the diversity and coverage of the aggregated search result.

2018

Santos Tiago, Kern Roman

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

Pammer-Schindler Viktoria, Fessl Angela, Franz Weghofer, Thalmann Stefan

Lernen 4.0 Herausforderungen für Menschen in der Industrie 4.0 erfolgreich meistern.

Productivity, 2017

Journal

Die Digitalisierung der Industrie wird aktuell sehr stark aus technoogischer Sicht betrachtet. Aber auch für den Menschen ergebn sich vielfältige Herausforderungen in dieser veränderten Arbeitsumgebung. Sie betreffen hautsächlich das Lernen von benötigtem Wissen.

2017

Stabauer Petra, Breitfuß Gert, Lassnig Markus

Changing business models arising from digitalization. A best practice case study based on two Austrian companies

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

Topps David, Dennerlein Sebastian, Treasure-Jones Tamsin

Raising the BarCamp: international reflections

MedEdPublish, 2017

Journal

There is increasing interest in Barcamps and Unconferences as an educational approach during traditional medical education conferences. Ourgroup has now accumulated extensive experience in these formats over a number of years in different educational venues. We present asummary of observations and lessons learned about what works and what doesn’t.

Link

2017

Thalmann Stefan, Pammer-Schindler Viktoria

ACM, Graz, 2017

Konferenz

2017

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

Robust Parameter-Free Season Length Detection in Time Series

MILETS 2017 @ International Conference on Knowledge Discovery and Data Mining, Halfiax, Nova Scotia Canada, 2017

Konferenz

The in-depth analysis of time series has gained a lot of re-search interest in recent years, with the identification of pe-riodic patterns being one important aspect. Many of themethods for identifying periodic patterns require time series’season length as input parameter. There exist only a few al-gorithms for automatic season length approximation. Manyof these rely on simplifications such as data discretization.This paper presents an algorithm for season length detec-tion that is designed to be sufficiently reliable to be used inpractical applications. The algorithm estimates a time series’season length by interpolating, filtering and detrending thedata. This is followed by analyzing the distances betweenzeros in the directly corresponding autocorrelation function.Our algorithm was tested against a comparable algorithmand outperformed it by passing 122 out of 165 tests, whilethe existing algorithm passed 83 tests. The robustness of ourmethod can be jointly attributed to both the algorithmic ap-proach and also to design decisions taken at the implemen-tational level.

2017

Rexha Andi, Kröll Mark, Ziak Hermann, Kern Roman

Extending Scientific Literature Search by Including the Author’s Writing Style

Fifth Workshop on Bibliometric-enhanced Information Retrieval, Atanassova, I.; Bertin, M.; Mayr, P., Springer, Aberdeen, UK, 2017

Konferenz

Our work is motivated by the idea to extend the retrieval of related scientific literature to cases, where the relatedness also incorporates the writing style of individual scientific authors. Therefore we conducted a pilot study to answer the question whether humans can identity authorship once the topological clues have been removed. As first result, we found out that this task is challenging, even for humans. We also found some agreement between the annotators. To gain a better understanding how humans tackle such a problem, we conducted an exploratory data analysis. Here, we compared the decisions against a number of topological and stylometric features. The outcome of our work should help to improve automatic authorship identificationalgorithms and to shape potential follow-up studies.

Link

2017

Rexha Andi, Kröll Mark, Ziak Hermann, Kern Roman

Open Science Conference 2017, Berlin, 2017

Konferenz

Link

2017

Trattner Christoph, Elsweiler David

Investigating the Healthiness of Internet-Sourced Recipes

Proceedings of the 26th International Conference on World Wide Web, ACM, Perth, Australia, 2017

Konferenz

Food recommenders have the potential to positively in uence theeating habits of users. To achieve this, however, we need to understandhow healthy recommendations are and the factors whichin uence this. Focusing on two approaches from the literature(single item and daily meal plan recommendation) and utilizing alarge Internet sourced dataset from Allrecipes.com, we show howalgorithmic solutions relate to the healthiness of the underlyingrecipe collection. First, we analyze the healthiness of Allrecipes.comrecipes using nutritional standards from the World Health Organisationand the United Kingdom Food Standards Agency. Second,we investigate user interaction patterns and how these relate to thehealthiness of recipes. Third, we experiment with both recommendationapproaches. Our results indicate that overall the recipes inthe collection are quite unhealthy, but this varies across categorieson the website. Users in general tend to interact most often with theleast healthy recipes. Recommender algorithms tend to score popularitems highly and thus on average promote unhealthy items. Thiscan be tempered, however, with simple post- ltering approaches,which we show by experiment are better suited to some algorithmsthan others. Similarly, we show that the generation of meal planscan dramatically increase the number of healthy options open tousers. One of the main ndings is, nevertheless, that the utilityof both approaches is strongly restricted by the recipe collection.Based on our ndings we draw conclusions how researchers shouldattempt to make food recommendation systems promote healthynutrition.

Link

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.

2017

Gursch Heimo, Cemernek David, Kern Roman

Multi-Loop Feedback Hierarchy Involving Human Workers in Manufacturing Processes

Mensch und Computer 2017 - Workshopband, Manuel Burghardt, Raphael Wimmer, Christian Wolff, Christa Womser-Hacker, Gesellschaft für Informatik e.V., Regensburg, 2017

Konferenz

In manufacturing environments today, automated machinery works alongside human workers. In many cases computers and humans oversee different aspects of the same manufacturing steps, sub-processes, and processes. This paper identifies and describes four feedback loops in manufacturing and organises them in terms of their time horizon and degree of automation versus human involvement. The data flow in the feedback loops is further characterised by features commonly associated with Big Data. Velocity, volume, variety, and veracity are used to establish, describe and compare differences in the data flows.

Link

2017

Kraker Peter, Enkhbayar Asuraa, Schramm Maxi, Kittel Christopher, Chamberlain Scott, Skaug Mike , Brembs Björn

A Lifecycle Approach to Knowledge Excellence in the Biopharmaceutical Industry, Nuala Calnan, Martin J Lipa, Paige E. Kane, Jose C. Menezes, CRC Press, 2017

Buch

2017

Jorge Guerra, Carlos Catania, Veas Eduardo Enrique

Visual exploration of network hostile behavior

Proceedings of the 2017 ACM Workshop on Exploratory Search and Interactive Data Analytics, ACM, Limassol, Cyprus, 2017

Konferenz

This paper presents a graphical interface to identify hostilebehavior in network logs. The problem of identifying andlabeling hostile behavior is well known in the network securitycommunity. There is a lack of labeled datasets, which makeit difficult to deploy automated methods or to test the perfor-mance of manual ones. We describe the process of search-ing and identifying hostile behavior with a graphical tool de-rived from an open source Intrusion Prevention System, whichgraphically encodes features of network connections from alog-file. A design study with two network security expertsillustrates the workflow of searching for patterns descriptiveof unwanted behavior and labeling occurrences therewith.

Link

2017

Peter Mohr, David Mandl, Markus Tatzgern, Veas Eduardo Enrique, Dieter Schmalstieg, Denis Kalkofen

Retargeting Video Tutorials Showing Tools With Surface Contact to Augmented Reality

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, ACM, Denver, CO, USA, 2017

Konferenz

A video tutorial effectively conveys complex motions, butmay be hard to follow precisely because of its restriction toa predetermined viewpoint. Augmented reality (AR) tutori-als have been demonstrated to be more effective. We bringthe advantages of both together by interactively retargetingconventional, two-dimensional videos into three-dimensionalAR tutorials. Unlike previous work, we do not simply overlayvideo, but synthesize 3D-registered motion from the video.Since the information in the resulting AR tutorial is registeredto 3D objects, the user can freely change the viewpoint with-out degrading the experience. This approach applies to manystyles of video tutorials. In this work, we concentrate on aclass of tutorials which alter the surface of an object

Link

2017

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

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.

2016

Thalmann Stefan, Ilona Ilvonen, Markus Manhart, Christian Sillaber

Knowledge Protection for Digital Innovations: Integrating Six Perspectives

Proceedings of the 11th Pre-ICIS Workshop on Information Security and Privacy, AIS Electronic Library (AISeL), Dublin, Ireland, 2016

Konferenz

New ways of combining digital and physical innovations, as well as intensified inter-organizational collaborations, create new challenges to the protection of organizational knowledge. Existing research on knowledge protection is at an early stage and scattered among various research domains. This research-in-progress paper presents a plan for a structured literature review on knowledge protection, integrating the perspectives of the six base domains of knowledge, strategic, risk, intellectual property rights, innovation, and information technology security management. We define knowledge protection as a set of capabilities comprising and enforcing technical, organizational, and legal mechanisms to protect tacit and explicit knowledge necessary to generate or adopt innovations.

Link

2016

Trattner Christoph, Kuśmierczyk Tomasz, Rokicki Markus, Herder Eelco

Plate and Prejudice: Gender Differences in Online Cooking

UMAP 2016, ACM, Halifax, NS, Canada , 2016

Konferenz

Historically, there have always been differences in how men andwomen cook or eat. The reasons for this gender divide have mostlygone in Western culture, but still there is qualitative and anecdotalevidence that men prefer heftier food, that women take care of everydaycooking, and that men cook to impress. In this paper, weshow that these differences can also quantitatively be observed in alarge dataset of almost 200 thousand members of an online recipecommunity. Further, we show that, using a set of 88 features, thegender of the cooks can be predicted with fairly good accuracy of75%, with preference for particular dishes, the use of spices andthe use of kitchen utensils being the strongest predictors. Finally,we show the positive impact of our results on online food reciperecommender systems that take gender information into account.

2016

Thalmann Stefan, Markus Manhart

Balancing Knowledge Protection and Sharing in Networks of SME

Proceedings of IKNOW 2016, 2016

Konferenz

Organizations join networks to acquire external knowledge. This is especially important for SMEs since they often lack resources and are dependent on external knowledge to achieve and sustain competitive advantage. However, finding the right balance between measures facilitating knowledge sharing and measures protecting knowledge is a challenge. Whilst sharing is the raison d’être of networks, neglecting knowledge protection can be also detrimental to network, e.g., lead to one-sided skimming of knowledge. We identified four practices SMEs currently apply to balance protection of competitive knowledge and knowledge sharing in the network: (a) share in subgroups with high trust, (b) share partial aspects of the knowledge base, (c) share with people with low proximities, and (d) share common knowledge and protect the crucial. We further found that the application of the practices depends on the maturity of the knowledge. Further, we discuss how the practices relate to organizational protection capabilities and how the network can provide IT to support the development of these capabilities.

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

Trattner Christoph, Kuśmierczyk Tomasz, Nørvåg Kjetil

ACM WWW2016, ACM, Montreal, Canada, 2016

Buch

2016

Fessl Angela, Pammer-Schindler Viktoria, Blunk Oliver, Prilla Michael

The known universe of reflection guidance: a literature review

International Journal of Technology Enhanced Learning, Inderscience Enterprises Ltd., 2016

Journal

Reflective learning has been established as a process that deepenslearning in both educational and work-related settings. We present a literaturereview on various approaches and tools (e.g., prompts, journals, visuals)providing guidance for facilitating reflective learning. Research consideredin this review coincides common understanding of reflective learning, hasapplied and evaluated a tool supporting reflection and presents correspondingresults. Literature was analysed with respect to timing of reflection, reflectionparticipants, type of reflection guidance, and results achieved regardingreflection. From this analysis, we were able to derive insights, guidelinesand recommendations for the design of reflection guidance functionality incomputing systems: (i) ensure that learners understand the purpose of reflectivelearning, (ii) combine reflective learning tools with reflective questions either inform of prompts or with peer-to-peer or group discussions, (iii) for work-relatedsettings consider the time with regard to when and how to motivate to reflect.

2016

Rexha Andi, Kern Roman, Mauro Dragoni, Kröll Mark

Exploiting Propositions for Opinion Mining

ESWC-16 Challenge on Semantic Sentiment Analysis, Springer Link, Springer-Verlag, Crete, Greece, 2016

Konferenz

With different social media and commercial platforms, users express their opinion about products in a textual form. Automatically extracting the polarity (i.e. whether the opinion is positive or negative) of a user can be useful for both actors: the online platform incorporating the feedback to improve their product as well as the client who might get recommendations according to his or her preferences. Different approaches for tackling the problem, have been suggested mainly using syntactic features. The “Challenge on Semantic Sentiment Analysis” aims to go beyond the word-level analysis by using semantic information. In this paper we propose a novel approach by employing the semantic information of grammatical unit called preposition. We try to drive the target of the review from the summary information, which serves as an input to identify the proposition in it. Our implementation relies on the hypothesis that the proposition expressing the target of the summary, usually containing the main polarity information.

Link

2016

Gursch Heimo, Kern Roman

Internet of Things meets Big Data: An Infrastructure to Collect, Connect, and Analyse Sensor Data

VDE Kongress 2016: Internet der Dinge (VDE Kongress 2016), DE Verlag GmbH, Berlin - Offenbach, Congress Center Rosengarten, Mannheim, Germany, 2016

Konferenz

Many different sensing, recording and transmitting platforms are offered on today’s market for Internet of Things (IoT) applications. But taking and transmitting measurements is just one part of a complete system. Also long time storage and processing of recorded sensor values are vital for IoT applications. Big Data technologies provide a rich variety of processing capabilities to analyse the recorded measurements. In this paper an architecture for recording, searching, and analysing sensor measurements is proposed. This architecture combines existing IoT and Big Data technologies to bridge the gap between recording, transmission, and persistency of raw sensor data on one side, and the analysis of data on Hadoop clusters on the other side. The proposed framework emphasises scalability and persistence of measurements as well as easy access to the data from a variety of different data analytics tools. To achieve this, a distributed architecture is designed offering three different views on the recorded sensor readouts. The proposed architecture is not targeted at one specific use-case, but is able to provide a platform for a large number of different services.

2016

Rexha Andi, Kröll Mark, Kern Roman

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

Silva Nelson, Christian Caldera, Ulrich Krispel, Eva Eggeling, Alexander Sunk, Gerhard Reisinger, Wilfried Sihn, Dieter W. Fellner

VASCO - Digging the Dead Man's Chest of Value Streams

International Journal on Advances in Intelligent Systems, IARIA, 2016

Journal

Value stream mapping is a lean management method for analyzing and optimizing a series of events for production or services. Even today the ﬁrst step in value stream analysis – the acquisition of the current state map – is still created using pen & paper by physically visiting the production line. We capture a digital representation of how manufacturing processes look like in reality. The manufacturing processes can be represented and efﬁciently analyzed for future production planning as a future state map by using a meta description together with a dependency graph. With VASCO we present a tool, which contributes to all parts of value stream analysis - from data acquisition, over analyzing, planning, comparison up to simulation of alternative future state maps.We call this a holistic approach for Value stream mapping including detailed analysis of lead time, productivity, space, distance, material disposal, energy and carbon dioxide equivalents – depending in a change of calculated direct product costs.

Link

2016

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

Sense.me - Open Source Framework for the Exploration and Visualization of Eye Tracking Data

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

Gutounig Robert, Goldgruber Eva, Dennerlein 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

Konferenz

Highly optimised assembly lines are commonly used in various manufacturing domains, such as electronics, microchips, vehicles, electric appliances, etc. In the last decades manufacturers have installed software systems to control and optimise their shop foor processes. Machine Learning can enhance those systems by providing new insights derived from the previously captured data. This paper provides an overview of Machine Learning felds and an introduction to manufacturing management systems. These are followed by a discussion of research projects in the feld of applying Machine Learning solutions for condition monitoring, process control, scheduling, and predictive maintenance.

Link

2016

Santos Tiago, Kern Roman

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

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

Konferenz

The use of contexts –side information associated to information tasks– has been one ofthe most important dimensions for the improvement of Information Retrieval tasks, helpingto clarify the information needs of the users which usually start from a few keywords in atext box. Particularly, the social context has been leveraged in search and personalizationsince the inception of the Social Web, but even today we find new scenarios of informationfiltering, search, recommendation and personalization where the use of social signals canproduce a steep improvement. In addition, the action of searching has become a social processon the Web, making traditional assumptions of relevance obsolete and requiring newparadigms for matching the most useful resources that solve information needs. This escenariohas motivated us for organizing the Social Personalization and Search (SPS) workshop,a forum aimed at sharing and discussing research that leverage social data for improvingclassic personalization models for information access and to revisiting search from individualphenomena to a collaborative process.

2015

Parra D., Gomez M., Hutardo D., Wen X., Lin Y., Trattner Christoph

Twitter in academic events: {A} study of temporal usage, communication, and topical patterns in 16 Computer Science conferences

Computer Communications, Elsevier, 2015

Journal

Twitter is often referred to as a backchannel for conferences. While the main conference takes place in a physicalsetting, on-site and off-site attendees socialize, introduce new ideas or broadcast information by microblogging on Twitter.In this paper we analyze scholars’ Twitter usage in 16 Computer Science conferences over a timespan of five years. Ourprimary finding is that over the years there are differences with respect to the uses of Twitter, with an increase ofinformational activity (retweets and URLs), and a decrease of conversational usage (replies and mentions), which alsoimpacts the network structure – meaning the amount of connected components – of the informational and conversationalnetworks. We also applied topic modeling over the tweets’ content and found that when clustering conferences accordingto their topics the resulting dendrogram clearly reveals the similarities and differences of the actual research interests ofthose events. Furthermore, we also analyzed the sentiment of tweets and found persistent differences among conferences.It also shows that some communities consistently express messages with higher levels of emotions while others do it in amore neutral manner. Finally, we investigated some features that can help predict future user participation in the onlineTwitter conference activity. By casting the problem as a classification task, we created a model that identifies factors thatcontribute to the continuing user participation. Our results have implications for research communities to implementstrategies for continuous and active participation among members. Moreover, our work reveals the potential for the useof information shared on Twitter in order to facilitate communication and cooperation among research communities, byproviding visibility to new resources or researchers from relevant but often little known research communities.

Link

2015

Reinhold Scherer, Andreas Schwarz, Gernot Müller Putz, Pammer-Schindler Viktoria, Mariano Lloria Garcia

Game-based BCI training: Interactive design for individuals with cerebral palsy

IEEE International Conference on Systems, Man, Cybernetics 2015, 2015

Konferenz

Mutual brain-machine co-adaptation is the mostcommon approach used to gain control over spontaneouselectroencephalogram (EEG) based brain-computer interfaces(BCIs). Co-adaptation means the concurrent or alternating useof machine learning and the brain’s reinforcement learningmechanisms. Results from the literature, however, suggest thatcurrent implementations of this approach does not lead todesired results (“BCI inefficiency”). In this paper, we proposean alternative strategy that implements some recommendationsfrom educational psychology and instructional design. We presenta jigsaw puzzle game for Android devices developed to train theBCI skill in individuals with cerebral palsy (CP). Preliminaryresults of a supporting study in four CP users suggest high useracceptance. Three out of the four users achieved better thanchance accuracy in arranging pieces to form the puzzle.Index Terms—Brain-Computer Interface, Electroencephalo-gram, Human-Computer Interaction, Game-based learning,Cerebral palsy.

2015

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

The Value of Self-tracking and the Added Value of Coaching in the Case of Improving Time Management

Proceedings of the10th European Conference on Technology Enhanced Learning (ECTEL 2015), 2015

Konferenz

We report two 6-week studies, each with 10 participants, on improving time management. In each study a different interventions was administered, in parallel to otherwise regular work: In the self-tracking setting, participants used only an activity logging tool to track their time use and a reflective practice, namely daily review of time use, to improve time management. In the coaching setting, participants did the same, but additionally received weekly bilateral coaching. In both settings, participants reported learning about time management. This is encouraging, as such self-directed learning is clearly cheaper than coaching. Only participants in the coaching setting however improved their self-assessment with respect to predefined time management best practices. The Value of Self-tracking and the Added Value of Coaching in the Case of Improving Time Management. Available from: https://www.researchgate.net/publication/300259607_The_Value_of_Self-tracking_and_the_Added_Value_of_Coaching_in_the_Case_of_Improving_Time_Management [accessed Oct 24 2017].

2015

Kravcik Milos, Mikroyannidis Alexander, Pammer-Schindler Viktoria, Michael Prilla, Ullmann Thomas Daniel

Proceedings of the 5th Workshop on Awareness and Reflection in Technology Enhanced Learning. In conjunction with the 10th European Conference on Technology Enhanced Learning: Design for Teaching and Learning in a Networked World

ARTEL 2015 Awareness and Reflection in Technology Enhanced Learning , 2015

Buch

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, J., Gumpenberger, C., Peters, I.

Research Data Explored II: the Anatomy and Reception of figshare

n Proceedings of the 20th International Conference on Science and Technology Indicators (STI 2015), Lugano, Schweiz, 2015

Konferenz

Link

2015

Mutlu Belgin, Veas Eduardo Enrique, Trattner Christoph, Sabol Vedran

VizRec: A Two-Stage Recommender System for Personalized Visualizations

ACM IUI, ACM, Atlanta, Georgia, USA, 2015

Konferenz

Identifying and using the information from distributed and heterogeneous information sources is a challenging task in many application fields. Even with services that offer welldefined structured content, such as digital libraries, it becomes increasingly difficult for a user to find the desired information. To cope with an overloaded information space, we propose a novel approach – VizRec– combining recommender systems (RS) and visualizations. VizRec suggests personalized visual representations for recommended data. One important aspect of our contribution and a prerequisite for VizRec are user preferences that build a personalization model. We present a crowd based evaluation and show how such a model of preferences can be elicited.

Link

2015

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

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

Ley Tobias, Dennerlein Sebastian, Cook John, Kravcik Milos, Kunzmann Christine, Pata Kai, Purma Jukka, Sanders John, Santos Patricia , Schmidt Andreas, Al-Smadi Mohammad, Trattner Christoph

Scaling informal learning at the workplace: A model and four designs from a large‐scale design‐based research effort

British Journal of Educational Technology, 2014

Workplace learning happens in the process and context of work, is multi-episodic, often informal, problem based and takes place on a just-in-time basis. While this is a very effective means of delivery, it also does not scale very well beyond the immediate context. We review three types of technologies that have been suggested to scale learning and three connected theoretical discourses around learning and its support. Based on these three strands and an in-depth contextual inquiry into two workplace learning domains, health care and building and construction, four design-based research projects were conducted that have given rise to designs for scaling informal learning with technology. The insights gained from the design and contextual inquiry contributed to a model that provides an integrative view on three informal learning processes at work and how they can be supported with technology: (1) task performance, reflection and sensemaking; (2) help seeking, guidance and support; and (3) emergence and maturing of collective knowledge. The model fosters our understanding of how informal learning can be scaled and how an orchestrated set of technologies can support this process.

2014

MIchael Granitzer, Veas Eduardo Enrique, Christin Seifert

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

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

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

Rauch Manuela, Wozelka Ralph, Veas Eduardo Enrique, Sabol Vedran

Semantic Blossom Graph: A new Approach for Visual Graph Exploration

SID 2013, 2013

Konferenz

2013

Dennerlein Sebastian, Gutounig Robert, Kraker Peter, Kaiser René, Rauter Romana , Ausserhofer Julian

Assessing Barcamps: Incentives for Participation in Ad-hoc Conferences and the Role of Social Media

Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies, ACM, 2013

Barcamps are informal conferences whose content is not de-fined in advance, often referred to as ad-hoc conferences orun-conferences. Therefore, the outcomes of a barcamp arelargely unknown before the event. This raises the question ofthe participants’ motivations to attend and contribute. Toanswer this question, we conducted an exploratory empiricalstudy at Barcamp Graz 2012. We applied a mixed-methodapproach: first we used a socio-demographic questionnaire(n=99) which allowed us to characterize the ’typical barcamper’.Second, we conducted qualitative interviews (n=10) toget a deeper understanding of the participants’ motivationsto attend, expectations, and the use of social media in thatcontext. We identified three concepts, which could be deductedfrom the interviews: people, format and topics. Wefound that the motivation to attend and even a commonidentity is quite strongly based on these three factors. Furthermore,the results indicate that participants share a set ofactivities and methods by following the barcamp’s inherentrules and make extensive use of social media.

2013

Cook John, Santos Patricia, Ley Tobias, Dennerlein Sebastian, Pata Kai, Colley Joanna, Sandars John, Treasure-Jones Tasmin

European Conference on Technology Enhanced Learning, Springer Berlin Heidelberg, 2013

While several technological advances have been suggested to scale learning at the workplace, none has been successful to scale informal learning. We review three theoretical discourses and suggest an integrated systems model of scaffolding informal workplace learning that has been created to tackle this challenge. We derive research questions that emerge from this model and illustrate these with an in-depth analysis of two workplace learning domains.

Wertner Alfred, Stern Hermann, Weghofer Franz, Pammer-Schindler_TU Viktoria

Talk2Me – Sprachgesteuerte Kommissionierung mit off-the-shelf Hardware

Buch

Sprachsteuerung stellt ein potentiell sehr mächtiges Werkzeug dar und sollte rein von der Theorie (grundlegende Spracheingabe) her schon seit 20 Jahren einsetzbar sein. Sie ist in der Vergangenheit im industriellen Umfeld jedoch primär an nicht ausgereifter Hardware oder gar der Notwendigkeit einer firmenexternen aktiven Datenverbindung gescheitert. Bei Magna Steyr am Standort Graz wird die Kommissionierung bisher mit Hilfe von Scan-nern erledigt. Dieser Prozess ließe sich sehr effektiv durch eine durchgängige Sprachsteue-rung unterstützen, wenn diese einfach, zuverlässig sowie Compliance-konform umsetzbar wäre und weiterhin den Menschen als zentralen Mittelpunkt und Akteur (Stichwort Hu-man in the Loop) verstehen würde. Daher wurden bestehende Spracherkennungssysteme für mobile Plattformen sowie passende „off the shelf“ Hardware (Smartphones und Headsets) ausgewählt und prototypisch als Android Applikation („Talk2Me“) umgesetzt. Ziel war es, eine Aussage über die Einsetzbarkeit von sprachgesteuerten mobilen Anwen-dungen im industriellen Umfeld liefern zu können.Mit dem Open Source Speech Recognition Kit CMU Sphinx in Kombination mit speziell auf das Vokabular der abgebildeten Prozesse angepassten Wörterbüchern konnten wir eine sehr gute Erkennungsrate erreichen ohne das Sprachmodell individuell auf einzelne Mitar-beiterInnen trainieren zu müssen. Talk2Me zeigt innovativ, wie erprobte, kostengünstige und verfügbare Technologie (Smartphones und Spracherkennung als Eingabe sowie Sprachsynthese als Ausgabe) Ein-zug in unseren Arbeitsalltag haben kann.