Call for papers: ACM Transactions on Data Science

November 19th, 2018

Data Science relies on the massive volumes of diverse data generated from all forms of human activity and interaction with the environment to make decisions and to solve problems. Traditional methods for managing and processing data have been scaled to address its growth, but new approaches are required to deal with these heterogeneous, high velocity, very large data sources of varying quality, coverage, and semantics. There are challenges at every stage. Addressing these challenges requires innovations in a wide range of computing sub-disciplines, from computer architecture to human computer interaction, and from data analytics to recommendations. ACM Transactions on Data Science (TDS) will serve as the premier forum for describing and advancing the state of the art on this important topic.

Scope

The scope of the TDS includes cross-disciplinary innovative research ideas, algorithms, systems, theory and applications for data science. Papers that address challenges at every stage, from acquisition on, through data cleaning, transformation, representation, integration, indexing, modeling, analysis, visualization, and interpretation while retaining privacy, fairness, provenance, transparency, and provision of social benefit, within the context of big data, fall within the scope of the journal.

The objective of the journal is to provide a forum for cross-cutting research results that contribute to data science. Papers that address core technologies without clear evidence that they propose multi/cross-disciplinary technologies and approaches designed for management and processing of large volumes of data, and for data-driven decision making will be out of scope of this journal.

Editor-in-Chief
Beng Chin Ooi, National University of Singapore

Senior Associate Editors
Mike Franklin, University of Chicago
H.V. Jagadish, University of Michigan
Hong Mei, Beijing Institute of Technology and Peking University
Renée J. Miller, University of Toronto
Jeannette M. Wing, Columbia University

For further information or to submit your manuscript.

Digital Humanities Day with DARIAH on 30 October 2018

October 2nd, 2018

Welcome to a Digital Humanities Day with Frank Fischer, Associate Professor for Digital Humanities at the Higher School of Economics, Moscow, and co-director of DARIAH-EU. Frank Fischer will talk about his own research on digital perspectives for the study of European Drama as well as DARIAH:s work for the Pan-European Infrastructure for the Arts and Humanities.

Programme
10.00-11.00 “Masks and Interfaces – Digital Perspectives for the Study of European Drama” * See abstract below.
11.00-13.00 Lunch
13:00-14.00 “A Social Marketplace for Services – Introduction to DARIAH, the Pan-European Infrastructure for the Arts and Humanities”
14.00-14.30 Coffee
14.30-15.30 Discussion

Registration kerstin.broden@lnu.se. Please advise of any food allergies.

Co-organised by the Digital Humanities Initiative and iInstitute

* Abstract: The digital literary studies have offered a lot of new approaches to the study of drama in recent years. New methods like social network analysis, stylometry and other quantitative and statistical approaches are complemented by a rich landscape of literary data in many languages and formats. This talk will recap these developments, oscillating between research and infrastructure, and introduce a platform for the research on European drama.

Seminar – How to get published with IEEE

September 12th, 2018

On September 19 at 10:00-11:30 Linnaeus University will be visited by Paul Henriques from IEEE (Institute of Electrical and Electronics Engineers). Paul will host a seminar on the topic “How to get published with IEEE”:

Increase the visibility of your research and build author credibility by publishing in a leading IEEE journal or conference. Learn how to identify the best journal or conference for your work and navigate the IEEE paper submission and peer review process. Review the required elements and proper structure of a manuscript to avoid reasons why papers may be rejected.

The presentation is in English. The seminar takes place in Växjö (location: Babel at the University Library) but will also be streamed to Kalmar (location: UB296A at the University Library).

Registration and more information:

//Diana

The 6th Swedish Workshop on Data Science (SweDS 2018)

September 10th, 2018

We have been asked to invite you to attend and participate in SweDS2018 (the 6th Swedish Workshop on Data Science).  The workshop takes place at Umeå UniversityNovember 20-21, 2018.  The abstract submission deadline is October 13, 2018 for contributed oral presentations.

Information:
Submissions
Call for abstracts

The Swedish Workshops on Data Science (SweDS) allow members of a community with common interests to meet in the context of a focused and interactive discussion. SweDS 2018, the sixth Swedish Workshop on Data Science, brings together researchers, practitioners, and opinion leaders with interest in data science. The goal is to further establish this important area of research and application in Sweden, foster the exchange of ideas, and to promote collaboration. Read the rest of this entry »

Computational Archival Science Workshop at IEEE Big Data 2018 – Call for papers

September 3rd, 2018

The organizers of the Computational Archival Science (CAS) Workshop at IEEE Big Data 2018 have issued a formal call for papers. This is the 3rd workshop at IEEE Big Data addressing CAS, following on from workshops in 2016 and 2017. All papers accepted for the workshop will be included in the Conference Proceedings published by the IEEE Computer Society Press, made available at the conference, which takes place Dec. 10-13, 2018 in Seattle, WA, USA.

The workshop will explore the conjunction (and its consequences) of emerging methods and technologies around big data with archival practice and new forms of analysis and historical, social, scientific, and cultural research engagement with archives. We aim to identify and evaluate current trends, requirements, and potential in these areas, to examine the new questions that they can provoke, and to help determine possible research agendas for the evolution of computational archival science in the coming years. At the same time, we will address the questions and concerns scholarship is raising about the interpretation of “big data” and the uses to which it is put, in particular appraising the challenges of producing quality (meaning, knowledge and value) from quantity, tracing data and analytic provenance across complex “big data” platforms and knowledge production ecosystems, and addressing data privacy issues.
Important dates:

  • Oct 8, 2018: Due date for full workshop papers submission
  • Oct 29, 2018: Notification of paper acceptance to authors
  • Nov 15, 2018: Camera-ready of accepted papers
  • Dec 10 – 13, 2018: Workshop [exact date TBD]

See the full workshop CFP to learn more, including suggested research topics and submission instructions.

New chance to take the PhD-course in Applied Machine learning 3 credits

August 20th, 2018

We are not offering you a second chance to take the PhD-course in Applied Machine Learning this fall.

Course content:

Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data. This course mixes theory and practice, with a focus on applied machine learning where we learn what algorithms and approaches to apply on different types of data.

The course includes the following:

  • Supervised learning, different types of data and data processing
  • Algorithms for handling text documents
  • Algorithms for handling data with numerical and categorical attributes
  • Neural Networks
  • Deep Learning for image recognition

Timetable

The course will start on Tuesday October 9th and finish by the end of the semester.

Registration

The registration needs to be finalized no later than September 19th 2018

Register here: https://goo.gl/forms/jn1DAAQsb5zm8S1D3

 

If you have any questions please turn to Johan Hagelbäck – johan.hagelback@lnu.se