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)

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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.

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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.

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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.

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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.

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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.

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ThinkSpatial: Gengchen Mai

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

Space2Vec: Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

Gengchen Mai

STKO Lab

University of California, Santa Barbara

11:30 a.m. (PT)

Tuesday, Dec 1, 2020

Zoom:  https://ucsb.zoom.us/meeting/register/tZUtcu6rrzosE9VEnfMGptAxbxe4zhNILoHY

Upon registration, you will receive access to this link

Abstract. Unsupervised text encoding models have recently fueled substantial progress in NLP. The key idea is to use neural networks to convert words in texts to vector space representations (embeddings) based on word positions in a sentence and their contexts, which are suitable for end-to-end training of downstream tasks. We see a strikingly similar situation in spatial analysis, which focuses on incorporating both absolute positions and spatial contexts of geographic objects such as POIs into models. A general-purpose representation model for space is valuable for a multitude of tasks. However, no such general model exists to date beyond simply applying discretization or feed-forward nets to coordinates, and little effort has been put into jointly modeling distributions with vastly different characteristics, which commonly emerges from GIS data. Meanwhile, Nobel Prize-winning Neuroscience research shows that grid cells in mammals provide a multi-scale periodic representation that functions as a metric for location encoding and is critical for recognizing places and for path-integration. Therefore, we propose a representation learning model called Space2Vec to encode the absolute positions and spatial relationships of places. We conduct experiments on two real-world geographic data for two different tasks: (1) predicting types of POIs given their positions and context, (2) image classification leveraging their geo-locations. Results show that because of its multi-scale representations, Space2Vec outperforms well-established ML approaches such as RBF kernels, multi-layer feed-forward nets, and tile embedding approaches for location modeling and image classification tasks. Detailed analysis shows that all baselines can at most well handle distribution at one scale but show poor performances in other scales. In contrast, Space2Vec ’s multi-scale representation can handle distributions at different scales.

 

Bio. Gengchen Mai is a Ph.D. candidate at the Space and Time for Knowledge Organization Lab in the Department of Geography, University of California, Santa Barbara. His Ph.D. adviser is Prof. Krzysztof Janowicz. His research interests include Machine Learning/Deep Learning, GIScience, Geographic Question Answering, NLP, Geographic Information Retrieval, Knowledge Graph, and Semantic Web. Currently, Mai’s research is highly focused on Geographic Question Answering and Spatially-Explicit Machine Learning models. He received his B.S. Degree in Geographic Information System from Wuhan University. Thus far, he has completed four AI/ML research-based internships at Esri Inc., SayMosaic Inc., Apple Map, and Google X. He now serves as a machine learning consultant/advisor for Google X.

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

ThinkSpatial: Patricia Murrieta-Flores

thinkspatial_logo
On Tuesday, November 24, 2020, the UCSB forum on spatial thinking presents

Subaltern Spatial Thinking: Towards a decolonial approach to spatial technologies

 

Patricia Murrieta-Flores

Lancaster University

11:30 a.m. Tuesday, November 24, 2020 | Zoom*

Abstract:

The quick emergence of digital technologies and the rise of the use of computational approaches and tools in all disciplines have substantially changed the ways that we do research, expediting and placing at our fingertips datasets and information at a scale that was impossible before. While our societies have enthusiastically embraced this change, technologies are neither unbiased nor innocent. In the wake of Geographic Information Systems (GIS), a now-ubiquitous tool, disciplines such as history and archaeology have adopted this technology for the study of the past. This is well represented in the creation of the field called the Spatial Humanities. Rooted in a modern, western and Cartesian conception of space, while GIS has proved invaluable to advance both research and discussions related to geography, space and place in these fields, there is the need for critical reflection regarding its use, and to work towards the development of more inclusive spatial tools. Given GIS’ increasing popularity in Humanities research worldwide, and especially its emergence in the Global South, I will present a case study from research produced in the project “Digging into Early Colonial Mexico: A large-scale computational analysis of 16th century historical sources”, aiming to showcase how through the analysis of Mesoamerican spatial thinking, we can highlight the need of carefully considering the use of particular technologies in historical research, and discuss a decolonial approach to technology.

Bio:

Patricia Murrieta-Flores is Senior Lecturer and Co-Director of Digital Humanities at Lancaster University. Her interest lies in the application of technologies for Humanities and her primary research area is the Spatial Humanities. Her main focus is the investigation of different aspects of space, place and time using a range of technologies including GIS, NLP, Machine Learning and Corpus Linguistics approaches. Patricia is the PI on the Transatlantic Platform (T-AP) funded project ‘Digging into Early Colonial Mexico: A large-scale computational analysis of 16th century historical sources’, and also collaborator and Co-I in multiple projects funded by the ERC, ESRC, AHRC, HERA, and the Paul Mellon Centre among others. She has edited and contributed to multiple books on Digital Humanities, Cultural Heritage, the use of GIS and other technologies in Archaeology, History, and Literature, and she has published multiple articles exploring theories and methodologies related to space and place. She is currently Executive Board Secretary Elect of the Alliance of Digital Humanities Organizations (ADHO).

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), Karen Doehner (kdoehner@spatial.ucsb.edu), or Emmanuel Papadakis (epd@ucsb.edu), to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

*This talk is a part of the spatial series Knowledge Representation and GeoHumanities; upon registration, you can access all the talks of the series using the provided link.

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ThinkSpatial: Karl Grossner

thinkspatial_logo
On Tuesday, October 27, 2020, the UCSB forum on spatial thinking presents

Representing Place for World Historical Gazetteer

 

Karl Grossner

University of Pittsburgh World History Center

11:30 a.m. Tuesday, October 27, 2020 | Zoom*

Abstract:

The recently launched World Historical Gazetteer (WHG) web platform aggregates contributions of information about named places drawn from historical source material by researchers studying the past in numerous humanities and social science fields. There are no constraints upon spatial or temporal extents, nor on scale of features, however, the project focus to date is on populated places, administrative units, natural geographic features, and regions of all kinds. Contributed datasets can be of any size.

To date, the WHG data stores hold records for about 1.8 million places having over 3 million name variants. Of these, only 60,000 have explicit temporal attributes; the remainder have been accessioned from the Getty Thesaurus of Geographic Names (TGN) and have unspecified temporal scope. We anticipate that the temporally scoped portion of WHG data will eventually grow to upwards of 10 million records. The project’s overarching goal is a free global resource useful for:

  1. geocoding of historical source materials, enabling mapping and spatial analysis of individual texts, corpora, and datasets
  2. linking historical research datasets and projects via shared references to places
  3. teaching, particularly geospatial perspectives in History
  4. via APIs, support for digital historical atlases and story maps

Linked Places format
As a data aggregation platform, WHG requires a standard contribution format. Researchers model data to suit their purposes, impacted by the nature of the source material and their conceptual model(s) of the phenomena being studied. We have developed the Linked Places format jointly with the Pelagios project, for use in both systems. Linked Places format is a hybrid: it is valid GeoJSON which has been extended with “when” objects for temporal scoping (GeoJSON-T), and it is valid JSON-LD v1.1, an RDF syntax.

Linked Places format enables relatively rich descriptions of places, including the temporal scoping of names, types, geometries, and relations with other places. We also developed a simpler and less expressive delimited text format, LP-TSV, and an automated transform is performed on ingest to WHG.

Toward Knowledge Representation
In this talk, Grossner will give an overview of Linked Places format, and the somewhat unorthodox path taken in development of its conceptual model, syntax, and supporting ontology. That path reflects the way that ontologies can emerge as working systems are developed, not as an afterthought, but as a product of investigating the entities and relations of a domain as the many variations of entities and properties “in the wild” present themselves.

Bio:

Karl Grossner is an independent GIScience researcher working to develop novel models, standard formats, and semantically-enabled software and systems supporting the emerging genre of digital historical atlases. Broadly, his research interest concern “computing place.” A co-founder of the GeoHumanities SIG within the Alliance for Digital Humanities Organizations (2013), Grossner is an active member of that global and trans-disciplinary community. From 2017 to the present, Grossner has served as Technical Director of the World Historical Gazetteer project at the University of Pittsburgh’s World History Center (whgazetteer.org).

After earning his Ph.D. in Geography at Santa Barbara in 2010, Grossner remained at the Center for Spatial Studies for a year, co-leading the NSF-funded TeachSpatial project (teachspatial.org) with Donald Janelle, the Center’s Program Director at the time. Following that, he worked for five years as a digital humanities research developer at Stanford University, building several significant interactive scholarly web applications in partnership with faculty members. Grossner’s side projects in recent years include GeoJSON-T, a temporal extension to the GeoJSON standard, and Linked Paths, experimental web software for representing, sharing, and analyzing data about historical geographic movement, including journeys, flows, and named routes.

Material:
ThinkSpatial-Grossner

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), Karen Doehner (kdoehner@spatial.ucsb.edu), or Emmanuel Papadakis (epd@ucsb.edu), to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

*This talk is a part of the spatial series Knowledge Representation and GeoHumanities; upon registration, you can access all the talks of the series using the provided link.

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

ThinkSpatial: Nicola Guarino

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On Tuesday, October 13, 2020, The UCSB forum on spatial thinking presents

Events and their (Spatial) Context: On the Semantics of Locative Modifiers

 

Nicola Guarino

ISTC-CNR Laboratory for Applied Ontology, Trento

9:00 a.m. Tuesday, October 13, 2020 | Zoom*

Abstract:

The notion of event is intimately connected to that of context. Describing an event means not just saying what happened, but also specifying how it happened, by adding details (generically called modifiers) that often involve the broader context where the event occurred. These modifiers often express locative information. But what are we referring to, when we add a locative modifier? This is an issue that has been investigated in the literature on linguistic semantics (especially by Claudia Maienborn), and is still rather open. Consider for instance “Maradona signed the contract in Argentina” versus “Maradona signed the contract on the last page.” While in the first case the modifier clearly denotes the location of the signature event, in the second case it refers to the location of something else. Similarly, in “John kissed Mary on the boat” the semantics of the locative modifier is clear, but in “John kissed Mary on the cheek” the semantics is different. In this talk, I will present a novel theory of events that explains these phenomena in terms of relationships between the modifier and the event’s context. It is a sort of microscopic approach based on the Aristotelian theory of change, according to which the actual subjects of change are individual qualities inhering in the participants, and not the participants themselves. In this view, an event (in its simplest form) is a single quality manifestation, i.e., the occurrence of a change (or unchanged) with respect to one of its qualities. More generally, ordinary events are clusters of quality manifestations, consisting of a focus accounting for what happens, and an internal context accounting for how it happens. Event kinds provide criteria to carve up events from the broader context by determining their focus and their internal context.

Bio:

Nicola Guarino is a retired research associate at the Institute of Cognitive Sciences and Technologies of the Italian National Research Council (ISTC-CNR), and former director of the ISTC-CNR Laboratory for Applied Ontology (LOA) based in Trento. Since 1991 he has been playing a leading role in the ontology field, developing a strongly interdisciplinary approach that combines together Computer Science, Philosophy, and Linguistics. The impact of such an approach is testified by a long list of widely cited papers and many keynote talks and tutorials in major conferences involving different communities. Among the most well-known results of his lab, the OntoClean methodology and the DOLCE foundational ontology. Guarino has been the founder and editor-in-chief (with Mark Musen, Stanford University) of the Applied Ontology journal, founder and former president of the International Association for Ontology and its Applications (IAOA), and editorial board member of Int. Journal of Semantic Web and Information Systems and Journal of Data Semantics. He is also a founding member of the Italian Association for Artificial Intelligence and fellow of the European Association for Artificial Intelligence (EurAI).

On the theoretical side, Guarino’s current research interests are focusing on the ontological foundations of knowledge representation and conceptual modeling and specifically the ontology of events and relationships (collaborating with Giancarlo Guizzardi to the new version of the UFO ontology), while on the application side his research is focusing on enterprise modeling and the ontology of economics. He is also interested in leveraging ontological analysis and semantic technologies to improve cognitive transparency, social accountability, and the participatory governance of artificial intelligence artifacts.

Material:
ThinkSpatial-Nicola-Guarino

The objectives of the ThinkSpatial 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 Karen Doehner, kdoehner@spatial.ucsb.edu or Emmanuel Papadakis epd@ucsb.edu, to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

*This talk is a part of the spatial series Knowledge representation and GeoHumanities; upon registration, you can access all the talks of the series using the provided link.

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