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KEYNOTE SPEAKERS

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Lucy Montgomery

Curtin University

 
 

Title: Understanding the Impacts of Open Access: Specialist Scholarly Books and their Communities

 

Abstract:

Specialist scholarly books, the key form of publication in the Humanities and some Social Sciences, are often the forgotten younger-siblings of scholarly big data projects. Humanities disciplines are ¡®peer review¡¯ rather than citation-based. Demand for data on how outputs perform ¨C from researchers, institutions and funding agencies ¨C has been lower than in the case of the exact sciences. Like book publishing more generally, large-scale and timely data about distribution and usage of monographs has been hard to collect (or to access) until recently. No single publisher controls more than 5% of the global market. Books have been slower than journals to transition to digital formats. Uniform approaches to DOIs and metadata are taking time to crystallise. Users engage with books in ways that are often difficult to ¡®see¡¯ at scale. Books have a much longer shelf-life than do articles; their impact can be measured in years and sometimes decades.

 

In this talk I present an applied, deep-dive case study of efforts to identify and track the uses of Open Access (OA) specialist scholarly books at global scale, through the lens of the Knowledge Unlatched project. Knowledge Unlatched Research is engaging with the data generated by the larger Knowledge Unlatched OA monograph initiative to help libraries, authors, publishers and research funders to understand what happens to their books once they have been made OA; and to explore what changes (and what doesn¡¯t) when open access licenses are applied to long form publications. I show that rather than being a disadvantage, many of the factors that make data about books difficult to gather at scale are actually strengths. A diverse publishing landscape, a high-proportion of mission driven publishers, and libraries that care deeply about books and the communities that engage with them, are powerful advantages for HSS researchers.

 

Helping communities to tackle challenges of coordination, transparency and trust as they relate to data about scholarly books, rather than simply going after ¡®low hanging fruit¡¯, will be vital to ensuring that big-data innovations help rather than harm peer review disciplines. However, there are signs that this is happening. Because diverse smaller stakeholders hold the data that relates to specialist scholarly books, there are structural incentives for libraries, publishers, research-funders and researchers to work together to make conscious decisions about how data are aggregated, and by whom. Questions arise about whether this is best tackled within commercial or public spaces, in light of what is now known about the value of being able to look across datasets to tell rich stories about engagement and impact; as well as the dangers of oversimplification of research metrics and the commercialisation of data resources. It may yet turn out that being the forgotten younger sibling will allow a viable alternative system to emerge.

 

Bio:

Associate Professor Lucy Montgomery ¨C is Director of the Centre for Culture and Technology (CCAT) at Curtin University. She is also Research Director for Knowledge Unlatched, a not-for-profit start-up developing a new approach to funding open access book publishing. Her current research investigates the ways in which knowledge-creating groups, institutions and technologies are being transformed by the internet and digital technologies and, in this context, the role of intellectual property rights in the growth of the creative economy. In a practical application of this work, she was part of the team that founded Knowledge Unlatched in 2012, in order to harness the power of global coordination and Open Access to reshape research communication.

 

 

 

Jianxin Li

University of Western Australia

 
 

Title: Influence Maximization in Social Media Data Analytics

 

Abstract:

Social media has become a new and main platform for organizations to broadcast their policies, for companies to advertise their products, and for people to propagate their opinions. Therefore, social media data analytics has become a timely and significant research topic in recent years. In this talk, Dr. Li will first go through the social media background and the data representation of social media data. And then, he will briefly discuss the main stream research in social data mining and social computing. After that, Dr. Li will mainly introduce how the two most popular influence models are defined in social computing, what the influence maximization problem is defined, how its variants are defined. Finally, Dr. Li will introduce his currenent social media research project and discuss the interesting collaboration with attendees.

 

This one-hour keynote targets researchers, designers and practitioners interested in social computing, social media data analytics, big data management systems and processing. While the audience with a good background in these areas would benefit most from this keynote, we believe the material to be presented would give general audience and newcomers an introductory pointer to the current work and important research topics in this field of viral marketing and social influence maximization, and inspire them to learn more. Only preliminary knowledge about graph, data mining, algorithms and their applications are needed.

 

Bio:
Jianxin Li is currently working as a Senior Lecturer in the School of Computer Science & Software Engineering, the University of Western Australia. He obtained his PhD degree by Swinburne University of Technology in 2009. After that, he worked as a Research Fellow in Swinburne in 2009-2014 and as a Lecturer/Early Career Development Fellow in RMIT in 2015. Jianxin's research interests include social computing, graph database management system, query processing and optimization, big data processing, and transport data analytics. His social computing research has been granted one ARC Discovery Project in 2016. He is an active researcher in database and data mining communities. He has published 37 high quality research papers in top international conferences and journals including IEEE ICDE 2011,2014, 2016, ICDM 2016, EDBT 2010, 2012, CIKM 2016, IEEE TKDE 2014, 2015, 2016. Jianxin is active in PC member, reviewer and co-organizer in many conferences such as SIGMOD 2017, PVLDB 2015, ACSW 2017, and ADC 2015; and was co-local Chair/publicityChair/proceeding Chair of ADC 2015; Proceeding Chair of ADMA 2016; and is co-Tutorial Chair of WWW 2017. His homepage is at https://sites.google.com/site/jianxinliit/.

 

 

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