About the STKO Lab

Do you like astronomy, the universe? Great, 'cause we are the astronomers of the information universe. The STKO Lab is an information observatory that investigates the role of Space and Time for Knowledge Organization. Thus, if you like, you can also spell out the STKO acronym as Spatio- Temporal Knowledge Observatory. Our work spans across different scientific disciplines such as geoinformatics & GIScience, cognitive science, computer science, and the broader earth sciences. While our research interests vary, we typically work on topics related to geospatial semantics, ontologies, and the Semantic Web, spatial data science, (location-based) social networks and volunteered geographic information, geographic information retrieval, Linked Data, Big Data, similarity and analogy-based reasoning, as well as mobile computing and location-based services.

A key driver for our work is the question of how to foster the publishing, retrieval, reuse, and integration of data without restricting semantic heterogeneity which we consider a motor of (interdisciplinary) science. We are also very interested in exploratory user interfaces and novel interaction paradigms to browse and navigate unfamiliar data. Methodologically, our niche is the combination of theory-driven (e.g., semantics) and data-driven (e.g., data mining) approaches. While we will be adding content to this page over time, you can find up-to-date information about our research, publications, and organized events following the links from the people site.

On the Prospects of Blockchain and Distributed Ledger Technologies for Open Science and Academic Publishing

Distributed ledger technologies such as blockchains and smart contracts have the potential to transform many sectors ranging from the handling of health records to real estate. Here we discuss the value proposition of these technologies and crypto-currencies for science in general and academic publishing in specific. We outline concrete use cases, provide an informal model of how the Semantic Web journal's peer-review workflow could benefit from distributed ledger technologies, and also point out challenges in implementing such a setup.

Bo Yan was awarded The Jack and Laura Dangermond Graduate Fellowship

The Jack and Laura Dangermond Graduate Fellowship is awarded to an outstanding graduate student in Geography studying within the area of Geographic Information Science. The recipient will hold the title “Jack and Laura Dangermond Fellow” in residence for 2017-2018 and will receive a stipend of $5,000, allowing its holder to devote more time to imaginative and creative research.

New Paper about ADCN Published in TGIS

As 2018 Winter quarter begins, our team published a new research article in Transactions in GIS:

Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao. ADCN: An Anisotropic Density-Based Clustering Algorithm for Discovering Spatial Point Patterns with Noise. Transactions in GIS. DOI:10.1111/tgis.12313

Place2Vec Ground Truth Data Available

We have presented our Place2Vec paper at this year's ACM Sigspatial conference and have attracted a lot of attention. In order to promote future research in place type similarity measurements, we have published the ground truth data we collected using Amazon Mechanical Turk. You can download the data from this repository: https://github.com/BoYanSTKO/place2vec .

We are recruiting new graduate students

The STKO Lab at UCSB is looking for highly-motivated and talented students to further strengthen our team. Please contact Krzysztof Janowicz, ideally before you apply. STKO works on a wide range of topics and our work style and the lab's atmosphere is what you would typically expect from a start-up. We are a very dynamic and well-funded team with projects from NSF, government agencies, and key industry players. Previous STKO students scored top jobs in industry and academia.

Two Papers Accepted at ACM SIGSPATIAL 2017

Full Paper
Bo Yan, Krzysztof Janowicz, Gengchen Mai, and Song Gao. From ITDL to Place2Vec – Reasoning About Place Type Similarity and Relatedness by Learning Embeddings From Augmented Spatial Contexts. In Proceedings of SIGSPATIAL’17, Los Angeles Area, CA, USA, November 7–10, 2017, 10 pages. https://doi.org/10.1145/3139958.3140054

Song Gao was selected as the Winner for 2017 Young Researcher Award in GIScience

Winners of 2017 'Young Researcher Award' in GIScience was just announced!

The Austrian Academy of Sciences' Commission for GIScience annually selects the winner of a 'Young Researcher' competition, based on an outstanding publication submitted by applicants. This year's review-and-selection process turned into a tight race, with two entries tied for first place.

Pages