Workshop on Data meets Applied Ontologies

Call for demos | Organization | Agenda

The Data meets Applied Ontologies (DAO) workshop will take place at the third edition of the Joint Ontology Workshops (JOWO) in which a series of different workshops meets for three days in the South Tyrollean alps to discuss innovative, applied and state of the art research.

Call for demos

Call for Demos: Workshop on Data meets Applied Ontologies (DAO@JOWO2017)

The DAO workshop will be a track of the 3rd edition of the Joint Ontology Workshops (JOWO),
which will be held in Bozen-Bolzano, Italy, on September 21-23th, 2017.
http://iaoa.org/jowo/JOWO-2017/ 

The goal of the DAO workshop is to provide opportunities for participants from academia and industry to present their latest developments in ontology-mediated data integration and analysis techniques, and data-driven industrial applications. The workshop will be a great opportunity to synthesize new insights, and disseminate knowledge across field boundaries to promote the interaction between these two different communities.

A demo proposal should provide:
– the motivation for the software/prototype;
– the design behind the software/prototype;
– the main functionalities;
– the significance of the software/prototype from a research and/or industrial perspectives.

Important Dates

July 31, 2017: (Extended) Deadline for demo submissions
September 1, 2017: Demo notifications
September 15, 2017: Camera-ready copy
September 21-23, 2017: Date of workshop

Submission Guidelines

The demonstration submissions must be up to 4 pages in IOS press format and follow these guidelines:

– Pages 1-2 to describe the system to be demonstrated. More precisely, the authors are encouraged to discuss the application domain, the problem scenario, the technology used, the data analysis, data integration techniques involved, the innovations of the system, and its live and interactive aspects, etc.
– Page 3 to list the bibliographic references (if needed).
– Page 4 to provide the organizers with a list of requirements for the demo setting at the workshop.

All submissions are made through the JOWO 2017 Easychair, selecting the Data meets Applied Ontologies (DAO) track.

https://easychair.org/conferences/?conf=jowo2017

Demos of accepted demo descriptions will be presented at the workshop and their descriptions will be published in the JOWO proceedings (WS-CEUR proceedings).

Submission of a demo description should be regarded as an agreement that, should the demo descriptions be accepted, at least one of the authors will attend the workshop to present the work.

Organization

Organizing committee

Roberto Confalonieri, Smart Data Factory, Free University of Bozen-Bolzano, Italy
Andrea Janes, Smart Data Factory, Free University of Bozen-Bolzano, Italy
Diego Calvanese, Smart Data Factory, Free University of Bozen-Bolzano, Italy

Agenda

The workshop will take place on Friday, 22 September, from 11 to 15:30, in two two sessions, before and after the lunch break.

The tentative program is the following:

  • 11:15-11:30: Welcome
  • 11:30-11:50: Using Very Large Scale Ontologies for Natural Language Generation (NLG) (paper)
  • 11:50-12:10: The OBDA-based “Observatory of Research and Innovation” of the Tuscany Region (paper)
  • 12:10-12:30: The Mastro Protégé Plug-in for OBDA (paper)
  • 12:30-14:15: Lunch break
  • 14:30-14:50: OntoGui: a Graphical User Interface for rapid instantiation of OWL Ontology (paper)
  • 14:50-15:10: Semantic GIOVE-VF: an ontology-based Virtual Factory Tool (paper)
  • 15:15: End

Our invited speaker is Alessandro Mosca from SIRIS Lab, Barcelona. He will give a keynote with title “Ontology-mediated Data Integration and Access in Research and Innovation Policy Making” on Saturday morning.

You can find additional information about the venue  and the overall program of JOWO here.

See you in Bozen-Bolzano!

1st Workshop on Technology Transfer in Software Engineering and Formal Methods (POTENTIAL)

Call for papers | Organization | Agenda

Our era is undergoing profound and unexpected changes in the economic and social level. On the one hand, we talk about “knowledge society”, pointing out that the knowledge and domain expertise, know-how and human competencies are increasingly becoming the key to the growth of the economy and, more generally, of society. On the other hand, we talk about “digital society”, underlining the fact that virtually every complex human activity employs, directly or indirectly, infrastructure and IT services. An important consequence of this is that a huge amount of data, digitally available, is routinely generated and stored in the most disparate fields of application.

These “big data” implicitly provide the picture of the complex reality on which decisions are based. Of course, an individual cannot administer such a large amount of data, while modern computer systems can manage and analyze large amounts of data. On the other hand, these same actors, at present, are not able to take advantage of the complex knowledge, experience, and insight of the domain experts who are at the heart of decision-making. One, therefore, needs to face the dichotomy between human decisions based on knowledge but not data, and automatic and efficient analysis of data, but often irrelevant for decision-making.

Technology transfer aims to overcome the dichotomy highlighted above, enabling the public and private sectors to benefit concretely from the advanced skills developed by researchers to solve the complex problems of intelligent data management that are faced in the industry.

Unfortunately, technology transfer is not easy to accomplish: the various actors not only speak different “languages”, but also have different goals, and different ways to work. Formal methods, as well as software engineering research, have particular fields in which industry applies the identified results with ease, but in many cases processes that accompany innovation, namely Open Innovation, are needed. Moreover, many companies, especially small and medium enterprises, need further support to adopt the research results developed in academia.

Promoting a close cooperation among the actors involved, technology transfer activities also aim to foster the co-design and co-development (including the design and participatory development) of IT applications focused on the intelligent use of the data, whose innovativeness and complexity does not allow the independent realization by the various actors.

To this end, in this workshop, we intend to provide a shared panel that discusses technology transfer activities, to create an ecosystem of research and industrial partners to support the entire life-cycle of technology transfer.

Both field of Formal Methods and Software Engineering can benefit from a discussion of how to alleviate the obstacles between efficient and effective technology transfer activities between the various actors in the marketplace and in the research landscape.

Call for papers

The 1st workshoP On Technology transfEr iN sofTware engIneering And formaL methods (POTENTIAL) will be held in Trento, Italy, on September 4th, 2017. The workshop is co-located with SEFM 2017.

Motivation

Our era is undergoing profound and unexpected changes in the economic and social level: we talk about “knowledge society”, pointing out that the knowledge and domain expertise, know-how, and human competencies are increasingly becoming the key to the growth of the economy and, more generally, of society. Furthermore, we talk about “digital society”, underlining the fact that, virtually, every complex human activity employs, directly or indirectly, infrastructure and services based on big data.

Data implicitly provide the picture of the complex reality on which decisions are based. Unfortunately, an individual cannot administer the large amount of data needed, and at present, is not able to take advantage of the complex knowledge, experience, and insight of the domain experts who are at the heart of decision-making. One, therefore, faces the dichotomy between human decisions based on knowledge but not data, and automatic, efficient data analysis techniques, but often irrelevant for decision-making.

Technology transfer of formal methods and software engineering can overcome the dichotomy highlighted above, and, in this workshop, we discuss technology transfer activities in the form of case studies, experience reports, failure and success stories, studies about the needs of the industry and research institutions to engage in productive technology transfer activities.

Objectives:

– Brainstorm and evaluate existing technology transfer activities
– Identify strengths, weaknesses, opportunities, and threats of technology transfer activities
– Develop best practices and a research agenda of how to overcome technology transfer obstacles.

Intended Audience

Researchers, practitioners, tool developers and users, and technology transfer experts are welcome.

Topics of interest include (but not limited to)

– Case studies
– Best practices and experience reports
– Failure and success stories
– Studies about the needs of the industry and research institutions to engage in productive technology transfer activities
– Open Innovation
– Tool integration
– Technology-enhanced educational systems
– Interactive systems
– Artificial intelligence systems

Important Dates

Paper submission: 16 June 2017 (Extended) July 31, 2017
Author notification: 07 July 2017 (Extended) August 4, 2017
Post-proceedings camera-ready version: 28 July 2017 (Extended) August 13, 2017
Workshop date: September 4th, 2017

Submission

We seek for both full and short papers. Full papers will be formatted using the  Springer LNCS proceedings format with a page limit of 15 pages. Short paper should  be limited to 8 pages. All accepted papers will be published in a joint LNCS

proceedings volume for SEFM co-located events.

Organization

Program chairs

Andrea Janes, Free University of Bozen-Bolzano, Bolzano, Italy
Roberto Confalonieri, Free University of Bozen-Bolzano, Bolzano, Italy

Program Committee

Barbara Russo, Free University of Bozen-Bolzano
Diego Calvanese, Free University of Bozen-Bolzano
Juan Antonio Rodriguez, Artificial Intelligence Research Institute (IIIA-CSIC)
Lissette Lemus, Artificial Intelligence Research Institute (IIIA-CSIC)
Matthew Yee-King, Goldsmiths College, University of London
Pablo Almajano, Narada Robotics S.L. and University of Barcelona
Patrick Ohnewein, IDM Südtirol
Peter Hopfgartner, Free University of Bozen-Bolzano
Tarek R. Besold, Digital Media Lab, TZI, University of Bremen
Wang Xiaofeng, Free University of Bozen-Bolzano

Agenda

TBA