25.03.2021. GISRUK Seminar Series 2021. Online.
Keynote: Semantic geographic knowledge on a world-scale – interlinking OpenStreetMap and knowledge graphs”
OpenStreetMap (OSM) is a rich source of openly available volunteered geographic information on a world scale. However, representations of geographic entities in OSM are highly diverse and incomplete. Knowledge graphs (i.e. graph-based knowledge repositories) such as Wikidata, EventKG, and DBpedia are a rich source of contextual semantic information about geographic entities. For example, Wikidata contains over six million geographic entities, including locations, points of interest, mountain peaks, etc. Whereas knowledge graphs provide a wide range of complementary semantic information for geographic entities, interlinking between knowledge graphs and OSM is insufficient with the links mainly manually defined by volunteers. This lecture will introduce emerging approaches that address tighter integration of OSM and knowledge graphs; it gives particular attention to link discovery and semantic enrichment of OSM datasets.
8 September 2020. VGIscience Young Researchers Seminar. Online. Keynote: Semantic Data Management and Analytics
20 Februar 2020. Symposium Intelligente Mobilität. Leibnizhaus, Hannover.
Title: Datenanalyse für Urbane Mobilität: Erfahrungen und Perspektiven.
Im Fokus des Vortrags steht die Entwicklung von robusten Datenanalyse-Methoden, Methoden des räumlichen und zeitlichen Wissenstransfers, transparente Methoden der Datenanalyse und Data Use Traceability, d.h. Nachverfolgbarkeit der Datenverarbeitung sowie die Vereinfachung und Wiederverwendbarkeit der Datenanalyse-Workflows. Diese Methoden erlauben zum Einem zuverlässige Analysen und Prognosen auf Basis von Mobilitätsdaten, die unter realistischen Bedingungen erhoben werden, zum Anderen, Wissenstransfer in die Regionen für die keine oder nur sehr wenige Daten vorhanden sind. Darüber hinaus, soll die erhöhte Transparenz den aktuellen Hürden für die Nutzerzustimmung zur Datenverarbeitung entgegenwirken.
19-21 August 2019. SSTD’19, Vienna, Austria (invited poster presentation).
Title: Crosstown Traffic – Supervised Prediction of Event Impact on Urban Traffic. Invited presentation of the article published in GeoInformatica [link] at the 16th International Symposium on Spatial and Temporal Databases (SSTD’19).
20 February 2019. GESIS – Leibniz Institute for the Social Sciences, Köln (invited talk).
Title: Towards efficient cross-lingual analytics of event-centric information.
The amount of multilingual information regarding contemporary and historical events of global importance continually grows on the web, within knowledge graphs, in the news sources, and within social media. Efficient collection, extraction, and analytics, as well as intuitive access to such information, constitute critical steps for a variety of real-world applications in the fields of Semantic Web, NLP, and Digital Humanities. In this talk, I briefly discuss selected challenges and introduce recent works in the area of event-centric multilingual data collection, semantic representation, analytics, and novel applications that constitute initial steps towards making such information accessible to a variety of users.
24 November 2018. Tagung der deutscher ingenieurinnenbund e.V. Hannover (Invited talk)
Title: Urbane Mobilität – ein Einblick in die Datenanalyse.
Die zunehmende Verfügbarkeit von Daten, wie Verkehrsinformationen oder Webdaten, birgt ein großes Potenzial für ein besseres Verständnis der urbanen Mobilität und effizientere Gestaltung innovativer Mobilitätsdienstleistungen. Die Beantwortung komplexer Fragestellungen wird aber erst durch die Verschränkung und Analyse von vielen heterogenen Datenquellen ermöglicht. Der Vortrag bietet aktuelle Einblicke in das Forschungsprojekt „Data4UrbanMobility – Datenbasierte Mobilitätsdienstleistungen für die Stadt der Zukunft“. In diesem Projekt werden Werkzeuge entwickelt, die einen ereignisbasierten Überblick über Mobilitätsinformationen liefern um effiziente Planung, Entwicklung, Durchführung und Nutzung von innovativen Mobilitätsdienstleistungen, insbesondere in der Region Hannover, zu ermöglichen.
10 October 2018. International Semantic Web Conference (ISWC 2018), BlueSky Track.
Title: Can Children Teach AI? Towards Expressive Human-AI Dialogs. [pdf]
AI-empowered dialogue systems become increasingly widespread. Whereas this adoption facilitates AI-based systems to engage in end-user dialogues on an unprecedented scale, the ability of AI to learn from their human dialogue partners is still substantially limited. In this presentation, I briefly discuss the opportunities, challenges, and risks on the interface of knowledge acquisition and human-computer interaction towards more expressive dialogues between end-users and AI.
4 June 2018. 4th International Workshop on Social Media World Sensors – Heraklion, Crete, Greece in conjunction with The 15th European Semantic Web Conference. (Invited talk)
Title: Towards Cross-Lingual Event-Centric Information Spaces.
The amount of multilingual information regarding contemporary and historical events of global importance continually grows on the web, in the news sources, and within social media. Efficient collection and effective analytics of increasingly available large-scale event-centric multilingual information are crucial for a variety of real-world applications in the fields of Semantic Web, NLP, and Digital Humanities. Cross-Lingual Event-Centric Information Spaces (CL-ECIS) aim to provide an integrated view of such information in particular domains. This paper briefly discusses selected challenges and recent works on event-centric multilingual data collection, semantic representation, analytics, and novel applications that constitute initial steps towards building these spaces.
8 March 2018. Workshop “Zukunft des Forschungsdatenmanagements für Ingenieurinnen und Ingenieure”, Technische Universität Darmstadt. (Impulsvortrag)
Titel: Forschungsdatenmanagement: die Web Science Perspektive [slides]
14 February 2018. Humanistisches Forum Garbsen, Hannover
Titel: Selbstlernende Systeme in der Künstlichen Intelligenz. Verstehen wir uns?
Die geheime Sprache: Ein Beispiel aus der Forschung verständlich erklärt. [slides]
Intelligente Informationssysteme beweisen sich zunehmend als praktische Helfer bei vielen alltäglichen Aufgaben. Gleichzeitig wird es, insbesondere in den Medien, kontrovers über die Möglichkeiten, Grenzen und potentielle Gefahren diese Systeme diskutiert. In dem Vortrag werden diese Zusammenhänge anhand von einem aktuellen Beispiel aus dem Bereich maschinelles Lernen für Dialogsysteme verdeutlicht.
21 August – 25 August 2017. 3rd KEYSTONE Training School, TU Wien, Austria (Tutorial & Hands-on)
The amount of unstructured information available on the Web is ever-growing. Information Extraction enables to automatically identify information nuggets such as named entities, time expressions, relations, and events in the text and interlink these information nuggets with structured background knowledge. The extracted information can then be used in many application domains, e.g. to categorize and cluster text, enable faceted exploration, populate knowledge bases, and correlate extracted data with other sources. In this introductory tutorial, we provide an overview of the basic blocks for Information Extraction, including methods for named entity extraction and linking, temporal extraction, relation extraction, and Open Information Extraction.
Title: Data4UrbanMobility: Data-Driven Mobility Services for Smart Cities
Abstract: Cities of the future have a growing demand for intelligent mobility services and infrastructure to support better mobility and enhance the quality of life in urban areas. The goal of the Data4UrbanMobility project is to address this demand through aggregation and analysis of mobility-related data from heterogeneous sources, in particular data about events, public transportation infrastructure, and usage, floating car data, as well as behavior and perception of users. While data is spread across heterogeneous institutional repositories, Web platforms, and in particular the social Web, semantic technologies and machine learning methods will be exploited to enable the extraction and analysis of data.
8 December 2016. The University of Southampton, UK (Tutorial) [slides]
Title: Data Visualisation: Data visualization tools & Twitter data
The tutorial aims to demonstrate the applications of visualization techniques for data analysis at the example of Twitter data and to develop practical skills to create such visualizations.
Title: Introduction to Information Extraction
Abstract: Information Extraction enables to automatically identify information nuggets such as named entities, time expressions, relations, and events in the text and interlink these information nuggets with structured background knowledge. The extracted information can then be used in many application domains, e.g. to categorize and cluster text, enable faceted exploration, populate knowledge bases, and correlate extracted data with other sources. In this introductory tutorial, we provide an overview of the basic blocks for Information Extraction, including methods for named entity extraction and linking, temporal extraction, relation extraction, and Open Information Extraction.
17 – 21 July 2016. ACM SIGIR 2016, Pisa, Italy. (Demo paper)
Title: Analysing Temporal Evolution of Interlingual Wikipedia Article Pairs.
Simon Gottschalk, Elena Demidova.
Abstract: Wikipedia articles representing an entity or a topic in different language editions evolve independently within the scope of the language-specific user communities. This evolution can lead to varying points of view reflected in the articles, as well as complementary and inconsistent information. An analysis of how the information is propagated across the Wikipedia language editions can provide essential insights in the article evolution along the temporal and cultural dimensions and support quality control. To facilitate such analysis, we present MultiWiki – a novel web-based user interface that provides an overview of the similarities and differences across the article pairs originating from different language editions on a timeline. MultiWiki enables users to observe the changes in the interlingual article similarity over time and to perform a detailed visual comparison of the article snapshots at a particular time point.
Title: Interactive keyword-based access to large scale structured datasets.
Abstract: The data available on the Web, in large-scale Web archives, in digital libraries and open datasets is continuously growing and changing its appearance. The heterogeneity and large scale of this data, substantially restrict its accessibility to the end-users. To supply users with relevant and fresh information on demand, effective and efficient methods are essential that can cope with unknown data structures and large scale data. In this tutorial, we explore the methods of tackling these challenges with the focus on interactive retrieval techniques for structured data that do not require a-priori schema knowledge.
24 May 2016. ACM WebSci, Hannover, Germany. (Short paper)
Title: Analyzing Web archives through Topic and Event Focused Sub-Collections.
Gerhard Gossen, Elena Demidova and Thomas Risse.
Abstract: Web archives capture the history of the Web and are therefore a valuable source to study how societal developments have been reflected on the Web. However, the large size of Web archives and their temporal nature pose many challenges to researchers interested in working with these collections. In this work, we describe the challenges of working with Web archives and propose the research methodology of creating and studying sub-collections of the archived materials focused on specific topics and events. We discuss the opportunities and challenges of this approach and suggest a framework for creating sub-collections.
Title: Efficient extraction of event-centric sub-collections from the Web and large scale Web archives.
Abstract: The Web and web archives are invaluable sources to follow the traces of recent and past events, in particular for researchers in the Digital Humanities, journalists, and historians. On the one hand, the large size of data and their distributed nature makes their analysis daunting, especially for non-computer scientists. On the other hand, most research questions only require a smaller relevant subset of the Web or a Web archive such as the snapshots of Web pages describing one particular event or topic. For example, these sub-collections can reflect the ongoing refugee crisis in Europe, the Fukushima nuclear disaster in 2011, the German federal election in 2009, or the FIFA World Cup 2006. In this talk, I present our recent work to create methods that facilitate the extraction of event-centric sub-collections from the Web and Web archives. The creation of sub-collections raises several challenging research questions concerning crawler guidance, indexing, and relevance estimation. On the Web, our methods are facilitated through social media guidance using Twitter and enable efficient monitoring, gathering, and analysis of the fresh online content regarding current events. In Web archives, we propose flexible re-crawling methods coupled with topical and temporal relevance estimation and light-weight indexing. We discuss the opportunities and challenges of these approaches and present a framework for creating sub-collections.
21 January 2016. The University of Bonn, Germany (Invited talk).
Title: Interactive Retrieval Methods, Sub-Collection Extraction, and Semantic Alignment for Large and Heterogeneous Multilingual Datasets.
Abstract: The data available on the Web, in large-scale web archives, in digital libraries and open datasets is continuously growing and changing its appearance. The structural and linguistic heterogeneity and large scale of this data substantially restrict its accessibility to the end-users. To supply users with relevant and fresh multilingual information on demand, effective and efficient methods are essential that can cope with unknown data structures, large-scale data, and data written in foreign languages. In this talk, I discuss methods tackling these challenges. In particular, I focus on 1) Interactive retrieval techniques for structured data that do not require a-priori schema knowledge; 2) On-demand creation of event-centric sub-collections from the Web and web archives; as well as 3) Semantic alignment of multilingual data to overcome the language barrier.
Title: ALEXANDRIA – Analysing and Exploring Web Archives.
Title: Analyzing Relative Incompleteness of Movie Descriptions in the Web of Data: A Case Study. Wancheng Yuan, Elena Demidova, Stefan Dietze, Xuan Zhou. International Semantic Web Conference (Posters & Demos) 2014: 197-200.