Hi Friends,
I submitted a Wikimedia project grant proposal for the 2020 round. I would
really appreciate it if you could check it out and endorse it if you
support the proposal.
https://meta.wikimedia.org/wiki/Grants:Project/JackieKoerner/Addressing_Imp…
The last day to share support is just days away. If addressing bias on
Wikipedia is important to you now is the time to speak up!
Thank you!
Best,
Jackie
--
Jackie Koerner, Ph.D.
jackiekoerner.com
[Apologies for cross-posting]
=====================================================================
EKAW 2020 CALL FOR PAPERS
https://ekaw2020.inf.unibz.it
Part of the Bolzano Summer of Knowledge 2020
https://summerofknowledge.inf.unibz.it
=====================================================================
KEY UPDATES
- Keynote Speakers:
* Axel-Cyrille Ngonga Ngomo (Paderborn University, Germany)
* Toby Walsh (University of New South Wales, Australia)
* Diana Maynard (University of Sheffield, United Kingdom)
- Workshops: Details of accepted workshops are now online at: https://ekaw2020.inf.unibz.it/accepted-workshops
- Coronavirus Pandemic: In light of potential travel disruption arising from the 2020 coronavirus pandemic, the EKAW 2020 organisation team is committed to finding alternative solutions, such as remote participation, for another successful EKAW conference.
=====================================================================
RESEARCH, IN-USE AND POSITION PAPERS
The 22nd International Conference on Knowledge Engineering and Knowledge Management concerns all aspects of eliciting, acquiring, modeling and managing knowledge, and the role of knowledge in the construction of systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and so on.
The special theme of EKAW 2020 is "Ethical and Trustworthy Knowledge Engineering". While recent reported breaches relate predominantly to machine learning systems, it is not impossible to envision ethical breaches in knowledge engineering more broadly and, conversely, devise methods and techniques to ensure no or minimal harm in knowledge acquisition, modelling, and knowledge-driven information systems. EKAW 2020 will put a special emphasis on the importance of Knowledge Engineering and Knowledge Management to keep fostering trustworthy systems.
PROCEEDINGS
=============
The proceedings of the research track will be published by Springer Verlag in the Lecture Notes in Artificial Intelligence series<http://www.springer.com/lncs>.
TOPICS OF INTEREST
==================
EKAW 2020 welcomes papers dealing with theoretical, methodological, experimental, and application-oriented aspects of knowledge engineering and knowledge management.
In particular, but not exclusively, we solicit papers about methods, tools and methodologies on the following topics:
- Ethical and Trustworthy Knowledge Engineering
* Ethics and trust in automated reasoning
* Algorithmic transparency and explanations for knowledge-based systems
* Knowledge and ethics
* Ontologies for trust and ethics
* Trust and privacy in knowledge representation
- Knowledge Engineering and Acquisition
* Tools and methodologies for ontology engineering
* Ontology design patterns
* Ontology localisation
* Multilinguality in ontologies
* Ontology alignment
* Knowledge authoring and semantic annotation
* Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
* Semi-automatic knowledge acquisition, e.g., ontology learning
* Collaborative knowledge acquisition and formalisation
* Mining the Semantic Web and the Web of Data
* Ontology evaluation and metrics
* Uncertainty and vagueness in knowledge representation
* Dealing with dynamic, distributed and emerging knowledge
- Knowledge Management
* Methodologies and tools for knowledge management
* Knowledge sharing and distribution, collaboration
* Best practices and lessons learned from case studies
* Provenance and trust in knowledge management
* FAIR data and knowledge
* Methods for accelerating take-up of knowledge management technologies
* Corporate memories for knowledge management
* Knowledge evolution, maintenance and preservation
* Incentives for human knowledge acquisition and data quality improvement (e.g. games with a purpose)
- Social and Cognitive Aspects of Knowledge Representation
* Similarity and analogy-based reasoning
* Knowledge representation inspired by cognitive science
* Synergies between humans and machines
* Knowledge emerging from user interaction and networks
* Knowledge ecosystems
* Expert finding, e.g., by social network analysis
* Collaborative and social approaches to knowledge management and acquisition
* Crowdsourcing in knowledge management
- Knowledge discovery
* Mining patterns and association rules
* Mining complex data: numbers, sequences, trees, graphs
* Formal Concept Analysis and extensions
* Numerical data mining methods and knowledge processing
* Mining the web of data for knowledge construction
* Text mining and ontology engineering
* Classification and clustering for knowledge management
* Symbolic and sub-symbolic learning machine learning
- Applications in specific domains such as:
* eGovernment and public administration
* Life sciences, health and medicine
* Humanities and Social Sciences
* Automotive and manufacturing industry
* Cultural heritage
* Digital libraries
* Geosciences
* ICT4D (Knowledge in the developing world)
TYPE OF PAPERS
===============
We will accept different types of papers. The papers will all have the same status and follow the same formatting guidelines in the proceedings but will receive special treatment during the reviewing phase. In particular, each paper type will be subject to its own evaluation criteria. The Programme Committee will also make sure that there is a reasonable balance of the paper types accepted. At submission time the paper has to be clearly identified as belonging to one of the following categories.
* Research papers: These are standard papers presenting a novel method, technique or analysis with appropriate empirical or other types of evaluation as a proof-of-concept. The main evaluation criteria here will be originality, technical soundness and validation.
* In-use papers: Here we are expecting papers describing applications of knowledge management and engineering in real environments. Applications need to address a sufficiently interesting and challenging problem on real-world datasets, involving many users, etc. The focus is less on the originality of the approach and more on presenting systems that solve a significant problem while addressing the particular challenges that come with the use of real-world data. Evaluations are essential for this type of paper and should involve a representative subset of the actual users of the system.
* Position papers: We invite researchers to also publish position papers, which describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order to contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments.
IMPORTANT DATES
================
* Abstract deadline: April 23, 2020
* Submission deadline: April 30, 2020
* Notification of acceptance: June 23, 2020
* Camera-ready paper: July 2, 2020
* Conference days: September 16-20, 2020
All submission deadlines are 23:59:59 Hawaii Time.
SUBMISSIONS
============
Pre-submission of abstracts is a strict requirement. All papers and abstracts have to be submitted electronically via EasyChair<https://easychair.org/conferences/?conf=ekaw2020> (https://easychair.org/conferences/?conf=ekaw2020).
All submissions for research, in-use, and position papers must be in English, and no longer than 15 pages. Papers that exceed this limit will be rejected without review.
Submissions must be in PDF, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer's Author Instructions<http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>.
ORGANISATION
============
General Chairs
* Oliver Kutz (Free University of Bozen-Bolzano, Italy)
* Rafael Penaloza (University of Milano-Bicocca, Italy)
Program Chairs
* Michel Dumontier (Maastricht University, the Netherlands)
* Maria Keet (University of Cape Town, South Africa)
Workshop Chairs
* Anastasia Dimou (Ghent University, Belgium)
* Karl Hammar (Jonkoping University, Sweden)
Posters & Demos Chairs
* Daniel Garijo (University of Southern California, USA)
* Agnieszka Lawrynowicz (Poznan University of Technology, Poland)
Publicity Chair
* Rafael Goncalves (Stanford University, USA)
Local Committee
* Pietro Galliani (Free University of Bozen-Bolzano, Italy)
* Guendalina Righetti (Free University of Bozen-Bolzano, Italy)
* Nicolas Troquard (Free University of Bozen-Bolzano, Italy)
--Apologies for cross-posting--
This is the 1st call for systems for the SemTab 2020 Semantic Web Challenge on Tabular Data to Knowledge Graph Matching collocated with the International Semantic Web Conference: http://www.cs.ox.ac.uk/isg/challenges/sem-tab/
Tabular data to Knowledge Graph (KG) matching is the process of assigning semantic tags from Knowledge Graphs (e.g., Wikidata or DBpedia) to the elements of the table. This task however is often difficult in practice due to metadata (e.g., table and column names) being missing, incomplete or ambiguous.
This challenge aims at benchmarking systems dealing with the tabular data to KG matching problem, so as to facilitate their comparison on the same basis and the reproducibility of the results.
Challenge Tasks
----------------------
The challenge includes the following tasks organised into several evaluation rounds:
- Assigning a semantic type (e.g., a KG class) to a column: CTA task.
- Matching a cell to a KG entity: CEA task.
- Assigning a KG property to the relationship between two columns: CPA task
The challenge will be run with the support of the AICrowd platform.
Discussion group
----------------------
We have a discussion group for the challenge where we share the latest news with the participants and we discuss issues risen during the evaluation rounds:
https://groups.google.com/d/forum/sem-tab-challenge
Tentative Dates
----------------------
March 23: Round 1 opens.
April 30: Round 1 closes.
May 8: Round 2 opens.
July 7: Round 2 closes.
July 8: Best participants in Rounds 1 and 2 are invited to present their results during the ISWC conference and the Ontology Matching workshop. Check the ISWC student travel grants.
July 15: Round 3 opens.
August 31: Round 3 closes.
September 15: Round 4 opens.
October 15: Round 4 closes.
October 20: System paper submissions (preliminary version).
November 2-3: Ontology Matching workshop.
November 4-6: Challenge Presentation and prize announcement.
November 15: System paper submissions (final version).
Organisation
----------------------
This track is organised by Kavitha Srinivas (IBM Research), Ernesto Jimenez-Ruiz (City, University of Lonson; University of Oslo), Oktie Hassanzadeh (IBM Research), Jiaoyan Chen (University of Oxford) and Vasilis Efthymiou (IBM Research). If you have any problems working with the datasets or any suggestions related to this challenge, do not hesitate to contact us via the discussion group.
Acknowledgements
----------------------
The challenge is currently supported by the SIRIUS Centre for Research-driven Innovation and IBM Research.
--
Ernesto Jiménez-Ruiz
Lecturer in Artificial Intelligence
Department of Computer Science
School of Mathematics, Computer Science and Engineering
City, University of London
T: +44 (0)20 7040 0212
https://www.city.ac.uk/people/academics/ernesto-jimenez-ruiz
Hi all,
join us for our monthly Analytics/Research Office hours on 2020-03-25 at
17.00-18.00 (UTC). Bring all your research questions and ideas to discuss
projects, data, analysis, etc…
To participate, please join the IRC channel: #wikimedia-research [1].
More detailed information can be found here [2] or on the etherpad [3] if
you would like to add items to agenda or check notes from previous meetings.
Best,
Martin
[1] irc://chat.freenode.net:6667/wikimedia-research
[2] https://www.mediawiki.org/wiki/Wikimedia_Research/Office_hours
[3] https://etherpad.wikimedia.org/p/Research-Analytics-Office-hours
--
Martin Gerlach
Research Scientist
Wikimedia Foundation
Dear All,
I didn't send this earlier because it isn't strictly Wiki related, but
seeing other recent posts to the list I wanted to share as I think many
people here would be good candidates. If you are interested by unable to
send a CV by the deadline, please just tell me.
We're hiring a Research Fellow at Meedan, a non-profit working with
journalists and human-rights defenders to build technology, execute
programmes, and conduct research.
The main project will be quantitative research analysing communication
dynamics in large datasets from messaging platforms. We have messaging app
data already collected for the project from tip lines operated by media
partners and webscraping.
This position is available remotely or in Oxford, UK, or San Francisco,
USA.
Further details are at:
https://meedan.com/jobs/research-fellow/
Please apply by 27 March 2020 and feel free to direct any questions to me.
Best wishes,
Scott
--
Dr Scott A. Hale
Senior Research Fellow, University of Oxford
Director of Research, Meedan
Turing Fellow, Alan Turing Institute
http://scott.hale.us/
scott(a)meedan.com
Some of you may be interested in the position below.
Best,
Leila
---------- Forwarded message ---------
From: MPIDR - Career <career(a)demogr.mpg.de>
Date: Mon, Mar 23, 2020 at 5:17 AM
Subject: Post-doc postion at Max Planck Institute for Demographic
Research, Rostock, Germany
To:
Dear Sir or Madame,
Hopefully this message finds you well. We would like to distribute the
attached post-doc ad on behalf of Emilio Zagheni in his Laboratory of
Digital and Computational Demography at the Max Planck Institute for
Demographic Research in Rostock, Germany. The details of the job
vacancy and how to apply can be found here rsp. in the attached PDF:
https://www.demogr.mpg.de/en/career_6122/jobs_fellowships_1910/postdocs_res…
Please kindly distribute these vacancies among your fellow researchers
and students at your institution.
Data protection notice:
We use your data exclusively to inform you about current news from the
MPIDR. Please use the following contact to obtain information on
personal data stored about you or to have the data changed at any
time:
career(a)demogr.mpg.de
Should you no longer wish to receive news from the MPIDR, please click
the following link:
Unsubscribe from MPIDR news distribution list and kindly name the
email adress this was sent to in case of delegation.
Information on data protection can be accessed at any time on the
website of the Max Planck Institute for Demographic Research
(https://www.demogr.mpg.de/en/privacy_policy_5725/default.htm).
Thanks a lot!
Stay safe and healthy.
With best wishes from Rostock,
On behalf of
Max Planck Institute for Demographic Research
Human Ressources
Konrad-Zuse-Str. 1
D-18057 Rostock
Germany
http://www.demogr.mpg.de
----------
This mail has been sent through the MPI for Demographic Research.
Should you receive a mail that is apparently from a MPI user without
this text displayed, then the address has most likely been faked. If
you are uncertain about the validity of this message, please check the
mail header or ask your system administrator for assistance.
The February 2020 issue of the Wikimedia Research Newsletter is out:
https://meta.wikimedia.org/wiki/Research:Newsletter/2020/February
In this issue:
1 How much would one need to pay readers to give up Wikipedia? $50 billion/year in the US alone.2 Briefly3 Other recent publications3.1 "Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems"3.2 Despite content saturation, "the activities of editors are still improving with time"3.3 "Individual and collaborative information behaviour of Wikipedians in the context of their involvement with Hebrew Wikipedia"3.4 "Knowledge curation work in Wikidata WikiProject discussions"3.5 "Building Knowledge Graphs: Processing Infrastructure and Named Entity Linking"3.6 "A deep learning-based quality assessment model of collaboratively edited documents: A case study of Wikipedia"3.7 "Wikipedia: Why is the common knowledge resource still neglected by academics?"3.8 "Finding Synonymous Attributes in Evolving Wikipedia Infoboxes"3.9 "Weakly Supervised Multilingual Causality Extraction from Wikipedia"3.10 "Temporal Analysis of Entity Relatedness and its Evolution using Wikipedia and DBpedia"3.11 Some of the editors contributing information about the circadian sleep cycle don't have one
*** 12 recent publications were covered or listed in this issue ***
Masssly and Tilman Bayer
---
Wikimedia Research Newsletter
https://meta.wikimedia.org/wiki/Research:Newsletter/
* Follow us on Twitter: @WikiResearch
* Like us on Facebook: Facebook.com/WikiResearch/
* Receive this newsletter by mail: Research-newsletter Mailing List - Wikimedia
Hi folks,
I am conducting a project on the value of using celebrity names in newspaper headlines. I am seeking your help to see if it is possible to get historical page view data for biographies between he years 2013 to 2015. I’ve been experimenting with this legacy API that looked promising: https://wikimedia.org/api/rest_v1/#/Pageviews%20data/get_metrics_pageviews_… <https://wikimedia.org/api/rest_v1/#/Pageviews data/get_metrics_pageviews_per_article__project___access___agent___article___granularity___start___end_> However, I receive the error “the date(s) you used are valid, but we either do not have data for those date(s), or the project you asked for is not loaded yet” whenever I execute a search for a biography for dates preceding summer 2015. I get the same message for searching for something like “Brad Pitt” as for “Isaac Newton.” Does anyone know of any way to get this page view information? I would be very grateful, and do let me know if you need more information from me.
Thank you,
Marianne
(Cornell Phd Student in Information Science)
Hi all,
Forwarding this along in case of interest, hope everyone is well.
The WikiCred initiative is offering microgrants ranging between from $250
to $10,000 to individuals and teams for pilot projects on how to support
credibility on the internet using Wikimedia and lessons from the Wikimedia
community. We are open to teams with proven records of working in the open
knowledge movement as well as newcomers with new and fresh ideas.
Researchers, Wikimedians, credibility enthusiasts and members of the open
knowledge community can get involved in the credibility movement by
applying for a grant and prototyping their software and research ideas with
the help of the community. Applications are accepted on a rolling basis.
The first deadline to receive funding is April 6th.
https://www.wikicred.org/
--
connie moon sehat
connieimdialog(a)gmail.com
https://linkedin.com/in/connieatwork
PGP Key ID: 0x95DFB60E
Hi all,
The next Research Showcase will be live-streamed on Wednesday, March 18, at
9:30 AM PDT/16:30 UTC. We’ll have a presentation on topic modeling by
Jordan Boyd-Graber. A question-and-answer session will follow.
YouTube stream: https://www.youtube.com/watch?v=fiD9QTHNVVM
As usual, you can join the conversation on IRC at #wikimedia-research. You
can also watch our past research showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
This month's presentation:
Big Data Analysis with Topic Models: Evaluation, Interaction, and
Multilingual Extensions
By: Jordan Boyd-Graber, University of Maryland
A common information need is to understand large, unstructured datasets:
millions of e-mails during e-discovery, a decade worth of science
correspondence, or a day's tweets. In the last decade, topic models have
become a common tool for navigating such datasets even across languages.
This talk investigates the foundational research that allows successful
tools for these data exploration tasks: how to know when you have an
effective model of the dataset; how to correct bad models; how to measure
topic model effectiveness; and how to detect framing and spin using these
techniques. After introducing topic models, I argue why traditional
measures of topic model quality---borrowed from machine learning---are
inconsistent with how topic models are actually used. In response, I
describe interactive topic modeling, a technique that enables users to
impart their insights and preferences to models in a principled,
interactive way. I will then address measuring topic model effectiveness in
real-world tasks.
Overview of topic models:
https://mimno.infosci.cornell.edu/papers/2017_fntir_tm_applications.pdf
Topic model evaluation: http://umiacs.umd.edu/~jbg//docs/nips2009-rtl.pdf
Interactive topic modeling:
http://umiacs.umd.edu/~jbg//docs/2014_mlj_itm.pdf
Topic Models for Categorization:
http://users.umiacs.umd.edu/~jbg//docs/2016_acl_doclabel.pdf
--
Janna Layton (she, her)
Administrative Assistant - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>