IFLA WLIC Preconference Satellite Meeting
Deutsche Nationalbibliothek – German National Library, Frankfurt, Germany
22 & 23 August 2019
https://2019.ifla.org/cfp-calls/big-data-sig
Data intelligence in libraries: the actual and artificial perspectives
There is a growing urgency for library professionals to explore the underlying considerations for administering scholarly, scientific and business data in libraries. From an actual or real-world perspective, library managers have a requirement for timely and insightful management information derived from library data generated by the use of online resources and library services. Library professionals need to continuously develop their data skills to enable themselves to be smarter in the use, wrangling, visualization and application of data.
Likewise, from an artificial perspective, machine agents are dependent on good quality data to be capable to infer and learn from it through a process of knowledge engineering. Libraries should leverage opportunities to implement interventions that could facilitate optimal access to reputable scientific data, thereby fostering the knowledge process by making data findable and available to information agents.
We are seeking proposals for papers on topics including but not limited to the following:
For the full call for papers with submission guidelines and important dates, please visit https://2019.ifla.org/cfp-calls/big-data-sig.
Deutsche Nationalbibliothek – German National Library, Frankfurt, Germany
22 & 23 August 2019
https://2019.ifla.org/cfp-calls/big-data-sig
Data intelligence in libraries: the actual and artificial perspectives
There is a growing urgency for library professionals to explore the underlying considerations for administering scholarly, scientific and business data in libraries. From an actual or real-world perspective, library managers have a requirement for timely and insightful management information derived from library data generated by the use of online resources and library services. Library professionals need to continuously develop their data skills to enable themselves to be smarter in the use, wrangling, visualization and application of data.
Likewise, from an artificial perspective, machine agents are dependent on good quality data to be capable to infer and learn from it through a process of knowledge engineering. Libraries should leverage opportunities to implement interventions that could facilitate optimal access to reputable scientific data, thereby fostering the knowledge process by making data findable and available to information agents.
We are seeking proposals for papers on topics including but not limited to the following:
- Collection and analysis of library operations data (facilities usage, IoT devices, building sensors)
- Programs which provide access to big data in science projects or government databases
- Projects that mine the long tail of scholarly data
- Collections as data projects, such as curated heritage and special collections
- Data literacy programs and/or data science training initiatives
- The professional issues around data science and data librarianship
- Infrastructure, frameworks, and applications on which data gathering, cleaning, analysis and visualization can be done
For the full call for papers with submission guidelines and important dates, please visit https://2019.ifla.org/cfp-calls/big-data-sig.
