Prognose der Verkehrslage in der Region Hannover

Die primäre Anforderung der Verkehrsteilnehmer im Bereich des Straßenverkehrs ist die Kenntnis der aktuellen Verkehrslage. Diese basiert in der Regel auf der wirklich benötigten Reisezeit von sehr vielen Verkehrsteilnehmern, deren Daten häufig im Kontext von Routingdiensten abgegriffen werden.

Im Rahmen von Data4UrbanMobility wurden Werkzeuge entwickelt um eine ganglineinbasierte Prognose der Verkehrslage zu ermöglichen. Die folgende Abbildung zeigt eine Oberfläche auf der typische Ganglinienverläufe und Ausreißer visualisiert werden.

Die Prognose der Verkehrslage kann dann mittels einer Karte für den Endnutzer visualisert werden:

Erste Version der MIC-App bereitgestellt

Eine erste Version der MIC-App (Move in the City) konnte allen Partnerinnen und Partnern des Projekts und einer geschützten Nutzer*innengruppe der Öffentlichkeit zur Verfügung gestellt werden. Die mobile App MiC ist ein Instrument zur Datenerhebung.

Dabei verknüpft MiC – eine Entwicklung des Institute for Sustainable Urbanism ISU der TU Braunschweig und Projektionisten GmbH Hannover – das wachsende Bewusstsein und die Notwendigkeit für digitale Bürger*innenrechte mit den Potentialen mittels der Auswertung großer Datenmengen neue Formen der menschzentrierten Entwicklung von Stadt und Mobilität zu ermöglichen stellt eine Möglichkeit dar, sich aktiv als Bürgerwissenschaftlerin und Bürgerwissenschaftler an der Forschung und Entwicklung der Mobilität für alle in der Stadt der Zukunft zu beteiligen.

MiC erhebt – durch die Nutzerinnen und Nutzer gesteuert – Daten zu Strecken und Art der Fortbewegung. Diese Daten werden pseudonymisiert, so dass ein Rückschluss auf die jeweilige Person nicht mehr möglich ist. Wichtig ist die Vielzahl der Nutzerinnen und Nutzer – nicht die einzelne Bewegung. Die Stadt der Zukunft zeichnet sich aus durch den barrierearmen Zugang zu Mobilität und Erreichbarkeit für alle. Der holistische Ansatz der Forscherinnen und Forscher des Institute for Sustainable Urbanism ISU (TU Braunschweig) sowie der Projektbeteiligten betrachtet Stadt dabei auf verschiedenen Maßstabsebenen und bringt intelligente Planungen – wie z.B. die 5-Minuten Stadt –, Städtebau und innovative Technologien zusammen. Für ein umfassendes Verständnis individueller Mobilität und darauf aufbauende neue Methoden und Werkzeuge für integrierte Verkehrs- und Stadtplanung werden mittels der MiC-App uns umfangreiche und detaillierte Daten darüber geliefert, wie und auf welchem Wege wir uns in der Stadt fortbewegen.

Entwicklungsstand:

In der ersten Version ermöglicht das Stadtforschungstool MiC den Nutzer*innen durch eine einfach Handhabung das Starten und Beenden der „Tracking-Time“ (Bild 1). Wichtig ist, die Nutzer*innen entscheidet selber über den Zeitraum. Als erstes Ergebnis für die Nutzer*innen steht eine Zusammenfassung ihrer bisher aufgezeichneten Routen (Bild2). In den Einstellung (Bild 3) kann der Nutzer sich aktiv an Feedback beteiligen (Bild 4) sowie seinen Account und somit seiner zur Verfügung gestellten Daten löschen (Bild 5).

von links nach recht: Bild1-5 MIC App Interface – Attribution-NonCommercial-ShareAlike 4.0 International  (CC BY-NC-SA 4.0)

Die aktuelle Weiterentwicklung sieht eine Visualisierung der Routen für den jeweiligen Nutzer vor.

Um Teil der Testgruppe zu werden ist zur Zeit noch eine Anmeldung unter: www.mic-app.org notwendig. Die Anwendung ist nicht frei im App Store / GooglePlay Store zu erhalten.

Auf der Internetseite www.mic-app.org wird zusätzlich detailliert auf häufige Fragen (FAQ) zur Anwendung sowie über Entwicklungen und Neuheiten informiert

D4UM Plattform und Dashboard V2

Die neue Version der Plattform inklusive des Dashboards gibt noch detailliertere Auskünfte über die Verkehrssituation

Die farblich unterschiedlichen Label lassen eine schnelle Unterscheidung zwischen den verschiedenen Event typen zu. Durch das klicken auf eines der Events wird der typically affected subgraph angezeigt für diesen Eventtyp.

Beispiele: Visualisierungen eines Konzerts und eines Fußballspiels

Zusätzlich gibt der Graph in der oberen rechten Ecke Auskunft über die Verkehrssituation vor und nach dem Eventstart.

{API}
Es wurden die API Endpunkte mit zusätzlichen Information erweitert.
Diese werden mittels der als Teil der Forschung entwickelten Modellen erstellt.

Erste Version der D4UM-App bereitgestellt

Eine erste Version der D4UM-App konnte allen Partnern des Projekts zur Verfügung gestellt werden. Die App stellt eine Möglichkeit dar, sich Fahrtauskünfte mit dem öffentlichen Personennahverkehr in Niedersachsen und Bremen (Datengrundlage: EFA – elektronische Fahrplanauskunft für Niedersachsen und Bremen) ausgeben zu lassen. Im Fokus stand hierbei, dass der Nutzer schnell und einfach an die für ihn wichtigen Informationen gelangen kann, um so seine Reise möglichst simpel planen zu können.

Folgende Funktionen dienen dabei in der ersten Version der schnellen Auskunft:

Abfahrten und Verbindungen

Über die Funktion Abfahrten lassen sich Abfahrtszeiten an einer bestimmten oder an nahegelegenen Haltestellen ermitteln. Unter Verbindungen können hingegen Fahrtvorschläge von einem Startpunkt (Adresse oder Haltestelle) zu einem Zielpunkt gesucht werden. Zeiten stehen dabei auch in Echtzeit zur Verfügung, sodass auch Verspätungen direkt von dem Nutzer erkannt werden können.

Karte

Über die Karte sind alle Haltestellen zu finden, sodass sich der Nutzer einen Überblick über die nähere Umgebung oder auch den Weg zur Haltestelle oder einem Ziel verschaffen kann.

Wird auf der Karte auf ein Haltestellensymbol oder den zugehörigen Haltestellennamen geklickt, öffnet sich der Abfahrtsmonitor zu dieser Haltestelle. Die nächsten Abfahrten können somit auch über diesen Weg aufgerufen werden.

Darüber hinaus kann sich der Nutzer auch den Verlauf seiner Fahrt anzeigen lassen.

Menü/Einstellungen

Weitere Funktionen und Einstellungen finden sich ergänzend im Menü der App.

Der Nutzer bekommt hier zum einen die Möglichkeit, dass erweiterte Einstellungen zu den Suchanfragen bei Verbindungen oder Abfahrten vorgenommen werden können, und zum anderen, dass er weitere Features verwenden kann. Darunter befindet sich zum Beispiel das Feedbackformular. Hierüber kann unkompliziert Kontakt mit den Entwicklern der D4UM-App per Mail aufgenommen werden. Icons ermöglichen es, dass ein Eindruck zu der App übermittelt werden kann. Ein weiteres Feld für Freitext bietet zudem Platz für individuelle Kritik und einer Meinung zu der App. So kann in Zukunft kundennah an der App weiterentwickelt und einfach auf Wünsche und Meinungen reagiert werden.

Quantifizierungen und Vorhersage von Auswirkungen von Veranstaltungen

Neue Data4UrbanMobility-Forschungsergebnisse ermöglichen es, die räumlichen Auswirkungen von Veranstaltungen zu quantifizieren und vorherzusagen. Dazu werden zusammenhängende, betroffene Straßenabschnitte in der Nähe von Veranstaltungen identifiziert. Auf dieser Grundlage kann dann die räumliche Auswirkung quantifiziert werden. Das Verfahren ist in der folgenden Grafik dargestellt.

(Karte von https://www.openstreetmap.org)

Hier in Gelb markiert ist eine Veranstaltung, in Rot betroffene Straßenabschnitte und in Dunkelblau die gemessene Auswirkung. Weiterhin wurden Verfahren des Maschinellen Lernens angewandt, um diese Auswirkungen zu prognostizieren. Dabei konnte der Fehler gegenüber bestehenden state-of-the-art Ansätzen um bis zu 40% verringert werden.

D4UM – Plattform V1 fertiggestellt

Die erste Version der Data4UrbanMobility Plattform wurde fertiggestellt. Dazu wurde zunächst eine 3-Schichten Architektur der Plattform konzipiert und implementiert. Die Plattform bietet RESTfull Webservices für Mobilitätsapplikationen wie Dashboard-Anwendungen oder Apps an. Als erste Beispielanwendung wurde dazu eine interaktive Karte entwickelt, die die Auswirkungen von Veranstaltungen visualisiert. Ein Ausschnitt aus der Anwendung ist im folgenden Screenshot zu sehen.

Zu sehen sind 4 Veranstaltungen in Hannover. Die Farben entsprechen dabei unterschiedlichen Veranstaltungsarten (etwa Konzerte, Messen, Fußballspiele). Die Kreise visualisieren die räumlichen Auswirkungen, die diese Veranstaltungen auf den Verkehr hatten.

Umfangreicher Anforderungskatalog
Die Data4UrbanMobility Anforderungsanalyse umfasst die Erfassung der Anforderungen der Anwendungspartner Region Hannover (RH) und Wolfsburg AG (WAG), sowie der nicht-funktionalen Anforderungen. Aus den Anforderungen der AnwendungspartnerInnen (RH und WAG), die von MOMA erhoben wurden, sind von L3S Forschungsfragen für die Datenanalyse abgeleitet worden, die sich speziell auf die Informationsbedürfnisse der AnwenderInnen beziehen und im weiteren Projektverlauf adressiert werden.

Die aktuelle Forschungsfragen adressieren insbesondere:

1.  Automatische Verifikation von Verkehrswarnmeldungen und Prognose von deren Auswirkungen.
2.  Identifikation von Veranstaltungen und Prognose verkehrsrelevanter Auswirkungen.
3. Korrelation von IV-Reiseflussdaten, EFA-Querylogs, Warnmeldungen und Twitterfeeds.
4. Bestimmung von optimalen Reisezeitpunkte.

Wachsende Datensammlung

Das ISU hat einen umfassende Datenmatrix mit potentiellen Quellen für mobilitätsrelevante Daten  erstellt. Das von L3S entwickelte Data4UrbanMobility Datenmodell beschreibt alle projektrelevanten Daten und setzt diese in Verbindung um die Daten sowohl für die Analyse als auch für die Anwendungen und Apps einheitlich zur Verfügung zu stellen. Die ausgewählten Datenquellen sind von L3S in das Data4UrbanMobility Datenmodell überführt. Einige der Datenquellen wie EFA-logs, und IV-Daten sind dabei auf deren Qualität geprüft worden.

Um die Datenintegration zu ermöglichen sind Werkzeuge zur Extraktion der relevanten Daten aus Mobilitätsrelevanten Datenquellen entwickelt worden:

• Straßen- und Graphextraktion aus OpenStreetMap
• EFA-Anfragen Bulkloader für die Extraktion der ÖPNV Anfragen aus EFA Logs
• Integration von Daten aus dem Zentralen Haltestellen Verzeichnis (ZHV) inklusive Verknüpfung der Daten mit den EFA-Anfragen

Die aktuelle Datensammlung (Stand: 12 Dezember 2017) umfasst:

EFA-Logs: 17 Mio. Suchanfragen
IV-Daten: 174 Tsd. Straßen, alle 15 Minuten
GTFS-Daten: 90 Tsd. Haltestellen, 2,6 Tsd. Routen
Wetter: Radolan Regenraster
Twitter: 2,5 Mio. Tweets ab Juni 2017

OSM: 440 Tsd. Straßen
Events: 21 Tsd. Veranstaltungen (14.08.2016-17.07.2018)

Warnmeldungen: 13 Tsd. Warnmeldungen (ab 06.2017)

Visualisierungen der ÖPNV Informationen

Zur intuitiven Analyse von mobilitätsrelevanten Informationen, insbesondere von ÖPNV Informationen, wurde von den PROJEKTIONISTEN (PROJ) eine Dashboard-Webapplikation konzipiert. Erste Prototypen visualisieren Anfragen an das regionale Fahrplanauskunftsystem EFA (www.efa.de) und dienen als Ausgangsbasis für explorative Analysen und die Implementierung der produktiven Version des Dashboards. Im Folgenden ist eine im Dashboard integrierte Visualisierung der häufigsten Start- und Ziel-punkte zu sehen.

Analysen der EFA-Logs
Als erste Forschungsfrage wird aktuell die Analyse der Auswirkungen der Veranstaltungen auf dem ÖPNV mit Methoden des Maschinellen Lernens analysiert.  Hierzu wurden in explorativen Datenanalysen der Einfluss von großen Veranstaltungen wie z.B. Fussballspielen und mittelgroßen Veranstaltungen, etwa Konzerte, auf Anfragen an den ÖPNV betrachtet.  Als Grundlage für umfassende Analysen wurden mit Hilfe visueller Methoden exemplarisch Korrelation zwischen ÖPNV-Nachfrage und Veranstaltungszeiträumen detektiert.

Dabei zeichnen sich z.B. für Hannovers Innenstadt klare, sternförmige Muster ab, die zentrale Mobilitätsknoten identifizieren.

Das Bild stellt die Luftlinie zwischen Start- und Ziel-Ort der Anfragen dar. Dabei entsprechen dunklere Farben häufigeren Strecken. Hier werden deutlich Hannover Hauptbahnhof und Hannover Kröpcke (die zentrale U-Bahn Station) als Mobilitätsknoten identifiziert.

Analysen der Nachfrage für einzelne Stationen lassen wochentagspezifische Muster erkennen.

Hier dargestellt sind die durchschnittliche Anzahl der Anfragen mit der Ziel-Haltestelle “Hannover Stadionbrücke”. Zu erkennen sind vor allem Unterschiede zwischen Werktagen und dem Wochenende.

Auch der Einfluss von Veranstaltungen kann mit Hilfe der Anfragen visualisiert werden:

Dargestellt sind die Anzahl der Anfragen mit Ziel “Hannover Stadionbrücke” für Mittwoch, den 26.04.2017 (Orange) sowie die durchschnittlichen Anzahl von Anfragen, die mittwochs mit gleichem Ziel gestellt wird (Blau).
An diesem Tag fand in einer nahe gelegenen Konzerthalle ein Konzert statt, das um 20 Uhr begann. Die signifikante Abweichung zwischen 17 und 19 Uhr wurde sehr wahrscheinlich von den anreisenden Gästen verursacht wurde. Dies illustriert, dass Anfragen an den ÖPNV eine wertvolle Informationsquelle sein können, um Prognosen über die Auswirkung von Veranstaltungen auf Mobilität zu erstellen.

• Utilising coastal blue carbon (CBC) to mitigate the climate crisis: Current status and future analysis of China. Gu, Tianze; Ng, Chuck Chuan (2025). 266 107699.
• ETCH: Generalizing Body Fitting to Clothed Humans via Equivariant Tightness. Li, Boqian; Feng, Haiwen; Cai, Zeyu; Black, Michael J.; Xiu, Yuliang (2025).
• Visualizing Intracellular Localization of Natural-Product-Based Chemical Probes Using Click-Correlative Light and Electron Microscopy. Schaller, Eva; Hofmann, Julian; Maher, Pamela; Stigloher, Christian; Decker, Michael (2025). 20(3) 721–730.
• Resound: A Moment of Reflection in a Techno-Spiritual RtD Inquiry. Claisse, Caroline; Chatting, David; Wolf, Sara; Morris, Ben; Durrant, Abigail C in TEI ’25 (2025).

  We present 'Resound', a Research through Design inquiry into alternative techno-spiritual practices of a UK Buddhist community, informed by a first-person and participatory approach with the members. In this pictorial we portray a moment of reflection as we consolidate our design work towards deployment with the community. We introduce the Resound Sphere, a materialisation of our learning and speculations to date, designed as a research product to empirically explore alternatives for how tangible interaction could mediate religious/spiritual practices. We contribute with the framing of a design space, the presentation of our design approach and artefact response to this design space.
• LOLA - An Open-Source Massively Multilingual Large Language Model. Srivastava, Nikit; Kuchelev, Denis; Ngoli, Tatiana Moteu; Shetty, Kshitij; Röder, Michael; Zahera, Hamada M.; Moussallem, Diego; Ngomo, Axel-Cyrille Ngonga O. Rambow, L. Wanner, M. Apidianaki, H. Al-Khalifa, B. D. Eugenio, S. Schockaert (eds.) (2025). 6420–6446.
• Ontolearn---A Framework for Large-scale OWL Class Expression Learning in Python. Demir, Caglar; Baci, Alkid; Kouagou, N’Dah Jean; Sieger, Leonie Nora; Heindorf, Stefan; Bin, Simon; Blübaum, Lukas; Bigerl, Alexander; Ngonga Ngomo, Axel-Cyrille (2025).
• Enhancement of Quality of Service in Underwater Wireless Sensor Networks. S, Vinayprasad M; N, Jayaram M (N. Meghanathan, ed.) (2025). 17(2) 53–70.

  Underwater Wireless sensor network (UWSN) has become a main topic in the research of underwater communication with more research challenges. One of the main issues in the UWSN communication process is Quality of Service (QoS). Therefore, for enhancing the QoS in the UWSN a novel Clustering Hello routing based Honey Badger GoogleNet (CHbHBG) model is proposed. Primarily, the required sensor hubs are placed in the underwater communication environment. Further, the energy usage of each node is monitored and energy-efficient cluster head is selected by the proposed mechanism. Moreover, the data rate resources were predicted and allocated at the channel using the fitness process of the model. The optimal allocation process improves the QoS in the network. To prove the efficacy of the system, the metrics including throughput, network lifetime, latency, energy consumption, PDR, transmission loss, and path creation time are validated and compared with the recent models. The developed model attained the higher network performance as 99.72% PDR, 949.2kbps throughput, 4004.31s network lifetime, and 230.84J energy consumption.
• Wax Arts With Honeybees – Taking First Steps Toward Multispecies Co-Creation. Huber, Stephan; Friedenberger, Tamara; Borlinghaus, Parzival; Wolf, Sara in TEI ’25 (2025).

  Centuries of beekeeping restricted the honeybees’ role to a producer of raw material, such as honey or wax, which is then harvested and processed, resulting in all artistic value being added by humans. In this project, we regard honeybees (Apis mellifera) as co-creators and explore the joint creations of our two species. During our first season, we scoped the co-creative space over the course of four months. We present image material of sculptures that exceed bees’ natural building behavior and contribute preliminary insights on artifacts originating from human-bee co-creation. We reflect on how human-introduced wax shapes made the bees deviate from their regular comb forms and discuss future paths of multi-species co-creation, temporality, material as well as ethical aspects. Our preliminary insights raise questions to be developed in discussions with the TEI community and answered in future work during the upcoming bee seasons.
• Teaching and Learning with Social Mixed Reality: Fostering Teacher Educators’ Technology Competencies Focusing on Diversity Hartmann, Melanie; Tiede, Jennifer; Latoschik, Marc Erich; Grafe, Silke (R. J. Cohen, ed.) (2025). Association for the Advancement of Computing in Education (AACE), Orlando, FL, USA.

  In an increasingly diverse and digitalized society, educators require competencies in media education and diversity-sensitive teaching. In this design-based research study, we further developed an action-oriented pedagogical concept to foster Teacher Educator Technology Competencies (TETCs) focusing on media education, diverse learners’ needs, and social augmented reality (AR) technologies. Accordingly, a professional development workshop was implemented at a German university. In a qualitative empirical case study involving a convenience sample of four teacher educators, data were collected from participants’ lesson designs before and after the workshop, as well as from a focus group discussion. Findings indicate that participants reflected on various legal and ethical aspects, as well as on social responsibility when considering the integration of social AR technologies in education. Additionally, participants demonstrated increased awareness of diverse students’ needs in this context. Based on these findings, implications for future pedagogical practices and research in higher education are discussed.
• Natural Language Generation. Reiter, Ehud (2025).
• Towards a phenomenological ontology of war. Gilks, Mark (2025). First View 1–19.

  This paper offers a critique of war from an existentialist-phenomenological perspective. Drawing on Martin Heidegger’s theory of ontology and Maurice Merleau-Ponty’s theory of perception, it develops a framework which integrates war and the body – and thus ontology and embodiment – in Critical War Studies. Two arguments are advanced: first, that war is in so far as we embody it (implying that the way in which we embody it determines the way in which it is); second, that the embodiment of war is essentially an agential activity. Thereby, this paper provides impetus for an ontological and moral re-avowal of war in critical academic discourse (for understanding war not primarily as a tragic fate but as our shameful doing). This, in turn, facilitates new perspective for interpretation and critique – to the extent, for example, that understanding the logic of war’s agential embodiment discloses what would constitute, and be necessary for, its disembodiment. Moreover, the paper points to clear possibilities for future research – for clarifying, for instance, the ontological upheaval latent in the prospect of future war.
• Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach. Hassouna, Mohamed; Holzhüter, Clara; Lehna, Malte; de Jong, Matthijs; Viebahn, Jan; Sick, Bernhard; Scholz, Christoph (2025).
• MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation. Sinha, Sankalp; Khan, Mohammad Sadil; Usama, Muhammad; Sam, Shino; Stricker, Didier; Ali, Sk Aziz; Afzal, Muhammad Zeshan (2025).
• Floral diversity enhances winter survival of honeybee colonies across climatic regions. Mainardi, Giulia; Sponsler, Douglas; Minaud, Etienne; Vardakas, Filippos; Charistos, Leonidas; Requier, Fabrice; Hatjina, Fani; Steffan‐Dewenter, Ingolf (2025).
• Polyfloral nutritional resources promote bumble bee colony development after exposure to a pesticide mixture. Castle, Denise; Alkassab, Abdulrahim T.; Erler, Silvio; Bischoff, Gabriela; Gerdes, Falk; Yurkov, Andrey; Steinert, Michael; Steffan-Dewenter, Ingolf; Pistorius, Jens (2025). 296 118170.
• SceneFactory: A Workflow-centric and Unified Framework for Incremental Scene Modeling. Yuan, Yijun; Bleier, Michael; Nüchter, Andreas (2025). 1–20.

  We present SceneFactory, a workflow-centric and unified framework for incremental scene modeling, that conveniently supports a wide range of applications, such as (unposed and/or uncalibrated) multi-view depth estimation, LiDAR completion, (dense) RGB-D/RGB-L/Mono/Depth-only reconstruction and SLAM. The workflow-centric design uses multiple blocks as the basis for constructing different production lines. The supported applications, i.e., productions avoid redundancy in their designs. Thus, the focus is placed on each block itself for independent expansion. To support all input combinations, our implementation consists of four building blocks that form SceneFactory: (1) tracking, (2) flexion, (3) depth estimation, and (4) scene reconstruction. The tracking block is based on Mono SLAM and is extended to support RGB-D and RGB-LiDAR (RGB-L) inputs. Flexion is used to convert the depth image (untrackable) into a trackable image. For general-purpose depth estimation, we propose an unposed & uncalibrated multi-view depth estimation model (U2 -MVD) to estimate dense geometry. U2-MVD exploits dense bundle adjustment to solve for poses, intrinsics, and inverse depth. A semantic-aware ScaleCov step is then introduced to complete the multi-view depth. Relying on U2-MVD, SceneFactory both supports user-friendly 3D creation (with just images) and bridges the applications of Dense RGB-D and Dense Mono. For high-quality surface and color reconstruction, we propose Dual-purpose Multi-resolutional Neural Points (DM-NPs) for the first surface accessible Surface Color Field design, where we introduce Improved Point Rasterization (IPR) for point cloud based surface query. We implement and experiment with SceneFactory to demonstrate its broad applicability and high flexibility. Its quality also competes or exceeds the tightly-coupled state of the art approaches in all tasks. We contribute the code to the community
• Forcing the world into machines. Geuter, Jürgen (2025).

  For generative AI this purpose is quite clear: It’s about putting pressure on human labour. If you can generate somewhat passable prose or images or software code using an “AI” you can either try to run your business with fewer people (who tend to want to be paid) or (more realistically) you can push people’s wages down by always pointing at “the AI” when someone wants a raise or does not want to do unpaid overtime. The actual problem generative AI is trying to solve is having to pay people for their work.
• Bridging the Communication Gap: Evaluating AI Labeling Practices for Trustworthy AI Development Fischer, Raphael; Wischnewski, Magdalena; van der Staay, Alexander; Poitz, Katharina; Janiesch, Christian; Liebig, Thomas (2025).
• App-basierte Lieferdienste in Deutschland: Warum Menschen Gig-Work aufnehmen und meist schnell wieder beenden. Friedrich, Martin; Helm, Ines; Jost, Ramona; Lang, Julia; Müller, Christoph (2025). 2025–04.

  App-basierte Lieferdienste haben sich in den letzten Jahren rasant ausgebreitet. Das hat auch die öffentliche Diskussion um schlechte Arbeitsbedingungen der dort beschäftigten Gig-Worker angefacht. Allerdings gibt es bisher wenige gesicherte Erkenntnisse darüber, was Menschen zur Aufnahme von Gig-Jobs bewegt. Über die Gründe zur Beendigung dieser meist kurzen Jobs ist ebenfalls wenig bekannt. Das IAB bringt mit Ergebnissen einer neuen Befragung Licht in dieses Dunkel.
• Der abwesende Partner in der Sozialpartnerschaft: Veränderungen der Mitbestimmungspraxis in Betrieben mit chinesischen Investoren. Technical Report (84), Bian, Shuwen (2025).

  Wenngleich die Beteiligung chinesischer Unternehmen an ausländischen Unternehmen in den letzten Jahren deutlich abgenommen hat, bleiben die chinesischen Investitionsaktivitäten in Deutschland auf einem stabil hohen Niveau. Der Einstieg chinesischer Investoren hat tiefgreifende Veränderungen in der Unternehmenskultur deutscher Standorte zur Folge. Mit den Übernahmen entsenden die meisten chinesischen Gesellschafter chinesische Manager*innen in die Geschäftsführung der Tochtergesellschaften. Diese personellen Veränderungen in der lokalen Führungsebene haben direkte Auswirkungen auf die Betriebsabläufe und die betriebliche Mitbestimmung. Zwar gibt es keine Hinweise darauf, dass chinesische Gesellschafter und das Management die Arbeit der Mitbestimmungsakteure proaktiv verhindern, allerdings suchen sie auch nicht die Zusammenarbeit mit den Arbeitnehmervertretungen. Diese Abwesenheit in der Sozialpartnerschaft wird besonders problematisch, wenn Krisensituationen eine gemeinsame Lösungsfindung erfordern. Von besonderer Bedeutung sind insbesondere vier Faktoren, die sich negativ auf die betriebliche Mitbestimmung auswirken können: eingeschränkter Informationszugang, sprachliche Barrieren, paternalistische Unternehmensführung und der Einfluss von Parteirichtlinien.
• Drivers of late Quaternary lake level fluctuations of Khyargas Nuur, western Mongolia - glacial meltwater discharge or atmospheric moisture supply?. Wolf, Dennis; Lehmkuhl, Frank; Schaubert, Viktor; Rahimzadeh, Neda; Frechen, Manfred; Stauch, Georg; Batkhishig, Ochirbat; Wegmann, Karl (2025). 359 109373.

  This study presents the first comprehensive late Quaternary chronology of lake level variations of the Khyargas Nuur (western Mongolia), based on a geomorphological approach supported by luminescence dating of relict shorelines and lacustrine sediments. The endorheic Khyargas Nuur in the Basin of Great Lakes is the ultimate sink of a sequential water and sediment cascade from the adjacent Mongolian Altai and Khangai Mountains. Several intercalated lakes repeatedly joined as one major paleolake, as evidenced by various morphological shoreline features. Situated in the mid-latitude Westerlies-dominated climate regime of Arid Central Asia and affected by the distant effects of the East Asian Summer Monsoon, the dynamic climate of the Basin of Great Lakes is determined by the co-evolution of these atmospheric circulation systems. Our observations comprise 11 distinct paleolake levels between +7 m and +188 m above modern lake level (aml). Calculations of paleolake extent and water volume emphasize the periodically enhanced inflow and gradual capture and abandonment of upstream-located lakes. In the regional to global paleoclimatic context, our results reveal three distinct phases of lake level dynamics: (i) A transgression to a maximum level of +129 m aml during Marine Isotope Stage 5c (104.7 ± 14.4–88.8 ± 12.7 ka) primarily controlled by increased atmospheric moisture supply from the Westerlies. (ii) A post-Last Glacial Maximum lake expansion to a level of +118 m aml around 14 ka, ultimately controlled by enhanced glacial meltwater discharge into the basin. This is followed by a lake regression throughout the late Glacial to early Holocene transition in response to a gradually decreasing meltwater supply and a drier climate. (iii) A late Holocene transgression to +15 m aml reflecting a general Holocene wetting trend across arid Central Asia, followed by small-scale level fluctuations post 2.6 ka.
• Evaluation of potentially toxic elements (PTEs) contamination in seawater, sediment, and sea snails (Nerita articulata and Cerithidea obtusa) from Kukup Fishing Village, Johor, Malaysia. Tan, Ruo Han; Ng, Chuck Chuan; Gu, Tianze; Tek, Peggy Pei Yee (2025). 197(5) 565.

  Molluscs, being highly susceptible to potentially toxic elements (PTEs) and easily accessible for human consumption, play a critical role in research on PTE pollution. This study focuses on Kukup Fishing Village in Johor, Malaysia, to investigate the levels of Cd, Cu, and Pb in seawater, sediment, and the soft tissues and shells of the gastropods Nerita articulata (lined nerite snail) and Cerithidea obtusa (obtuse horn shell). All collected samples were chemically digested before being analysed using the flame atomic absorption spectrometer (F-AAS). It is found that the PTEs are mostly accumulated in soft tissues and shells, followed by sediments and seawater, respectively. Besides, the results revealed that all study locations exhibited moderate to severe pollution, and the PTE concentrations in sea snails exceeded the thresholds set by the Malaysian Food Regulations (1985). The mean concentrations of the studied elements in the seawater, soft tissues, and shells of two studied species were found to be in the order of Pbthinspace>thinspaceCuthinspace>thinspaceCd. Additionally, Pb was heavily accumulated in the soft tissues of both species: N. articulata (712.587--723.242 ppm) and C. obtusa (705.935--708.626 ppm). Compared to N. articulata, C. obtusa showed a higher capacity to accumulate Cd (3.702--4.350 ppm) and Cu (92.687--157.445 ppm), particularly in the soft tissues. The shell of N. articulata and the soft tissue of C. obtusa were identified as potential biomonitoring indicators for Cd and Cu, respectively. It is recommended that the local Malaysian authorities could strengthen environmental management, implement regular monitoring, and raise public awareness to minimise seafood consumption from polluted areas as these measures could aid to reduce pollution, protect marine ecosystems, and safeguard public health.
• Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation. Cai, Yunxuan; Xiang, Sitao; Li, Zongjian; Chen, Haiwei; Zhao, Yajie (2025).
• Leveraging Prompting Guides as Worked Examples for Advanced Prompt Engineering Strategies. Tolzin, Antonia; Knoth, Nils; Janson, Andreas (2024).

  Artificial intelligence systems, particularly those based on large language models, are increasingly prevalent in personal and professional settings, making the skill of prompt engineering—formulating effective AI inputs—vital. This paper explores the effects and how to enhance students' prompt engineering skills based on a multi-study design. Our first study confirmed the baseline hypothesis that prompt engineering can predict AI output quality, framing it as a critical skill. We then investigated whether instructional designs (worked examples & instructions), could develop prompting skills. Using worked examples, the second study tested the effectiveness of instructional materials on enhancing prompting skills. The experiment involved 245 students who demonstrated that a brief exposure to a worked example-based prompting guide significantly improved their ability to deploy targeted prompting strategies. These findings suggest that integrating worked examples into curricula could effectively equip students with essential prompting skills, offering both theoretical and practical implications for AI education.
• Generating SPARQL from Natural Language Using Chain-of-Thoughts Prompting. Zahera, Hamada M.; Ali, Manzoor; Sherif, Mohamed Ahmed; Moussallem, Diego; Ngomo, Axel-Cyrille Ngonga in Studies on the Semantic Web, A. A. Salatino, M. Alam, F. Ongenae, S. Vahdati, A. L. Gentile, T. Pellegrini, S. Jiang (eds.) (2024). (Vol. 60) 353–368.
• PCFWebUI: Data-driven WebUI for holistic decarbonization based on PCF-Tracking. Kumar, Ajay; Naumann, Marius; Henne, Kevin; Sherif, Mohamed Ahmed in CEUR Workshop Proceedings, D. Garijo, A. L. Gentile, A. Kurteva, A. Mannocci, F. Osborne, S. Vahdati (eds.) (2024). (Vol. 3759)
• Top Manufacturer of Orthocoir Sheets, Coir Cake & China Coir. Coir, We (W. Coir, ed.) (2024).
• Plekhg5 controls the unconventional secretion of Sod1 by presynaptic secretory autophagy. Hutchings, Amy-Jayne; Hambrecht, Bita; Veh, Alexander; Giridhar, Neha Jadhav; Zare, Abdolhossein; Angerer, Christina; Ohnesorge, Thorben; Schenke, Maren; Selvaraj, Bhuvaneish T.; Chandran, Siddharthan; Sterneckert, Jared; Petri, Susanne; Seeger, Bettina; Briese, Michael; Stigloher, Christian; Bischler, Thorsten; Hermann, Andreas; Damme, Markus; Sendtner, Michael; Lüningschrör, Patrick (2024). 15(1) 8622-.

  Increasing evidence suggests an essential function for autophagy in unconventional protein secretion (UPS). However, despite its relevance for the secretion of aggregate-prone proteins, the mechanisms of secretory autophagy in neurons have remained elusive. Here we show that the lower motoneuron disease-associated guanine exchange factor Plekhg5 drives the UPS of Sod1. Mechanistically, Sod1 is sequestered into autophagosomal carriers, which subsequently fuse with secretory lysosomal-related organelles (LROs). Exocytosis of LROs to release Sod1 into the extracellular milieu requires the activation of the small GTPase Rab26 by Plekhg5. Deletion of Plekhg5 in mice leads to the accumulation of Sod1 in LROs at swollen presynaptic sites. A reduced secretion of toxic ALS-linked SOD1G93A following deletion of Plekhg5 in SOD1G93A mice accelerated disease onset while prolonging survival due to an attenuated microglia activation. Using human iPSC-derived motoneurons we show that reduced levels of PLEKHG5 cause an impaired secretion of ALS-linked SOD1. Our findings highlight an unexpected pathophysiological mechanism that converges two motoneuron disease-associated proteins into a common pathway.
• Navigating Intersections of Religion/Spirituality and Human-Computer Interaction. Markum, Robert B.; Maas, Franzisca; Wolf, Sara; Halperin, Brett A.; Claisse, Caroline; Buie, Elizabeth in NordiCHI ’24 Adjunct (2024).

  Religion and spirituality (R/S) are an important part of many people’s lives, and while HCI is increasingly engaged in research and design in specific R/S contexts, there are many cases where researchers or designers encounter R/S outside of such contexts. In this workshop, we seek to bring together HCI researchers and designers across all research areas and with varying levels of experience with R/S to discuss encounters with R/S in their work, either intentional or not, and to develop principles and strategies to guide HCI research and design that intersects with R/S. Through this workshop, we also seek to further establish a network of scholars who can provide each other support in navigating R/S-related challenges and opportunities in their work and can participate in publication-oriented collaborations that consider the intersection of R/S and HCI.
• Efficient Evaluation of Conjunctive Regular Path Queries Using Multi-way Joins. Karalis, Nikolaos; Bigerl, Alexander; Heidrich, Liss; Sherif, Mohamed Ahmed; Ngonga Ngomo, Axel-Cyrille (2024).
• IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains. Gusmita, Ria Hari; Faruq, Muhammad; Mousallem, Diego; Ngonga Ngomo, Axel-Cyrille (2024).
• Multi-Resolution Diffusion Models for Time Series Forecasting. Shen, Lifeng; Chen, Weiyu; Kwok, James (2024).
• Making Alternatives Through Design for Mediated Spiritual Practice. Claisse, Caroline; Chatting, David; Wolf, Sara; Morris, Ben; Durrant, Abigail C in HttF ’24 (2024).

  The COVID-19 pandemic has intensified our dependence on screen-based devices, re-shaping how we connect with one another. Motivated by a yearning for alternative and post-pandemic religious and spiritual (R/S) practice, we pursue a Research-through-Design (RtD) project, Resound, exploring mediated technospiritual connections with a UK-based Buddhist community. This pictorial depicts the complexity of (i) designing with spiritual-corporeal selves engaged in community-centred and ritualistic practices; (ii) and tangible artefacts and sonic environments being made, configured and practiced with. We reflect on this ongoing material engagement as making tangible alternatives through techno-spiritual practice.
• (Un)designing AI for Mental and Spiritual Wellbeing. Smith, C. Estelle; Bezabih, Alemitu; Freed, Diana; Halperin, Brett A.; Wolf, Sara; Claisse, Caroline; Li, Jingjin; Hoefer, Michael; Rifat, Mohammad Rashidujjaman in CSCW Companion ’24 (2024). 117–120.

  With rapid advances in Artificial Intelligence (AI) impacting human health and wellbeing, scholarly discourse should focus equally on the prospective opportunities and harms of Human-AI Interaction (HAI) in Computer-Supported Collaborative Work and Social Computing (CSCW). This panel invites critical interdisciplinary discussion around the (un)designing of AI by asking: how, when, where, and why should AI (not) be involved in sociotechnical systems for mental and spiritual health and wellbeing? Motivated by functional, technical, and ethical concerns, the panel aims to ensure that: (1) progress in HAI for mental and spiritual health is informed by expertise from the respective clinical disciplines; (2) ethical and responsible design principles lie at the core of research motivations and methodologies; and (3) AI hype can be tempered by caution given its impacts on marginalized and stigmatized groups. A panel of respected experts in mental health, spiritual care, and AI will discuss CSCW topics regarding HAI in contexts of clinical practice (e.g., electronic health records, patient portals, decision-making and referral systems, technology-supported interactions during bedside care or clinical appointments) as well as social contexts beyond the clinic (e.g., social apps, online health communities and social media, and computer-mediated communication in spiritual/religious groups).
• An OWL Ontology for Linguistic Phenomena with Applications to Gallo-Italic Dialects in Sicily. Cantone, Domenico; Di Caro, Vincenzo Nicolò; Longo, Cristiano; Menza, Salvatore; Asmundo, Marianna Nicolosi; Santamaria, Daniele Francesco in CEUR Workshop Proceedings, A. Bikakis, R. Ferrario, S. Jean, B. Markhoff, A. Mosca, M. N. Asmundo (eds.) (2024). (Vol. 3809)
• ENHANCING PERSONALIZED RECIPE RECOMMENDATION THROUGH MULTI CLASS CLASSIFICATION. Neelam, Harish; Veerella, Koushik Sai (H. Neelam; K. S. Veerella, eds.) (2024). 14(5) 11.

  This paper intends to address the challenge of personalized recipe recommendation in the realm of diverse culinary preferences. The problem domain involves recipe recommendations, utilizing techniques such as association analysis and classification. Association analysis explores the relationships and connections between different ingredients to enhance the user experience. Meanwhile, the classification aspect involves categorizing recipes based on user-defined ingredients and preferences. A unique aspect of the paper is the consideration of recipes and ingredients belonging to multiple classes, recognizing the complexity of culinary combinations. This necessitates a sophisticated approach to classification and recommendation, ensuring the system accommodates the nature of recipe categorization. The paper seeks not only to recommend recipes but also to explore the process involved in achieving accurate and personalized recommendations.
• Inference over Unseen Entities, Relations and Literals on Knowledge Graphs. Demir, Caglar; Kouagou, N; Sharma, Arnab; Ngonga Ngomo, Axel-Cyrille (2024). arXiv–2410.
• FaVEL: Fact Validation Ensemble Learning. Qudus, Umair; Tatkeu Pekarou, Franck Lionel; Morim da Silva, Ana Alexandra; Röder, Michael; Ngonga Ngomo, Axel-Cyrille in Lecture Notes in Computer Science, M. Alam, M. Rospocher, M. van Erp, L. Hollink, G. A. Gesese (eds.) (2024). (Vol. 15370) 209–225.
• UniQ-Gen: Unified Query Generation across Multiple Knowledge Graphs. Vollmers, Daniel; Srivastava, Nikit; Zahera, Hamada M.; Moussallem, Diego; Ngonga Ngomo, Axel-Cyrille (2024).
• Evaluating Negation with Multi-way Joins Accelerates Class Expression Learning. Karalis, Nikolaos; Bigerl, Alexander; Demir, Caglar; Heidrich, Liss; Ngomo, Axel-Cyrille Ngonga in Lecture Notes in Computer Science, A. Bifet, J. Davis, T. Krilavicius, M. Kull, E. Ntoutsi, I. Zliobaite (eds.) (2024). (Vol. 14946) 199–216.
• Enhancing Answers Verbalization using Large Language Models. Vollmers, Daniel; Sharma, Parth; Zahera, Hamada M.; Ngonga Ngomo, Axel-Cyrille (2024).
• REDFM: a Filtered and Multilingual Relation Extraction Dataset. Huguet Cabot, ‪Pere-Lluís; Tedeschi, Simone; Ngonga Ngomo, Axel-Cyrille; Navigli, Roberto A. Rogers, J. Boyd-Graber, N. Okazaki (eds.) (2023). 4326–4343.

  Relation Extraction (RE) is a task that identifies relationships between entities in a text, enabling the acquisition of relational facts and bridging the gap between natural language and structured knowledge. However, current RE models often rely on small datasets with low coverage of relation types, particularly when working with languages other than English.In this paper, we address the above issue and provide two new resources that enable the training and evaluation of multilingual RE systems. First, we present SRED\($^\textrmFM$\), an automatically annotated dataset covering 18 languages, 400 relation types, 13 entity types, totaling more than 40 million triplet instances. Second, we propose RED\($^\textrmFM$\), a smaller, human-revised dataset for seven languages that allows for the evaluation of multilingual RE systems. To demonstrate the utility of these novel datasets, we experiment with the first end-to-end multilingual RE model, mREBEL, that extracts triplets, including entity types, in multiple languages. We release our resources and model checkpoints at [\urlhttps://www.github.com/babelscape/rebel](\urlhttps://www.github.com/babelscape/rebel).
• Parameterized Complexity of Weighted Team Definability. Kontinen, Juha; Mahmood, Yasir; Meier, Arne; Vollmer, Heribert (2023).
• Analysis of Common Supervised Learning Algorithms Through Application. Narula, Palak (2023).
• COBALT: A Content-Based Similarity Approach for Link Discovery over Geospatial Knowledge Graphs. Becker, Alexander; Ahmed, Abdullah; Sherif, Mohamed Ahmed; Ngonga Ngomo, Axel-Cyrille (2023).
• Using Pre-trained Language Models for Abstractive DBPEDIA Summarization: A Comparative Study. Zahera, Hamada M.; Vitiugin, Fedor; Sherif, Mohamed Ahmed; Castillo, Carlos; Ngonga Ngomo, Axel-Cyrille (2023).
• Native Execution of GraphQL Queries over RDF Graphs Using Multi-way Joins. Karalis, Nikolaos; Bigerl, Alexander; Ngonga Ngomo, Axel-Cyrille (2023).
• Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras. Demir, Caglar; Ngomo, Axel-Cyrille Ngonga (2023).
• Hardware-agnostic computation for large-scale knowledge graph embeddings. Demir, Caglar; Ngomo, Axel-Cyrille Ngonga (2022). 13
• Hashing the Hypertrie: Space- and Time-Efficient Indexing for SPARQL in Tensors. Bigerl, Alexander; Conrads, Lixi; Behning, Charlotte; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille U. Sattler, A. Hogan, M. Keet, V. Presutti, J. P. A. Almeida, H. Takeda, P. Monnin, G. Pirrò, C. d’Amato (eds.) (2022). 57–73.

  Time-efficient solutions for querying RDF knowledge graphs depend on indexing structures with low response times to answer SPARQL queries rapidly. Hypertries---an indexing structure we recently developed for tensor-based triple stores---have achieved significant runtime improvements over several mainstream storage solutions for RDF knowledge graphs. However, the space footprint of this novel data structure is still often larger than that of many mainstream solutions. In this work, we detail means to reduce the memory footprint of hypertries and thereby further speed up query processing in hypertrie-based RDF storage solutions. Our approach relies on three strategies: (1) the elimination of duplicate nodes via hashing, (2) the compression of non-branching paths, and (3) the storage of single-entry leaf nodes in their parent nodes. We evaluate these strategies by comparing them with baseline hypertries as well as popular triple stores such as Virtuoso, Fuseki, GraphDB, Blazegraph and gStore. We rely on four datasets/benchmark generators in our evaluation: SWDF, DBpedia, WatDiv, and WikiData. Our results suggest that our modifications significantly reduce the memory footprint of hypertries by up to 70% while leading to a relative improvement of up to 39% with respect to average Queries per Second and up to 740% with respect to Query Mixes per Hour.
• Consistent signals of a warming climate in occupancy changes of three insect taxa over 40 years in central Europe. Engelhardt, Eva Katharina; Biber, Matthias F.; Dolek, Matthias; Fartmann, Thomas; Hochkirch, Axel; Leidinger, Jan; Löffler, Franz; Pinkert, Stefan; Poniatowski, Dominik; Voith, Johannes; Winterholler, Michael; Zeuss, Dirk; Bowler, Diana E.; Hof, Christian (2022). 28(13) 3998–4012.
• LAUREN - Knowledge Graph Summarization for Question Answering. Jalota, Rricha; Vollmers, Daniel; Moussallem, Diego; Ngomo, Axel-Cyrille Ngonga (2021).

  Besides the challenge that a human can ask one question in many different ways, a key aspect in Question Answering approaches over Knowledge Graphs (KGQA) is to deal with the vast amount of information present in the knowledge graphs. Modern real-world knowledge graphs contain nearly millions of entities and relationships. Additionally, they are enriched with new facts every day. However, not all facts are relevant for answering particular questions, thus fostering several challenges to KGQA systems, which require interpretable and query-able data. One solution to filtering the extra data in knowledge graphs is to rely on graph summarization techniques. Graph-based summarization approaches aim to resize knowledge graphs to be more concise and precise by storing only relevant information. In this paper, we propose a framework named LAUREN that applies different summarization techniques on knowledge graphs to be used in KGQA systems. Our experiments show that LAUREN summarizes large knowledge graphs such as DBpedia by 2 million entities and its summarization still achieves the same performance on both question answering and linking tasks compared to the complete DBpedia.
• Automatically generating instructions from tutorials for search and user navigation. Heindorf, Stefan; Lipka, Nedim (2021).
• GATES: Using Graph Attention Networks for Entity Summarization. Firmansyah, Asep Fajar; Moussallem, Diego; Ngomo, Axel-Cyrille Ngonga (2021).

  The sheer size of modern knowledge graphs has led to increased attention being paid to the entity summarization task. Given a knowledge graph T and an entity e found therein, solutions to entity summarization select a subset of the triples from T which summarize e's concise bound description. Presently, the best performing approaches rely on sequence-to-sequence models to generate entity summaries and use little to none of the structure information of T during the summarization process. We hypothesize that this structure information can be exploited to compute better summaries. To verify our hypothesis, we propose GATES, a new entity summarization approach that combines topological information and knowledge graph embeddings to encode triples. The topological information is encoded by means of a Graph Attention Network. Furthermore, ensemble learning is applied to boost the performance of triple scoring. We evaluate GATES on the DBpedia and LMDB datasets from ESBM (version 1.2), as well as on the FACES datasets. Our results show that GATES outperforms the state-of-the-art approaches on 4 of 6 configuration settings and reaches up to 0.574 F-measure. Pertaining to resulted summaries quality, GATES still underperforms the state of the arts as it obtains the highest score only on 1 of 6 configuration settings at 0.697 NDCG score. An open-source implementation of our approach and of the code necessary to rerun our experiments are available at https://github.com/dice-group/GATES.
• Towards holistic Entity Linking: Survey and directions. Oliveira, Italo Lopes; Fileto, Renato; Speck, René; Garcia, Lu’is Paulo F.; Moussallem, Diego; Lehmann, Jens (2021). 95
• ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs. Zahera, Hamada M.; Heindorf, Stefan; Ngonga Ngomo, Axel-Cyrille (2021).

  Entity typing in knowledge graphs (KGs) aims to infer missing types of entities and might be considered one of the most significant tasks of knowledge graph construction since type information is highly relevant for querying, quality assurance, and KG applications. While supervised learning approaches for entity typing have been proposed, they require large amounts of (manually) labeled data, which can be expensive to obtain. In this paper, we propose a novel approach for KG entity typing that leverages semi-supervised learning from massive unlabeled data. Our approach follows a teacher-student paradigm that allows combining a small amount of labeled data with a large amount of unlabeled data to boost performance. We conduct several experiments on two benchmarking datasets (FB15k-ET and YAGO43k-ET). Our results demonstrate the effectiveness of our approach in improving entity typing in KGs. Given type information for only 1% of entities, our approach ASSET predicts missing types with a F1-score of 0.47 and 0.64 on the datasets FB15k-ET and YAGO43k-ET, respectively, outperforming supervised baselines.
• I-AID: Identifying Actionable Information from Disaster-related Tweets. Zahera, Hamada M.; Jalota, Rricha; Sherif, Mohamed Ahmed; Ngonga Ngomo, Axel-Cyrille (2021).

  Social media plays a significant role in disaster management by providing valuable data about affected people, donations and help requests. Recent studies highlight the need to filter information on social media into fine-grained content labels. However, identifying useful information from massive amounts of social media posts during a crisis is a challenging task. In this paper, we propose I-AID, a multimodel approach to automatically categorize tweets into multi-label information types and filter critical information from the enormous volume of social media data. I-AID incorporates three main components: i) a BERT- based encoder to capture the semantics of a tweet and represent as a low-dimensional vector, ii) a graph attention network (GAT) to apprehend correlations between tweets' words/entities and the corresponding information types, and iii) a Relation Network as a learnable distance metric to compute the similarity between tweets and their corresponding information types in a supervised way. We conducted several experiments on two real publicly-available datasets. Our results indicate that I-AID outperforms state-of- the-art approaches in terms of weighted average F1 score by +6% and +4% on the TREC-IS dataset and COVID-19 Tweets, respectively.
• HOBBIT: A platform for benchmarking Big Linked Data. Röder, Michael; Kuchelev, Denis; Ngonga Ngomo, Axel-Cyrille (2020). 3(1) 15–35.
• Tentris -- A Tensor-Based Triple Store. Bigerl, Alexander; Conrads, Lixi; Behning, Charlotte; Sherif, Mohamed Ahmed; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille J. Z. Pan, V. Tamma, C. d’Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, L. Kagal (eds.) (2020). 56–73.

  The number and size of RDF knowledge graphs grows continuously. Efficient storage solutions for these graphs are indispensable for their use in real applications. We present such a storage solution dubbed Tentris. Our solution represents RDF knowledge graphs as sparse order-3 tensors using a novel data structure, which we dub hypertrie. It then uses tensor algebra to carry out SPARQL queries by mapping SPARQL operations to Einstein summation. By being able to compute Einstein summations efficiently, Tentris outperforms the commercial and open-source RDF storage solutions evaluated in our experiments by at least 1.8 times with respect to the average number of queries it can serve per second on three datasets of up to 1 billion triples. Our code, evaluation setup, results, supplementary material and the datasets are provided at https://tentris.dice-research.org/iswc2020.
• Participant’s View: Short-Term Evaluation of Realizing PD Ideals. Klüber, Sara; Maas, Franzisca; Hohm, Anna; Hurtienne, Jörn in PDC ’20 (2020). 138–142.

  Participatory Design (PD) has long been described as a way to democratize technology development by involving those affected by the outcomes. Besides a good fit of technology as the outcome, PD allows participants to ‘have a say’, and supports ‘mutual learning’ and ‘co-realization’. A diverse range of PD methods has been developed, but there is a shortage of empirical studies showing whether (and why) these methods help pursue PD ideals. We therefore report on a case study of a short-term evaluation approach that may exemplary close this gap, and that allowed us to gain more knowledge on how our method affected participants. Participants perceived moderate to high feelings of ‘having a say’, ‘mutual learning’, and ‘co-realization’. In future research, mutual learning may exemplarily be improved by introducing a changing peer-to-peer procedure to the method. The evaluation may further be advanced by taking expectations into account.
• Experience Matters: Design and Evaluation of an Anesthesia Support Tool Guided by User Experience Theory. Klüber, Sara; Maas, Franzisca; Schraudt, David; Hermann, Gina; Happel, Oliver; Grundgeiger, Tobias in DIS ’20 (2020). 1523–1535.

  Despite many advances, clinical decision support tools (DSTs) often suffer from implementation and acceptance problems in the actual clinical context. We suggest that considering psychological needs-based and embodied user experience theories in the design of DSTs could help to overcome these problems. To examine this idea, we iteratively developed a DST called Cassandra supporting anesthetic teams in crisis management, specifically focusing on psychological needs and fluent interaction with the social and physical environment. We preliminarily evaluated Cassandra in a medical simulation, requiring anesthetic teams to handle a crisis. Although not all features of Cassandra had the intended effect, the results indicated that interacting with Cassandra supported the fulfillment of the identified needs for autonomy, competence, and relatedness and was seamlessly integrated into existing diagnostic processes. Considering user experience theories for the design of DSTs seems a promising way to overcome implementation and acceptance problems and eventually improve patient safety.
• MindPeaks: Formative Evaluation Method of Mindfulness Meditation Apps. Reinhardt, Daniel; Baur, Cordula; Klüber, Sara; Hurtienne, Jörn in DIS’ 20 Companion (2020). 37–42.

  Today's busy lifestyle can make us feel overwhelmed. Mindfulness meditation supports our well-being by slowing things down and drawing our attention to the present moment. Accordingly, a wealth of guided mindfulness meditation apps have emerged in the past years. Despite the many apps and an increasing interest within the HCI literature, there is little consensus of how to evaluate these apps and how to derive opportunities for re-design from the results. Our new MindPeaks method utilizes electroencephalography (EEG) to link design elements to meditative states and the user`s self-regulation of attention. This information can help designers to understand and optimize the efficacy of, for example, applications supporting mindfulness meditation.
• NABU - Multilingual Graph-Based Neural RDF Verbalizer. Moussallem, Diego; Gnaneshwar, Dwaraknath; Ferreira, Thiago Castro; Ngomo, Axel-Cyrille Ngonga in Lecture Notes in Computer Science, J. Z. Pan, V. Tamma, C. d’Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, L. Kagal (eds.) (2020). (Vol. 12506) 420–437.
• Finally on Par?! Multimodal and Unimodal Interaction for Open Creative Design Tasks in Virtual Reality. Zimmerer, Chris; Wolf, Erik; Wolf, Sara; Fischbach, Martin; Lugrin, Jean-Luc; Latoschik, Marc Erich (2020). 222–231.

  Multimodal Interfaces (MMIs) have been considered to provide promising interaction paradigms for Virtual Reality (VR) for some time. However, they are still far less common than unimodal interfaces (UMIs). This paper presents a summative user study comparing an MMI to a typical UMI for a design task in VR. We developed an application targeting creative 3D object manipulations, i.e., creating 3D objects and modifying typical object properties such as color or size. The associated open user task is based on the Torrence Tests of Creative Thinking. We compared a synergistic multimodal interface using speech-accompanied pointing/grabbing gestures with a more typical unimodal interface using a hierarchical radial menu to trigger actions on selected objects. Independent judges rated the creativity of the resulting products using the Consensual Assessment Technique. Additionally, we measured the creativity-promoting factors flow, usability, and presence. Our results show that the MMI performs on par with the UMI in all measurements despite its limited flexibility and reliability. These promising results demonstrate the technological maturity of MMIs and their potential to extend traditional interaction techniques in VR efficiently.
• Designing Ritual Artifacts for Technology-Mediated Relationship Transitions. Klüber, Sara; Löffler, Diana; Hassenzahl, Marc; Nord, Ilona; Hurtienne, Jörn in TEI ’20 (2020). 349–361.

  Rituals are ubiquitous but not commonplace, help people to make sense of their life, and cultivate personal or social meaning. Although secularization and digitalization impact the occurrence of formal rituals, the need for marking life's transitions remains unchanged. New rituals emerge, such as marking relationship status by hanging love locks on bridges. Tangible technologies hold great potential for augmenting, changing, or enhancing ritual practices which often involve enactments and symbolic props. In this paper, we analyze individual stories of hanging love locks and derive six pointers for designing technology-mediated relationship transition rituals. We applied the pointers in the design of El Corazón, a tangible artifact for relationship transition rituals. The results of an evaluation with 20 sweethearts show that relationship rituals can be designed deliberately, that tangibles can shape ritual experiences and that technology-mediated rituals can provide people with new means of coping with relationship uncertainty.
• OPTIC: A Deep Neural Network Approach for Entity Linking using Word and Knowledge Embeddings. Oliveira, Italo Lopes; Moussallem, Diego; Garcia, Lu’is Paulo Faina; Fileto, Renato J. Filipe, M. Smialek, A. Brodsky, S. Hammoudi (eds.) (2020). 315–326.
• Squirrel - Crawling RDF Knowledge Graphs on the Web. Röder, Michael; de Souza Jr, Geraldo; Ngonga Ngomo, Axel-Cyrille in Lecture Notes in Computer Science, J. Z. Pan, V. Tamma, C. d’Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, L. Kagal (eds.) (2020). (Vol. 12507) 34–47.
• "Paint That Object Yellow": Multimodal Interaction to Enhance Creativity During Design Tasks in VR. Wolf, Erik; Klüber, Sara; Zimmerer, Chris; Lugrin, Jean-Luc; Latoschik, Marc Erich (2019). 195–204.

  Virtual reality (VR) has always been considered a promising medium to support designers with alternative work environments. Still, graphical user interfaces are prone to induce attention shifts between the user interface and the manipulated target objects which hampers the creative process. This work proposes a speech-and-gesture-based interaction paradigm for creative tasks in VR. We developed a multimodal toolbox (MTB) for VR-based design applications and compared it to a typical unimodal menu-based toolbox (UTB). The comparison uses a design-oriented use-case and mea-sures flow, usability, and presence as relevant characteristicsfor a VR-based design process. The multimodal approach (1) led to a lower perceived task duration and a higher reported feeling of flow. It (2) provided a higher intuitive use and a lower mental workload while not being slower than an UTB. Finally, it (3) generated a higher feeling of presence. Overall, our results confirm significant advantages of the proposed multimodal interaction paradigm and the developed MTB for important characteristics of design processes in VR.
• Monitoring Vital Signs with Time-Compressed Speech. Sanderson, Penelope M.; Brecknell, Birgit; Leong, SokYee; Klueber, Sara; Wolf, Erik; Hickling, Anna; Tang, Tsz-Lok; Bell, Emilea; Li, Simon Y. W.; Loeb, Robert G. (2019). 25(4) 647–673.

  Spearcons—time-compressed speech phrases—may be an effective way of communicating vital signs to clinicians without disturbing patients and their families. Four experiments tested the effectiveness of spearcons for conveying oxygen saturation (SpO2) and heart rate (HR) of one or more patients. Experiment 1 demonstrated that spearcons were more effective than earcons (abstract auditory motifs) at conveying clinical ranges. Experiment 2 demonstrated that casual listeners could not learn to decipher the spearcons whereas listeners told the exact vocabulary could. Experiment 3 demonstrated that participants could interpret sequences of sounds representing multiple patients better with spearcons than with pitch-based earcons, especially when tones replaced the spearcons for normal patients. Experiment 4 compared multiple-patient monitoring of two vital signs with either spearcons, a visual display showing SpO2 and HR in the same temporal sequence as the spearcons, or a visual display showing multiple patient levels simultaneously. All displays conveyed which patients were abnormal with high accuracy. Visual displays better conveyed the vital sign levels for each patient, but cannot be used eyes-free. All displays showed accuracy decrements with working memory load. Spearcons may be viable for single and multiple patient monitoring. Further research should test spearcons with more vital signs, during multitasking, and longitudinally.
• Finding Datasets in Publications: The University of Paderborn Approach. Jalota, Rricha; Srivastava, Nikit; Vollmers, Daniel; Speck, René; Röder, Michael; Usbeck, Ricardo; Ngonga Ngomo, Axel-Cyrille J. I. Lane, I. Mulvany, P. Nathan (eds.) (2019).
• Pyro: Deep Universal Probabilistic Programming. Bingham, Eli; Chen, Jonathan P.; Jankowiak, Martin; Obermeyer, Fritz; Pradhan, Neeraj; Karaletsos, Theofanis; Singh, Rohit; Szerlip, Paul A.; Horsfall, Paul; Goodman, Noah D. (2019). 20 28:1–28:6.

  Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. To scale to large data sets and high-dimensional models, Pyro uses stochastic variational inference algorithms and probability distributions built on top of PyTorch, a modern GPU-accelerated deep learning framework. To accommodate complex or model-specific algorithmic behavior, Pyro leverages Poutine, a library of composable building blocks for modifying the behavior of probabilistic programs.
• Authorization Framework for Medical Data. Madadevaiah, Geetha (2019). 11(3) 7–28.

  In this paper, the authors describe an approach for sharing sensitive medical data with the consent of the data owner. The framework builds on the advantages of the Semantic Web technologies and makes it secure and robust for sharing sensitive information in a controlled environment. The framework uses a combination of Role-Based and Rule-Based Access Policies to provide security to a medical data repository as per the FAIR guidelines. A lightweight ontologywas developed, to collect consent from the users indicating which part of their data they want to share with another user having a particular role. Here, the authors have considered the scenario of sharing the medical data by the owner of data, say the patient, with relevant persons such as physicians, researchers, pharmacist, etc. To prove this concept, the authors developed a prototype and validated using the Sesame OpenRDF Workbench with 202,908 triples and a consent graph stating consents per patient.
• Under the Greenwood Tree Hardy, Thomas in The Cambridge Edition of the Novels and Stories of Thomas Hardy, (S. Gatrell, ed.) (2019). Cambridge University Press.
• Supporting Multiple Patient Monitoring with Head-Worn Displays and Spearcons. Klueber, Sara; Wolf, Erik; Grundgeiger, Tobias; Brecknell, Birgit; Mohamed, Ismail; Sanderson, Penelope M. (2019). 78 86–96.

  In hospitals, clinicians often need to monitor several patients while performing other tasks. However, visual displays that show patients' vital signs are in fixed locations and auditory alarms intended to alert clinicians may be missed. Information such as spearcons (time-compressed speech earcons) that ‘travels’ with the clinician and is delivered by earpiece and/or head-worn displays (HWDs), might overcome these problems. In this study, non-clinicians monitored five simulated patients in three 10-min scenarios while performing a demanding tracking task. Monitoring accuracy was better for participants using spearcons and a HWD (88.7%) or a HWD alone (86.2%) than for participants using spearcons alone (74.1%). Participants using the spearcons and HWD (37.7%) performed the tracking task no differently from participants using spearcons alone (37.1%) but participants using the HWD alone performed worse overall (33.1%). The combination of both displays may be a suitable solution for monitoring multiple patients.
• Towards a Semantic Message-driven Microservice Platform for Geospatial and Sensor Data. Wauer, Matthias; Sherif, Mohamed Ahmed; Ngonga Ngomo, Axel-Cyrille in CEUR Workshop Proceedings, M. Wauer, M. A. Sherif, M. Saleem, O. Hartig, R. Usbeck, R. Verborgh, A.-C. N. Ngomo (eds.) (2018). (Vol. 2110) 47–58.
• Developing a Framework for Online Practice Examination and Automated Score Generation. Sani, S. M. Saniul Islam; Karim, Rezaul; Arefin, Mohammad Shamsul (2018). abs/0806.3765
• Joint proceedings of the 4th Workshop on Semantic Deep Learning (SemDeep-4) and NLIWoD4: Natural Language Interfaces for the Web of Data (NLIWOD-4) and 9th Question Answering over Linked Data challenge (QALD-9) co-located with 17th International Semantic Web Conference (ISWC 2018), Monterey, California, United States of America, October 8th - 9th, 2018 Choi, Key-Sun; Anke, Luis Espinosa; Declerck, Thierry; Gromann, Dagmar; Kim, Jin-Dong; Ngonga Ngomo, Axel-Cyrille; Saleem, Muhammad; Usbeck, Ricardo in CEUR Workshop Proceedings (2018). (Vol. 2241) CEUR-WS.org.
• Proceedings of the 3rd International Workshop on Geospatial Linked Data and the 2nd Workshop on Querying the Web of Data co-located with 15th Extended Semantic Web Conference (ESWC 2018), Heraklion, Greece, June 3, 2018 Wauer, Matthias; Sherif, Mohamed Ahmed; Saleem, Muhammad; Hartig, Olaf; Usbeck, Ricardo; Verborgh, Ruben; Ngomo, Axel-Cyrille Ngonga in CEUR Workshop Proceedings (2018). (Vol. 2110) CEUR-WS.org.
• Second RDF Stream Processing and the Querying the Web of Data Workshops Calbimonte, JP; Tran, MD; Dell’Aglio, D; Le Phuoc, D; Saleem, Muhammad; Usbeck, Ricardo; Verborgh, Ruben; Ngonga Ngomo, Axel-Cyrille (2017).
• Joint Proceedings of BLINK2017: 2nd International Workshop on Benchmarking Linked Data and NLIWoD3: Natural Language Interfaces for the Web of Data co-located with 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, October 21st - to - 22nd, 2017 Usbeck, Ricardo; Ngomo, Axel-Cyrille Ngonga; Kim, Jin-Dong; Choi, Key-Sun; Cimiano, Philipp; Fundulaki, Irini; Krithara, Anastasia in CEUR Workshop Proceedings (2017). (Vol. 1932) CEUR-WS.org.
• The Tale of Sansa Spark. Ermilov, Ivan; Lehmann, Jens; Sejdiu, Gezim; Bühmann, Lorenz; Westphal, Patrick; Stadler, Claus; Bin, Simon; Chakraborty, Nilesh; Petzka, Henning; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille; Jabeen, Hajira (2017).
• Using Multi-Label Classification for Improved Question Answering. Usbeck, Ricardo; Hoffmann, Michael; Röder, Michael; Lehmann, Jens; Ngomo, Axel-Cyrille Ngonga (2017).
• Self-Wiring Question Answering Systems. Usbeck, Ricardo; Huthmann, Jonathan; Duldhardt, Nico; Ngonga Ngomo, Axel-Cyrille (2016).
• Managing Geospatial Linked Data in the GeoKnow Project. Lehmann, Jens; Athanasiou, Spiros; Both, Andreas; Garcia-Rojas, Alejandra; Giannopoulos, Giorgos; Hladky, Daniel; Hoeffner, Konrad; Grange, Jon Jay Le; Ngomo, Axel-Cyrille Ngonga; Sherif, Mohamed Ahmed; Stadler, Claus; Wauer, Matthias; Westphal, Patrick; Zaslawski, Vadim T. Narock, P. Fox (eds.) (2015). (Vol. 20) 51–78.
• Using Caching for Local Link Discovery on Large Data Sets. Hassan, Mofeed M.; Speck, René; Ngonga Ngomo, Axel-Cyrille P. Cimiano, F. Frasincar, G.-J. Houben, D. Schwabe (eds.) (2015). (Vol. 9114) 344–354.
• MANAGING WEB SERVICES COMMUNITIES: A CACHE FOR QUERIES OPTIMISATION. Limam, Hela; Akaichi, Jalel (2014). 1(1) 01–19.

  With the advance of Web Services technologies and the mergence of Web Services into the information space, tremendous opportunities for empowering users and organizations appear in various application domains including electronic commerce, travel, intelligence information gathering and analysis, health care, digital government, etc. However, the technology to organize, search, integrate these Web Services has not kept pace with the rapid growth of the available information space. The number of Web Services to be integrated may be large and continuously changing. The ubiquitous need for Web Services integration across heterogeneous information sources pushed Web Services providers to join each others into Web Services Communities. Different approaches related to the specification, management and querying of a community were proposed. Whoever, current approaches for managing and querying Web Services Communities’ lack of a general formal and clear design. Hence, we propose a framewok which enables the community management then allows community members to share reusable fragments of kow-how in order to optimize query processing among communities .To demonstrate the viability of our approach, we propose a health care community infrastructure for supporting a community management and querying as well as a prototype application that utilizes communities.
• Semantic Quran: A Multilingual Resource for Natural-Language Processing. Sherif, Mohamed Ahmed; Ngonga Ngomo, Axel-Cyrille (2014). 6(4) 339–345.

  In this paper we describe the Semantic Quran dataset, a multilingual RDF representation of translations of the Quran. The dataset was created by integrating data from two different semi-structured sources and aligned to an ontology designed to represent multilingual data from sources with a hierarchical structure. The resulting RDF data encompasses 43 different languages which belong to the most under-represented languages in the Linked Data Cloud, including Arabic, Amharic and Amazigh. We designed the dataset to be easily usable in natural-language processing applications with the goal of facilitating the development of knowledge extraction tools for these languages. In particular, the Semantic Quran is compatible with the Natural-Language Interchange Format and contains explicit morpho-syntactic information on the utilized terms. We present the ontology devised for structuring the data. We also provide the transformation rules implemented in our extraction framework. Finally, we detail the link creation process as well as possible usage scenarios for the Semantic Quran dataset.
• From RDF to Natural Language and Back. Gerber, Daniel; Ngonga Ngomo, Axel-Cyrille P. Buitelaar, P. Cimiano (eds.) (2014). 193–209.
• Ensemble Learning for Named Entity Recognition. Speck, René; Ngomo, Axel-Cyrille Ngonga in Lecture Notes in Computer Science, P. Mika, T. Tudorache, A. Bernstein, C. Welty, C. A. Knoblock, D. Vrandecic, P. Groth, N. F. Noy, K. Janowicz, C. A. Goble (eds.) (2014). (Vol. 8796) 519–534.
• AGDISTIS - Agnostic Disambiguation of Named Entities Using Linked Open Data. Usbeck, Ricardo; Ngonga Ngomo, Axel-Cyrille; Röder, Michael; Gerber, Daniel; Coelho, Sandro Atha’ide; Auer, Sören; Both, Andreas in Frontiers in Artificial Intelligence and Applications, T. Schaub, G. Friedrich, B. O’Sullivan (eds.) (2014). (Vol. 263) 1113–1114.
• Evaluating topic coherence measures. Rosner, Frank; Hinneburg, Alexander; Röder, Michael; Nettling, Martin; Both, Andreas (2014).
• The Design and Implementation of Probabilistic Programming Languages. Goodman, Noah D.; Stuhlmüller, Andreas (2014).

  Probabilistic programming languages (PPLs) unify techniques for the formal description of computation and for the representation and use of uncertain knowledge. PPLs have seen recent interest from the artificial intelligence, programming languages, cognitive science, and natural languages communities. This book explains how to implement PPLs by lightweight embedding into a host language. We illustrate this by designing and implementing WebPPL, a small PPL embedded in Javascript. We show how to implement several algorithms for universal probabilistic inference, including priority-based enumeration with caching, particle filtering, and Markov chain Monte Carlo. We use program transformations to expose the information required by these algorithms, including continuations and stack addresses. We illustrate these ideas with examples drawn from semantic parsing, natural language pragmatics, and procedural graphics.
• Publishing and Interlinking the Global Health Observatory Dataset. Zaveri, Amrapali; Lehmann, Jens; Auer, Sören; Hassan, Mofeed M.; Sherif, Mohamed Ahmed; Martin, Michael (2013). (3) 315–322.

  The improvement of public health is one of the main indicators for societal progress. Statistical data for monitoring public health is highly relevant for a number of sectors, such as research (e.g. in the life sciences or economy), policy making, health care, pharmaceutical industry, insurances etc. Such data is meanwhile available even on a global scale, e.g. in the Global Health Observatory (GHO) of the United Nations's World Health Organization (WHO). GHO comprises more than 50 different datasets, it covers all 198 WHO member countries and is updated as more recent or revised data becomes available or when there are changes to the methodology being used. However, this data is only accessible via complex spreadsheets and, therefore, queries over the 50 different datasets as well as combinations with other datasets are very tedious and require a significant amount of manual work. By making the data available as RDF, we lower the barrier for data re-use and integration. In this article, we describe the conversion and publication process as well as use cases, which can be implemented using the GHO data.
• The Principles and Practice of Probabilistic Programming. Goodman, Noah D. (2013). 399–402.
• Enhanced Generic Information Services Using Mobile Messaging. Saleem, Muhammad; Zahir, Ali; Ismail, Yasir; Saeed, Bilal in Lecture Notes in Computer Science, P. Bellavista, R.-S. Chang, H.-C. Chao, S.-F. Lin, P. M. A. Sloot (eds.) (2010). (Vol. 6104) 510–521.
• Evaluating the disparity between active areas of biomedical research and the global burden of disease employing Linked Data and data-driven discovery. Zaveri, Amrapali; Pietrobon, Ricardo; Ermilov, Timofey; Martin, Michael; Heino, Norman; Auer, Sören H.Herre, R.Hoehndorf, J.Kelso, S.Schulz (eds.) (2010).
• Disentangling the Wikipedia Category Graph for Corpus Extraction. Ngonga Ngomo, Axel-Cyrille; Schumacher, Frank (2009). 39(2) 5–10.
• Disentangling the Wikipedia Category Graph for Corpus Extraction. Ngomo, Axel-Cyrille Ngonga; Schumacher, Frank (2009). 39 5–10.
• Towards an Implicit and Collaborative Evolution of Terminological Ontologies. Ngonga Ngomo, Axel-Cyrille E. Bolisani (ed.) (2008). 65–88.
• Adaptive and Context-Sensitive Information Retrieval. Ngonga Ngomo, Axel-Cyrille S. Hawamdeh (ed.) (2007). (Vol. 5) 289–300.