An abundance of scholarly resources are available to the researcher, easily discoverable through use of a few search terms. However, this opulence comes at a price: there is too much literature for a researcher to find and read themselves.
Text and Data Mining (TDM) offer a solution for health researchers wishing to analyse a large corpus of resources, including research papers, medical records, and other material, even when the information is held in an unstructured form. The resultant output may be used to identify hidden patterns that emerge over time and across geographic regions, predict and address gaps within the data, and convert content into a form better suited to modern research. Read more
The International Open Access Week is held annually to celebrate and further promote the principles of the open access movement. Local events and online activities are organized by a variety of organizations, including universities, publishers and societies. This year’s theme is “Open in order to…”, which asks us to…
The Library & Archives Service will be holding a training event for staff wishing to better understand LSHTM processes for setting up a research grant and how they can deal with project management issues. This event will be held on Monday Feb 13, at 2-5pm in the Mary Seacole room at Tavistock Place and is open to all LSHTM staff. Read more
The LSHTM Research Data Management Service are organising a series of events with our counterparts at SOAS and Birkbeck to celebrate research data in its various forms. Join us during 16-20th January 2017 for the following events.
Location: Manson theatre, LSHTM building, Keppel Street
Date: 17th January, 12.30-2pm
The LSHTM Research Data Management Service will be hosting a lunchtime seminar on January 17th to discuss the use of mobile devices to perform data collection in the field. Three case studies will be presented, each covering a data collection tool used in a specific research study. Speakers will discuss the benefits and limitations of each tool and provide recommendations for how they may be applied in your own work.
Data sharing can help you to increase the impact of your research. Studies by Piwowar, Day and Fridsma (2007) and Piwowar and Vision (2013) have found that journal articles with accompanying data receive more citations in comparison to those with no accompanying data, and that data is often used in new research, leading to the original creators being cited in data reuse papers. In this blog post I’ll discuss how you can publish resources - data, processing scripts, code and other material – with journals and digital repositories, and consider new opportunities offered by data journals.