describing this presentation is included in this volume.
have been proposed to measure metadata and data quality, in most cases they are highly subjective and/or domain speci c. Moreover, they are directly related to the intended use of the data, meaning that a dataset could be of high quality for one use and of low quality for another. In all cases, (meta)data quality has a tremendous impact on data science related tasks and ultimately in everyday life.
The (meta)-data quality workshop aimed at exploring the various quality issues found in people working with both data and metadata across domains. Hence its objectives was to (a) share and exchange experiences regarding (meta)data quality, (b) identify patterns in (meta)data quality, (c) share methodologies and metrics that will help to measure (meta)data quality and (d) share and propose tools that can be used e ectively in improving automatically (meta)data quality.
The workshop received a total of 5 full paper and 2 poster/demo submissions, of which 4 full papers and 1 demo were presented after being reviewed by 3 members of the program committee. The workshop also featured an invited keynote presentation by Prof. Peter Doorn and Mrs Eleftheria Tsoupra entitled \A Simple Approach to Assessing the FAIRness of Data in Trusted Digital Repositories". An extended abstract describing this presentation is included in this volume.
Arti cial Intelligence struggles to enrich machines with human-like features, therefore accessing meaning and sharing it with computers is one of the main challenges that the computational linguistics domain faces nowadays. While still far from completely decoding hidden messages in political speeches, computer scientists, language engineers and linguists have joined e orts in making the language more machine-understandable. In order to teach computers to understand and predict human behavior, language models need to be speci ed and created from human knowledge. Building machine-readable knowledge bases takes a huge amount of time and resources, both nancial and human (trained experts). Since today we found ourselves in an era in which software learns from its users and all of the users are connected, this workshop intends to discuss natural language processing applications which explore the web (with a special emphasis on the social web) in new and innovative ways, in order to extract the wisdom of crowds captured within. With such knowledge extraction applications, dynamically created for di erent user types, contexts or time frames, a gap will be lled between where we are now and where we could be in arti cial intelligence: an era when computers are engaged in intellectual cooperation (with humans, or even more futuristic, with each other) in order to foster creativity, innovation and inventiveness. The speci c aim of FUTURITY-2017 is to establish a consolidated community of internationally appreciated language technology practitioners from di erent backgrounds, with interests in real-life applications, bridging the gap between research and innovation in order to make sense of crowdsourced knowledge and foreseen future societal challenges. Taking advantage of this huge knowledge repository, and the new search and extraction methods, the scienti c program of FUTURITY-2017 invites papers focusing on the following (and related) topics: { Modeling search to extract knowledge from social web; { Collaborative and interactive search; { Conversational search interaction; { Community behavioral analysis; { Intelligent personal assistants; { Semantic search; { Extracting and mining forum data { Social media and linked data methodologies in real-life scenarios { Collaborative tools and services for citizens, organizations, communities; { Diversity and aggregated search { Creating and using structured social media-based resources through social web mining; { Exploring crowdsourcing and user communities; { Strategic early warning systems and detection of week signals; { Using the social web to foster innovation; { Exploring the digital cultural heritage; { Interaction with the web as a mental, social and physical extension of people.
For the FUTURITY-2017 workshop, we received 8 submissions through the Easychair submission platform, out of which 5 were accepted for presentation at the workshop and publication in this proceedings. Each of the submitted papers was thoroughly reviewed by two Program Committee members, experts in the topics of the workshop. All papers emphasize innovative approaches addressing the following topics: { Reviewers Classi cation in an Online Community of Romanian Tourists by
Mihaela Colhon, Costin Badica { Developing a Technology Allowing (Semi-) automatic Interpretative Transcription by Daniela G^fu, Mihaela Onofrei { Neutrosophy, Method of Uncertainties Process Analysis by Florentin Smarandache, Mirela Teodorescu { How can we reconstruct stories based on memories? by Andreea Macovei,
Diana Trandabat { Assistive technology in stock market decision making by Radu A. Ciora,
Carmen M. Simion and Marius Cioca.
TDDL workshop was supported by the European Unions Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement No 713567 and by the ADAPT Centre for Digital Content Technology, which is funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. FUTURITY workshop was supported by a grant of the Romanian National Authority for Scienti c Research and Innovation, CNCS/CCCDI UEFISCDI, project number PN-III-P2-2.1-BG-2016-0390, contract 126BG/2016, within PNCDI III funding program.
Many people contributed to the success of this event, and we express our sincere thanks to all of them. The program committee, made up of international experts in the area of information retrieval, natural language processing, social media and linked data, spent time carefully reviewing all the proposals submitted to TDDL, MDQual, and FUTURITY 2017 to insure a qualitative improvement of the papers. The members of the Organizing Committee have enthusiastically assured the settings were appropriate for scienti c networking. See you next edition!
Nattiya Kanhabua
Pierpaolo Basile Seamus Lawless
Dimitris Gavrilis Christos Papatheodorou
Daniela G^fu Diana Trandabat Commitees
Wolfgang Nejdl Kjetil N rvag Thomas Risse Rachele Sprugnoli
School of Computer Science and Technology, University of Bedfordshire University of Illinois, Urbana-Champaign SUNY @ Albany and MIT Clinical Decision Making group Kyoto University L3S Research Center, Hannover Norwegian University of Science and Technology L3S Research Center, Hannover Digital Humanities at Fondazione Bruno Kessler (FBK) (Meta)-Data Quality
Amir Aryani Australian National Data Service, Australia Donatella Castelli CNR, Italy Valentine Charles Europeana Foundation, The Netherlands Peter Doorn Data Archiving and Networked Services, The Netherlands Pythagoras Karampiperis Agroknow, Greece Laurent Romary French Institute for Research in Computer Science and
Automation, France Timos Sellis Swinburne University of Technology, Australia Giannis Tsakonas University of Patras, Greece Michalis Sfakakis Ionian University, Greece