Occasional Events

An archive of events that are not annual occurrences.

  • Dangermond Lectures: Annual lectures delivered in the Department of Geography colloquium series by an internationally outstanding researcher in geographic information science, supported through a gift from Jack and Laura Dangermond. (Includes videos archived since 2016)
  • GIS Days:  As part of Geography Awareness Week, the annual GIS Day enables GIS users and researchers to exchange ideas and present their work to a wide audience.
  • Golledge Lectures: The Reginald Golledge Distinguished Lecture in Geography was instituted in 1984, when Prof. Reginald Golledge lost his sight. Although Reg passed away in May 2009, the Golledge Distinguished Lecture continues in his honor as part of the Department of Geography colloquium series.
  • Hosted Conferences: Conferences hosted by the UCSB Center for Spatial Studies.
  • Spatial Unconferences: Outreach to domain specialists and applications of spatial information as a primary force to push the frontiers of Geographic Information Science, Spatial Cognition, and related fields.

Spatial Data Science Hangout Series: Reproducibility

The Center for Spatial Studies invites you to join us on Thursday May 20 at 9:00 a.m PT for the next Spatial Data Science Hangout on Reproducibility in Data Science Research. For this special event, we are thrilled to welcome two reproducibility experts as speakers: Daniel Nüst (Institute for Geoinformatics, University of Münster) and Casey O’Hara (BREN School, UC Santa Barbara). 

Don’t miss this event! Everyone is welcome to participate, just keep in mind that these hangouts are meant to be a comfortable environment for graduate students and early career researchers to brainstorm, talk through their imaginative ideas, discuss, and learn from each other.  

To participate in this event, please register here

Upon registration, you will receive a confirmation email with Zoom login details

Casey O’Hara is a PhD candidate in the BREN School at UCSB. After completing his MESM degree in 2014, Casey has worked on the Ocean Health Index, applying data science to communicate the range of economic, ecological, and cultural benefits people can sustainably derive from healthy oceans. In his research, he applies spatial analysis and data science principles to examine the ecological and socioeconomic impacts of human activity and climate change on marine biodiversity.

Abstract: In his talk, Casey will give a short introduction to his paper on better science in less time using open data science tools, including a quick introduction to GitHub for version control and communication, and a comparison of the pros and cons of spatial analysis using ArcMap GIS, ArcMap ModelBuilder, and R. Casey will wrap up his talk by presenting some quick results from his most recent paper: At-risk marine biodiversity faces extensive, expanding, and intensifying human impacts.

Daniel Nüst (https://orcid.org/0000-0002-0024-5046) is a researcher at the Spatio-temporal Modelling Lab at the Institute for Geoinformatics at the University of Münster. Daniel pursues a Ph.D. in the context of the DFG project, Opening Reproducible Research, where he develops tools for creation and execution of research compendia in geography and the geosciences. His professional interest is improving the scholarly publication process with new information technology—of course, with Open Source software! Daniel is reproducibility chair at the AGILE conference series and vice chair of the German association for research software engineering.

Abstract: In his talk, Daniel will give a short introduction to his paper on practical reproducibility in geography and geosciences and present some advanced technologies for reproducibility (notebooks, containers, Binder). Daniel will wrap up his talk by discussing  how reproducibility should be taken into account during peer review and give a brief overview of the initiatives CODECHECK and Reproducible AGILE. 

 

NSF Convergence Accelerator Series Tracks A&B: Carole Goble

FAIRy Stories: The FAIR Data Principles in Theory and in Practice

Carole Goble

University of Manchester

Wednesday, May 19, 2021. 9:00 a.m. (PT)

Required Zoom Registration: here.

Upon registration, you will receive a confirmation email with Zoom login details

The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program is proud to present Carole Goble in its 2021/2022 speaker series on Open Knowledge Networks. The series features researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data.

Abstract. The “FAIR Guiding Principles for scientific data management and stewardship” [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the armies of authors). Over the past 5 years, FAIR has become a movement, a mantra, and a methodology for scientific research and, increasingly, in the commercial and public sector. FAIR is now part of NIH, the European Commission, and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need.”

As a data infrastructure wrangler, I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-led approaches like Schema.org; work with big pharma on specialized FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.

In this talk, I will use some of these projects to shine some light on the FAIR movement. Spoiler alert: Although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role—not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”

[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18.

Bio: Carole Goble is a Professor of Computer Science at the University of Manchester, UK, where she leads a team of Researchers, Research Software Engineers, and Data Stewards. She has spent 25 years working in e-Science on reproducible science, open data and method sharing, knowledge and metadata management and computational workflows in a range of disciplines, and has led many scientific and e-Infrastructure projects and resources at the national and European level. She was an early pioneer of semantic web and linked data approaches in the Life Sciences.

Goble is extensively involved in ELIXIR, the pan-national European Research Infrastructures for Life Science data, and the European Open Science Cloud. She is a co-founder of the UK’s Software Sustainability Institute, coordinates the FAIRDOM infrastructure for research project assets management, and leads work at the international level on FAIR Research Objects and workflows. An advocate of FAIR and Open Data, she serves as the UK representative on the G7 Open Science Working Group and is one of the authors of the original FAIR data principles paper.

Please contact us for follow-up questions.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

ThinkSpatial: Armin Haller

thinkspatial_log<strong></strong>oThe UCSB forum on spatial technologies presents

What Are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web

Armin Haller

Australian National University

3:00 p.m. (PT)

Thursday, April 8, 2021

The recorded video of this talk can be found here.

Slides can be found here.

 

Abstract. Linked Open Data promises to provide guiding principles to publish interlinked knowledge graphs on the Web in the form of findable, accessible, interoperable, and reusable datasets. I will argue that while as such, Linked Data may be viewed as a basis for instantiating the FAIR principles, there are still a number of open issues that cause significant data quality issues even when knowledge graphs are published as Linked Data. In this talk I will first define the boundaries of what constitutes a single coherent knowledge graph within Linked Data, i.e., present a principled notion of what a dataset is and what links within and between datasets are. I will also define different link types for data in Linked datasets and present the results of our empirical analysis of linkage among the datasets of the Linked Open Data cloud. Recent results from our analysis of Wikidata, which has not been part of the Linked Open Data Cloud, will also be presented.

Bio. Armin Haller is an Associate Professor of Business Information Systems at the Australian National University. His research interests include knowledge graph engineering, ontology engineering, linked data, the Internet-of-Things and the semantic Web in general. Haller has received funding from organisations including: the Department of Finance, to develop an ontology framework for government information and an open-source software that allows domain experts to maintain knowledge graphs called Schímatos; and from the Australian Research Council’s Linkage Program, for a project with Sydney Trains. He has published in the premier journals and conferences in his field, including Semantic Web Journal, Journal of Web Semantics, Applied Ontology, World Wide Web Conference and the International Semantic Web Conference. Haller has been an active contributor to several W3C working groups and chaired the Semantic Sensor Network Ontology working group. This work has resulted in an international standard for the description of sensors and actuators on the Internet-of-Things. Haller is a passionate evangelist of Open Government Data and, to this end, has chaired the Australian Government Linked Data Working Group for the last 7 years.

The objectives of the ThinkSpatial brown-bag presentations are to exchange ideas about spatial perspectives in research and teaching, to broaden communication and cooperation across disciplines among faculty and graduate students, and to encourage the sharing of tools and concepts.

Please contact Marcela Suarez (amsuarez@ucsb.edu), or Karen Doehner (kdoehner@spatial.ucsb.edu)), to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

NSF Convergence Accelerator Series Tracks A&B

NSF Convergence Accelerator Tracks A&B Speaker Series

 

The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program are proud to present a speaker series on Open Knowledge Networks. The series features researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data. Due to the closure of UCSB for COVID-19, presentations will temporarily be hosted via Zoom meeting rooms.

Please contact Karen Doehner, kdoehner@spatial.ucsb.edu or Rui Zhu, ruizhu@ucsb.edu to review and schedule possible discussion topics or presentations for this series.

Schedule 2021 (also available on our Google Calendar)

DateSpeaker/Topic
May 19, 2021Carole Goble
University of Manchester

FAIRy Stories: The FAIR Data Principles in Theory and in Practice
March 18, 2021Natasha Noy
Google Research

Google Dataset Search: Building an Open Ecosystem for Dataset Discovery
February 11, 2021Denny Vrandečić
Wikimedia Foundation

Knowledge beyond the Graph: Toward a Multilingual Wikipedia
February 3, 2021Markus Krötzsch
Technische Universität Dresden

Knowledge Graphs for AI: Wikidata and Beyond

NSF Convergence Accelerator Series Tracks A&B: Natasha Noy

NSF Convergence Accelerator Tracks A&B Speaker Series

 

Google Dataset Search: Building an Open Ecosystem for Dataset Discovery

Natasha Noy

Google Research

Thursday, March 18, 2021. 9:00 a.m. (PT)

The recorded video of this talk can be found here.

 

The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program are proud to present Natasha Noy in its 2021/2022 speaker series on Open Knowledge Networks. The series features researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data.

Abstract. There are thousands of data repositories on the Web, providing access to millions of datasets. National and regional governments, scientific publishers and consortia, commercial data providers, and others publish data for fields ranging from social science to life science to high-energy physics to climate science and more. Access to this data is critical to facilitating reproducibility of research results, enabling scientists to build on others’ work, and providing data journalists easier access to information and its provenance. In this talk, we will discuss recently launched Dataset Search by Google, which provides search capabilities over potentially all dataset repositories on the Web. I will talk about the open ecosystem for describing datasets that we hope to encourage.

Bio: Natasha Noy is a senior staff scientist at Google Research where she works on making structured data accessible and useful. She leads the team building Dataset Search, a search engine for all the datasets on the Web. Prior to joining Google, Noy worked at Stanford Center for Biomedical Informatics Research where she made major contributions in the areas of ontology development and alignment, and collaborative ontology engineering. Noy is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). She served as president of the Semantic Web Science Association from 2011 to 2017.

Please contact us for follow-up questions.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

2021 Lightning Talks

The Center for Spatial Studies’ Lightning Talks are designed to be serious or funny, as long as the mantra is followed: “​Enlighten us, but make it quick​.

This year the talks were held on ​Tuesday, March 16, 2021. This annual series of ​3-minute​ lightning talks typically brings together speakers from across the UCSB campus and the local community to enlighten the crowd on thought-provoking ​spatial topics of all kinds​. Since this year the event was held online, it had much broader participation from across the globe with an exciting lineup of speakers from the spatial community worldwide. See the list of selected speakers and the titles of their talks below. Recorded videos can be found here.

Special note: ​The 2021 annual Center for Spatial Studies ​Lightning Talks​ were dedicated to the memory of Paul Wilson, who was one of the Center’s most avid and constant participants of all things spatial. Paul’s presence at our ongoing activities will be sorely missed. See his 2014 Lighting Talk on Whale Traffic Control: https://escholarship.org/uc/item/6t4627c5

Contact:
Rui Zhu ruizhu@geog.ucsb.edu

NSF Convergence Accelerator Series Tracks A&B: Denny Vrandečić

NSF Convergence Accelerator Tracks A&B Speaker Series

 

Knowledge beyond the Graph: Toward a Multilingual Wikipedia

 

Denny Vrandečić

Wikimedia Foundation

Thursday, Feb 11, 2021. 9:00 a.m. (PT)

The recorded video of this talk can be found here.

 

The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program are proud to present the next speaker in its 2021/22 speaker series on Open Knowledge Networks. The series will feature researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data

Abstract. Wikipedia’s vision is a world in which everyone can share in the sum of all knowledge. In its first two decades, this vision has been very unevenly achieved. One of the largest hindrances is the sheer number of languages Wikipedia needs to cover in order to achieve that goal. We argue that we need a new approach to tackle this problem more effectively, a multilingual Wikipedia where content can be shared between language editions.

We have started a new project where we separate this goal into two parts: creating and maintaining content in an abstract notation within a project called Abstract Wikipedia, and creating a new project called Wikifunctions that can translate this notation to natural language. Both parts are fully owned and maintained by the community. This architecture will make more encyclopedic content available to more people in their own language, and at the same time allow more people to contribute knowledge and reach more people with their contributions, no matter what their respective language backgrounds.

Bio: Denny Vrandečić has joined Wikimedia Foundation as Head of Special Projects in order to lead the Abstract Wikipedia project. He obtained his Ph.D. from Karlsruhe Institute of Technology (KIT) in 2012 where he co-founded Semantic MediaWiki, and thereafter launched Wikidata at Wikimedia Deutschland. He then joined Google as an ontologist on the Google Knowledge Graph and later worked as a researcher on the topic of knowledge representation.

Please contact us for follow-up questions.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

NSF Convergence Accelerator Series Tracks A&B: Markus Krötzsch

NSF Convergence Accelerator Tracks A&B Speaker Series

 

Knowledge Graphs for AI: Wikidata and Beyond

 

Markus Krötzsch

Technische Universität Dresden

Wednesday, Feb 3, 2021. 9:00 a.m. (PT)

The recorded video of this talk can be found here.

 

The National Science Foundation’s (NSF) tracks A and B of the Convergence Accelerator program are proud to present the first speaker in their 2021/22 speaker series on Open Knowledge Networks. The series will feature researchers and practitioners widely recognized for their contribution to knowledge graphs, knowledge engineering, and FAIR data

Abstract. Wikidata, the knowledge graph of Wikimedia, has successfully grown from an experimental “data wiki” to a well-organized reference knowledge base with a large and active editor community as well as many academic and industrial uses. It is also a key ingredient of popular AI applications, most prominently of intelligent agents such as Apple’s Siri or Amazon’s Alexa. Of course, human knowledge is fully expected to be in high demand in this time of rapidly advancing AI. And yet, the fact that modern AI relies on the manual labor of thousands of human knowledge modelers is in stark contrast to the common narrative of AI in popular media, which tells us that methods of pattern recognition and statistical function approximation can produce intelligent behavior from unstructured data without much human intervention. However, Wikidata is not a singular exception to the trend but rather a specific solution to a general need of AI: the need for knowledge that is understandable to humans and accessible to computers. Almost every major AI application incorporates such knowledge, and organizations long have realized the need to acquire and develop knowledge resources as part of their AI strategy. The next frontier in AI is the ability of systems to explain and justify their behavior. There, too, we can see the need for knowledge-based technologies as a bridge between human understanding and computational mechanisms, but the task goes far beyond the realms of knowledge representation or machine learning, and will require the effort of all of AI and maybe all of computer science. In my talk, I will give an overview of Wikidata and outline some ongoing research efforts that combine knowledge representation with other methods towards the creation of (more) understandable and accountable AI.

Bio: Markus Krötzsch is a full professor at the Faculty of Computer Science of TU Dresden, where he is holding the chair for Knowledge-Based Systems. He obtained his Ph.D. from Karlsruhe Institute of Technology (KIT) in 2010, and thereafter worked at the Department of Computer Science of the University of Oxford until October 2013. He has contributed to the concept and design of Wikidata, as one of the most prominent examples of applied knowledge representation today. His research made many further contributions to the development and analysis of knowledge modeling languages (including the W3C OWL standard), inference methods, and automated reasoners. Krötzsch is a member of the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) and of the Center for Perspicuous Computing (CPEC).

Please contact us for follow-up questions.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

Spatial Data Science Hangout Series: Reminder

Our Spatial Data Hangout will take place tomorrow (Thursday), December 3 from 10:00 to 11:00 am (Pacific Time). Please join us for this special session focused on Graph Data and Networks, and led by Rui Zhu, Su Burtner, Gengchen Mai, and Mike Johnson.

Zoom Meeting Link: https://ucsb.zoom.us/j/88693830517?pwd=emUyejFWa0s5K0EyUXNaZVI4bnBEdz09

Meeting ID: 886 9383 0517
Passcode: geohangout

We look forward to seeing you!