ASIST2018 Workshop: Call for Papers and Presentations
Big Metadata Analytics: Setting an Agenda for Data-Intensive Future (BMA2018)
Hyatt Regency Vancouver, Vancouver, Canada, November 14, 2018
Big metadata exists in bibliographic, indexing, and research data repositories and is an important part of the cyberinfrastructure supporting information and data management, discovery, sharing, and reuse. Its other role – as a data source for data/text mining and knowledge discovery – is less visible compared to the one for management, discovery, sharing, and reuse of information and data. Research in big metadata analytics has been dynamic and encompasses a wide range of topics, methods, and applications that have been labeled as bibliometrics, citation analysis, scientometrics, and informetrics. New family members of big metadata such as Linked Data are also gaining momentum.
As big metadata is pivotal for the data-intensive research, learning, health, and business, there has been a lack of discussion on what big metadata analytics encompasses, what theoretical, methodological, and computational issues need to be addressed, and how it might be applied to support decision making at team, organizational, and even national levels. Although using bibliographic metadata as the data source in research has a long history, using big metadata in data repositories is still a new area waiting to be explored. The purpose of this workshop is to bring current researchers who have used or are using big metadata in their projects to share their challenges, methods, datasets, and findings, through which we hope to produce a research agenda for a new research area – big metadata analytics.
SUBMISSION GUIDELINES
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Full papers: should be completed research on one or more of the topics listed below. A full paper should be no more than 10 pages, including figures, tables, and references.
- Presentation abstracts: may be used to report an ongoing research project with a focus on any of the topics listed below, with approximately 500 words.
The format for both papers and presentation abstracts should follow the template specified at the ASIST2018 website: AM18 Proposal Template (https://www.asist.org/am18/wp-content/uploads/2018/01/Proposal-Template.docx). All papers and abstracts should be submitted to: https://easychair.org/conferences/?conf=bma2018. If you do not have an account with EasyChair, you will need to register first to be able to submit your paper/presentation abstract.
All submissions will be reviewed by the program committee. Full papers accepted for the workshop will be invited to contribute extended versions to a special issue, known as a Research Topic (RT), in Frontiers in Research Metrics and Analytics. (https://www.frontiersin.org/journals/research-metrics-and-analytics).
We are soliciting papers and presentation abstracts on the following topics (but not limited to):
- Theories and models:
- Complex network models
- Classic bibliometric models
- Theories in big metadata analytics and/or from adjacent fields of studies, e.g., SciTech Human Capital theory
- Methodologies and metrics
- Data processing, transformation, integration
- Workflows in big metadata analytics
- Predictive and evaluative metrics
- Traditional methods applied to big metadata (e.g. how statistics might be used)
- Application of big metadata analytics in subject/disciplinary domains
- Research impact assessment
- Use in other social sciences (e.g. communication or sociology)
- Linked Data as a type of big metadata
The workshop website is located at http://metadataetc.org/BMA2018/bma2018.html. Information about the workshop program will be updated as it becomes available.
IMPORTANT DATES:
- July 30 August 10: Deadline for submitting papers and presentation abstracts
- August 30 September 10: Notification to authors
- September 30 October 15: Final papers and abstract submission
- November 14: Workshop date
ORGANIZING AND PROGRAM COMMITTEE:
Jian Qin, Syracuse University, jqin@syr.edu
Chaomei Chen, Drexel University, chaomei.chen@drexel.edu
Jane Greenberg, Drexel University, jg3243@drexel.edu
Jeff Hemsley, Syracuse University, jjhemsle@syr.edu
Dietmar Wolfram, University of Wisconsin at Milwaukee, dwolfram@uwm.edu