About the project

# Problem In open-data portals, such as the mCLOUD, citizens, researchers and entrepreneurs have access to a large number of datasets. Many of these data on the topics of weather or traffic are usually unstructured and not related to each other. The use of the available data requires expert knowledge and complicates the machine processing of the contents.

Project goal

Specifically, the LIMBO project aims to set up a Mobility Data Space to make data from the Federal Ministry of Transport and Digital Infrastructure accessible for as many applications as possible. The proposed approach will encourage the reuse of data by third parties (industry, startups, citizens). The planned data catalog will in particular pave the way for innovative services in the field of mobility.

Execution

The project is implemented using semantic technologies that allow the linking of different data sources (linked data) and a formal description (semantics). The goal is to firmly anchor the Mobility Data Space with open Semantic Web data sources (DBpedia, Linked Geo Data). Deploying as linked data provides the ability to network mobility data with new data sources from other domains, and to develop innovative mobility solutions and new business models based on this. The prototype of the system to be developed is being tested in various application scenarios.

Staff

Daniel Vollmers Diego Moussallem Kevin Dreßler

Partners

Fraunhofer IAIS USU Software AG YellowMap eccenca GmbH appPlant GmbH CISS TDI GmbH Institut für Angewandte Informatik Technische Universität Berlin

Publications

LIMES - A Framework for Link Discovery on the Semantic Web

By Axel-Cyrille Ngonga Ngomo, Mohamed Ahmed Sherif, Kleanthi Georgala, Mofeed Hassan, Kevin Dreßler, Klaus Lyko, Daniel Obraczka, Tommaso Soru

KI - Künstliche Intelligenz, German Journal of Artificial Intelligence - Organ des Fachbereichs "Künstliche Intelligenz" der Gesellschaft für Informatik e.V., 2021, #article

LIGER -- Link Discovery with Partial Recall

By Kleanthi Georgala, Mohamed Ahmed Sherif, Axel-Cyrille Ngonga Ngomo

Proceedings of Ontology Matching Workshop 2020, 2020, #inproceedings

LIGON -- Link Discovery with Noisy Oracles

By Mohamed Ahmed Sherif, Kevin Dreßler, Axel-Cyrille Ngonga Ngomo

Proceedings of Ontology Matching Workshop 2020, 2020, #inproceedings

Applying edge-counting semantic similarities to Link Discovery: Scalability and Accuracy

By Kleanthi Georgala, Michael Röder, Mohamed Ahmed Sherif, Axel-Cyrille Ngonga Ngomo

Proceedings of Ontology Matching Workshop 2020, 2020, #inproceedings

ProBERT: Product Data Classification with Fine-tuning BERT Model

By Hamada M. Zahera, Mohamed Ahmed Sherif

Proceedings of Mining the Web of HTML-embedded Product Data Workshop (MWPD2020), 2020, #inproceedings

Ranking on Very Large Knowledge Graphs

By Abdelmoneim Amer Desouki, Michael Röder, Axel-Cyrille Ngonga Ngomo

Proceedings of the 30th ACM Conference on Hypertext and Social Media, 2019, #inproceedings

Jointly Learning from Social Media and Environmental Data for Typhoon Intensity Prediction

By Hamada M. Zahera, Mohamed Ahmed Sherif, Axel-Cyrille Ngonga Ngomo

K-CAP 2019: Knowledge Capture Conference, 2019, #inproceedings

Do your Resources Sound Similar? On the Impact of Using Phonetic Similarity in Link Discovery

By Abdullah Fathi Ahmed, Mohamed Ahmed Sherif, Axel-Cyrille Ngonga Ngomo

K-CAP 2019: Knowledge Capture Conference, 2019, #inproceedings

Dragon: Decision Tree Learning for Link Discovery.

By Daniel Obraczka, Axel-Cyrille Ngonga Ngomo

ICWE, 2019, #inproceedings

Entity Linking in 40 Languages using MAG

By Diego Moussallem, Ricardo Usbeck, Michael Röder, Axel-Cyrille Ngonga Ngomo

The Semantic Web, ESWC 2018, Lecture Notes in Computer Science, 2018, #inproceedings

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

, 2018, #proceedings

DICE @ TREC-IS 2018: Combining Knowledge Graphs and Deep Learning to Identify Crisis-Relevant Tweets

By Hamada M. Zahera, Rricha Jalota, Ricardo Usbeck

Proceedings of the Twenty-Seventh Text REtrieval Conference, TREC 2018, Gaithersburg, Maryland, USA, November 14-16, 2018, 2018, #inproceedings

9th Challenge on Question Answering over Linked Data (QALD-9) (invited paper)

By Ricardo Usbeck, Ria Hari Gusmita, Axel-Cyrille Ngonga Ngomo, Muhammad Saleem

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., 2018, #inproceedings