17 research outputs found
Geographic information extraction from texts
A large volume of unstructured texts, containing valuable geographic information, is available online. This information â provided implicitly or explicitly â is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction
Thinking outside the graph: scholarly knowledge graph construction leveraging natural language processing
Despite improved digital access to scholarly knowledge in recent decades, scholarly communication remains exclusively document-based.
The document-oriented workflows in science publication have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis.
In this form, scientific knowledge remains locked in representations that are inadequate for machine processing.
As long as scholarly communication remains in this form, we cannot take advantage of all the advancements taking place in machine learning and natural language processing techniques.
Such techniques would facilitate the transformation from pure text based into (semi-)structured semantic descriptions that are interlinked in a collection of big federated graphs.
We are in dire need for a new age of semantically enabled infrastructure adept at storing, manipulating, and querying scholarly knowledge.
Equally important is a suite of machine assistance tools designed to populate, curate, and explore the resulting scholarly knowledge graph.
In this thesis, we address the issue of constructing a scholarly knowledge graph using natural language processing techniques.
First, we tackle the issue of developing a scholarly knowledge graph for structured scholarly communication, that can be populated and constructed automatically.
We co-design and co-implement the Open Research Knowledge Graph (ORKG), an infrastructure capable of modeling, storing, and automatically curating scholarly communications.
Then, we propose a method to automatically extract information into knowledge graphs.
With Plumber, we create a framework to dynamically compose open information extraction pipelines based on the input text.
Such pipelines are composed from community-created information extraction components in an effort to consolidate individual research contributions under one umbrella.
We further present MORTY as a more targeted approach that leverages automatic text summarization to create from the scholarly article's text structured summaries containing all required information.
In contrast to the pipeline approach, MORTY only extracts the information it is instructed to, making it a more valuable tool for various curation and contribution use cases.
Moreover, we study the problem of knowledge graph completion.
exBERT is able to perform knowledge graph completion tasks such as relation and entity prediction tasks on scholarly knowledge graphs by means of textual triple classification.
Lastly, we use the structured descriptions collected from manual and automated sources alike with a question answering approach that builds on the machine-actionable descriptions in the ORKG.
We propose JarvisQA, a question answering interface operating on tabular views of scholarly knowledge graphs i.e., ORKG comparisons.
JarvisQA is able to answer a variety of natural language questions, and retrieve complex answers on pre-selected sub-graphs.
These contributions are key in the broader agenda of studying the feasibility of natural language processing methods on scholarly knowledge graphs, and lays the foundation of which methods can be used on which cases.
Our work indicates what are the challenges and issues with automatically constructing scholarly knowledge graphs, and opens up future research directions
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User Experience for Elephants: Researching Interactive Enrichment through Design and Craft
This thesis explores the challenge for humans of designing and crafting interactive enrichment systems for elephants housed in captivity.
Captive elephants may have limited opportunity to express a full range of natural behaviours and therefore benefit from well-designed environmental enrichment. We asked whether technology could support the design and development of novel enrichment for elephants and investigated what kinds of technology-enabled systems would hold their interest. Crucially, these systems were designed to provide the elephants with opportunities to make and enact choices â giving them more control over what happened in their environment.
After researching wild elephant lifestyle and characteristics, our fieldwork started with an ethnographic study of captive elephants. We then followed an exploratory approach: Research through Design and Craft. Over several years, a range of interactive systems were crafted for elephants. Each device included embedded technology that enabled elephant interactions to be captured and mapped to associated system outputs. Elephants and their keepers were involved in this cyclical process, and the elephantsâ reactions to the devices were noted and interpreted, giving rise to insights that informed the subsequent designs.
Analysis of the design and development of the enrichment systems revealed important interface attributes and design considerations that we describe in this document. Finally, we offer five contributions for the ACI community: (i) Research through Design and Craft methodology, which was developed and tested over several years; (ii) ZooJam workshops, which were organised with colleagues over three years; (iii) six key principles of interaction design for ACI development â consistency, differentiation, graduation, specificity, multiplicity and affordance; (iv) an exploration of More than Human Aesthetics focusing on performative aesthetics; (v) a prototype deck of Concept Craft Cards that share theoretical and practical topics with other designers and developers
Usability analysis of contending electronic health record systems
In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe
Re-examining and re-conceptualising enterprise search and discovery capability: towards a model for the factors and generative mechanisms for search task outcomes.
Many organizations are trying to re-create the Google experience, to find and exploit their own corporate information. However, there is evidence that finding information in the workplace using search engine technology has remained difficult, with socio-technical elements largely neglected in the literature. Explication of the factors and generative mechanisms (ultimate causes) to effective search task outcomes (user satisfaction, search task performance and serendipitous encountering) may provide a first step in making improvements. A transdisciplinary (holistic) lens was applied to Enterprise Search and Discovery capability, combining critical realism and activity theory with complexity theories to one of the worlds largest corporations. Data collection included an in-situ exploratory search experiment with 26 participants, focus groups with 53 participants and interviews with 87 business professionals. Thousands of user feedback comments and search transactions were analysed. Transferability of findings was assessed through interviews with eight industry informants and ten organizations from a range of industries. A wide range of informational needs were identified for search filters, including a need to be intrigued. Search term word co-occurrence algorithms facilitated serendipity to a greater extent than existing methods deployed in the organization surveyed. No association was found between user satisfaction (or self assessed search expertise) with search task performance and overall performance was poor, although most participants had been satisfied with their performance. Eighteen factors were identified that influence search task outcomes ranging from user and task factors, informational and technological artefacts, through to a wide range of organizational norms. Modality Theory (Cybersearch culture, Simplicity and Loss Aversion bias) was developed to explain the study observations. This proposes that at all organizational levels there are tendencies for reductionist (unimodal) mind-sets towards search capability leading to fixes that fail. The factors and mechanisms were identified in other industry organizations suggesting some theory generalizability. This is the first socio-technical analysis of Enterprise Search and Discovery capability. The findings challenge existing orthodoxy, such as the criticality of search literacy (agency) which has been neglected in the practitioner literature in favour of structure. The resulting multifactorial causal model and strategic framework for improvement present opportunities to update existing academic models in the IR, LIS and IS literature, such as the DeLone and McLean model for information system success. There are encouraging signs that Modality Theory may enable a reconfiguration of organizational mind-sets that could transform search task outcomes and ultimately business performance
Sketchography - Automatic Grading of Map Sketches for Geography Education
Geography is a vital classroom subject that teaches students about the physical features of the planet we live on. Despite the importance of geographic knowledge, almost 75% of 8th graders scored below proficient in geography on the 2014 National Assessment of Educational Progress. Sketchography is a pen-based intelligent tutoring system that provides real-time feedback to students learning the locations, directions, and topography of rivers around the world. Sketchography uses sketch recognition and artificial intelligence to understand the userâs sketched intentions. As sketches are inherently messy, and even the most expert geographer will draw only a close approximation of the riverâs flow, data has been gathered from both novice and expert sketchers. This data, in combination with professorsâ grading rubrics and statistically driving AI-algorithms, provide real-time automatic grading that is similar to a human graderâs score. Results show the system to be 94.64% accurate compared to human grading
Exploratory information searching in the enterprise: A study of user satisfaction and task performance
No prior research has been identified which investigates the causal factors for workplace exploratory search task performance. The impact of user, task and environmental factors on user satisfaction and task performance was investigated through a mixed methods study with 26 experienced information professionals using enterprise search in an oil and gas enterprise. Some participants found 75% of high value items, others found none with an average of 27%. No association was found between self-reported search expertise and task performance, with a tendency for many participants to overestimate their search expertise. Successful searchers may have more accurate mental models of both search systems and the information space. Organizations may not have effective exploratory search task performance feedback loops, a lack of learning. This may be caused by management bias towards technology not capability, a lack of systems thinking. Furthermore, organizations may not âknowâ they âdonât knowâ their true level of search expertise, a lack of knowing. A metamodel is presented identifying the causal factors for workplace exploratory search task performance. Semi-structured qualitative interviews with search staff from the Defence, Pharmaceutical and Aerospace sectors indicates the potential transferability of the finding that organizations may not know their search expertise levels
Automotive user interfaces for the support of non-driving-related activities
Driving a car has changed a lot since the first car was invented. Today, drivers do not only maneuver the car to their destination but also perform a multitude of additional activities in the car. This includes for instance activities related to assistive functions that are meant to increase driving safety and reduce the driverâs workload. However, since drivers spend a considerable amount of time in the car, they often want to perform non-driving-related activities as well. In particular, these activities are related to entertainment, communication, and productivity. The driverâs need for such activities has vastly increased, particularly due to the success of smart phones and other mobile devices. As long as the driver is in charge of performing the actual driving task, such activities can distract the driver and may result in severe accidents. Due to these special requirements of the driving environment, the driver ideally performs such activities by using appropriately designed in-vehicle systems. The challenge for such systems is to enable flexible and easily usable non-driving-related activities while maintaining and increasing driving safety at the same time.
The main contribution of this thesis is a set of guidelines and exemplary concepts for automotive user interfaces that offer safe, diverse, and easy-to-use means to perform non-driving-related activities besides the regular driving tasks. Using empirical methods that are commonly used in human-computer interaction, we investigate various aspects of automotive user interfaces with the goal to support the design and development of future interfaces that facilitate non-driving-related activities. The first aspect is related to using physiological data in order to infer information about the driverâs workload. As a second aspect, we propose a multimodal interaction style to facilitate the interaction with multiple activities in the car. In addition, we introduce two concepts for the support of commonly used and demanded non-driving-related activities: For communication with the outside world, we investigate the driverâs needs with regard to sharing ride details with remote persons in order to increase driving safety. Finally, we present a concept of time-adjusted activities (e.g., entertainment and productivity) which enable the driver to make use of times where only little attention is required. Starting with manual, non-automated driving, we also consider the rise of automated driving modes.When cars were invented, they allowed the driver and potential passengers to get to a distant location. The only activities the driver was able and supposed to perform were related to maneuvering the vehicle, i.e., accelerate, decelerate, and steer the car. Today drivers perform many activities that go beyond these driving tasks. This includes for example activities related to driving assistance, location-based information and navigation, entertainment, communication, and productivity. To perform these activities, drivers use functions that are provided by in-vehicle information systems in the car. Many of these functions are meant to increase driving safety or to make the ride more enjoyable. The latter is important since people spend a considerable amount of time in their cars and want to perform similar activities like those to which they are accustomed to from using mobile devices. However, as long as the driver is responsible for driving, these activities can be distracting and pose driver, passengers, and the environment at risk. One goal for the development of automotive user interfaces is therefore to enable an easy and appropriate operation of in-vehicle systems such that driving tasks and non-driving-related activities can be performed easily and safely.
The main contribution of this thesis is a set of guidelines and exemplary concepts for automotive user interfaces that offer safe, diverse, and easy-to-use means to perform also non-driving-related activities while driving. Using empirical methods that are commonly used in human-computer interaction, we approach various aspects of automotive user interfaces in order to support the design and development of future interfaces that also enable non-driving-related activities. Starting with manual, non-automated driving, we also consider the transition towards automated driving modes.
As a first part, we look at the prerequisites that enable non-driving-related activities in the car. We propose guidelines for the design and development of automotive user interfaces that also support non-driving-related activities. This includes for instance rules on how to adapt or interrupt activities when the level of automation changes. To enable activities in the car, we propose a novel interaction concept that facilitates multimodal interaction in the car by combining speech interaction and touch gestures. Moreover, we reveal aspects on how to infer information about the driver's state (especially mental workload) by using physiological data. We conducted a real-world driving study to extract a data set with physiological and context data. This can help to better understand the driver state, to adapt interfaces to the driver and driving situations, and to adapt the route selection process.
Second, we propose two concepts for supporting non-driving-related activities that are frequently used and demanded in the car. For telecommunication, we propose a concept to increase driving safety when communicating with the outside world. This concept enables the driver to share different types of information with remote parties. Thereby, the driver can choose between different levels of details ranging from abstract information such as ``Alice is driving right now'' up to sharing a video of the driving scene. We investigated the drivers' needs on the go and derived guidelines for the design of communication-related functions in the car through an online survey and in-depth interviews. As a second aspect, we present an approach to offer time-adjusted entertainment and productivity tasks to the driver. The idea is to allow time-adjusted tasks during periods where the demand for the driver's attention is low, for instance at traffic lights or during a highly automated ride. Findings from a web survey and a case study demonstrate the feasibility of this approach.
With the findings of this thesis we envision to provide a basis for future research and development in the domain of automotive user interfaces and non-driving-related activities in the transition from manual driving to highly and fully automated driving.Als das Auto erfunden wurde, ermöglichte es den Insassen hauptsĂ€chlich, entfernte Orte zu erreichen. Die einzigen TĂ€tigkeiten, die Fahrerinnen und Fahrer wĂ€hrend der Fahrt erledigen konnten und sollten, bezogen sich auf die Steuerung des Fahrzeugs. Heute erledigen die Fahrerinnen und Fahrer diverse TĂ€tigkeiten, die ĂŒber die ursprĂŒnglichen Aufgaben hinausgehen und sich nicht unbedingt auf die eigentliche Fahraufgabe beziehen. Dies umfasst unter anderem die Bereiche Fahrerassistenz, standortbezogene Informationen und Navigation, Unterhaltung, Kommunikation und ProduktivitĂ€t. Informationssysteme im Fahrzeug stellen den Fahrerinnen und Fahrern Funktionen bereit, um diese Aufgaben auch wĂ€hrend der Fahrt zu erledigen. Viele dieser Funktionen verbessern die Fahrsicherheit oder dienen dazu, die Fahrt angenehm zu gestalten. Letzteres wird immer wichtiger, da man inzwischen eine betrĂ€chtliche Zeit im Auto verbringt und dabei nicht mehr auf die AktivitĂ€ten und Funktionen verzichten möchte, die man beispielsweise durch die Benutzung von Smartphone und Tablet gewöhnt ist. Solange der Fahrer selbst fahren muss, können solche AktivitĂ€ten von der FahrtĂ€tigkeit ablenken und eine GefĂ€hrdung fĂŒr die Insassen oder die Umgebung darstellen. Ein Ziel bei der Entwicklung automobiler Benutzungsschnittstellen ist daher eine einfache, adĂ€quate Bedienung solcher Systeme, damit Fahraufgabe und NebentĂ€tigkeiten gut und vor allem sicher durchgefĂŒhrt werden können.
Der Hauptbeitrag dieser Arbeit umfasst einen Leitfaden und beispielhafte Konzepte fĂŒr automobile Benutzungsschnittstellen, die eine sichere, abwechslungsreiche und einfache DurchfĂŒhrung von TĂ€tigkeiten jenseits der eigentlichen Fahraufgabe ermöglichen. Basierend auf empirischen Methoden der Mensch-Computer-Interaktion stellen wir verschiedene Lösungen vor, die die Entwicklung und Gestaltung solcher Benutzungsschnittstellen unterstĂŒtzen. Ausgehend von der heute ĂŒblichen nicht automatisierten Fahrt betrachten wir dabei auch Aspekte des automatisierten Fahrens.
ZunĂ€chst betrachten wir die notwendigen Voraussetzungen, um TĂ€tigkeiten jenseits der Fahraufgabe zu ermöglichen. Wir stellen dazu einen Leitfaden vor, der die Gestaltung und Entwicklung von automobilen Benutzungsschnittstellen unterstĂŒtzt, die das DurchfĂŒhren von Nebenaufgaben erlauben. Dies umfasst zum Beispiel Hinweise, wie AktivitĂ€ten angepasst oder unterbrochen werden können, wenn sich der Automatisierungsgrad wĂ€hrend der Fahrt Ă€ndert. Um AktivitĂ€ten im Auto zu unterstĂŒtzen, stellen wir ein neuartiges Interaktionskonzept vor, das eine multimodale Interaktion im Fahrzeug mit Sprachbefehlen und Touch-Gesten ermöglicht. FĂŒr automatisierte Fahrzeugsysteme und zur Anpassung der Interaktionsmöglichkeiten an die Fahrsituation stellt der Fahrerzustand (insbesondere die mentale Belastung) eine wichtige Information dar. Durch eine Fahrstudie im realen StraĂenverkehr haben wir einen Datensatz generiert, der physiologische Daten und Kontextinformationen umfasst und damit RĂŒckschlĂŒsse auf den Fahrerzustand ermöglicht. Mit diesen Informationen ĂŒber Fahrerinnen und Fahrer wird es möglich, den Fahrerzustand besser zu verstehen, Benutzungsschnittstellen an die aktuelle Fahrsituation anzupassen und die Routenwahl anzupassen.
AuĂerdem stellen wir zwei konkrete Konzepte zur UnterstĂŒtzung von NebentĂ€tigkeiten vor, die schon heute regelmĂ€Ăig bei der Fahrt getĂ€tigt oder verlangt werden. Im Bereich der Telekommunikation stellen wir dazu ein Konzept vor, das die Fahrsicherheit beim Kommunizieren mit Personen auĂerhalb des Autos erhöht. Das Konzept erlaubt es dem Fahrer, unterschiedliche Arten von Kontextinformationen mit Kommunikationspartnern zu teilen. Dies reicht von der abstrakten Information, dass man derzeit im Auto unterwegs ist bis hin zum Teilen eines Live-Videos der aktuellen Fahrsituation. DiesbezĂŒglich haben wir ĂŒber eine Web-Umfrage und detaillierte Interviews die BedĂŒrfnisse der Nutzer(innen) erhoben und ausgewertet. Zudem stellen wir ein prototypisches Konzept sowie Richtlinien vor, wie kĂŒnftige Kommunikationsaufgaben im Fahrzeug gestaltet werden sollen. Als ein zweites Konzept betrachten wir zeitbeschrĂ€nkte Aufgaben zur Unterhaltung und ProduktivitĂ€t im Fahrzeug. Die Idee ist hier, zeitlich begrenzte Aufgaben in Zeiten niedriger Belastung zuzulassen, wie zum Beispiel beim Warten an einer Ampel oder wĂ€hrend einer hochautomatisierten (Teil-) Fahrt. Ergebnisse aus einer Web-Umfrage und einer Fallstudie zeigen die Machbarkeit dieses Ansatzes auf.
Mit den Ergebnissen dieser Arbeit soll eine Basis fĂŒr kĂŒnftige Forschung und Entwicklung gelegt werden, um im Bereich automobiler Benutzungsschnittstellen insbesondere nicht-fahr-bezogene Aufgaben im Ăbergang zwischen manuellem Fahren und einer hochautomatisierten Autofahrt zu unterstĂŒtzen
Creating sparks: comparing search results using discriminatory search term word co-occurrence to facilitate serendipity in the enterprise.
Categories or tags that appear in faceted search interfaces which are representative of an information item, rarely convey unexpected or non-obvious associated concepts buried within search results. No prior research has been identified which assesses the usefulness of discriminative search term word co-occurrence to generate facets to act as catalysts to facilitate insightful and serendipitous encounters during exploratory search. In this study, 53 scientists from two organisations interacted with semi-interactive stimuli, 74% expressing a large/moderate desire to use such techniques within their workplace. Preferences were shown for certain algorithms and colour coding. Insightful and serendipitous encounters were identified. These techniques appear to offer a significant improvement over existing approaches used within the study organisations, providing further evidence that insightful and serendipitous encounters can be facilitated in the search user interface. This research has implications for organisational learning, knowledge discovery and exploratory search interface design