Liliana Melgar is the data specialist at the SKILLNET project at the History Department of Utrecht University. “The ERC Consolidator project ‘Sharing Knowledge in Learned and Literary Networks – The Republic of Letters as a Pan-European Knowledge Society’ (SKILLNET), under the direction of Dr Dirk van Miert, conducts research into the ideal of sharing knowledge within early modern scholarly networks in Europe by applying social network analysis and text mining techniques to the metadata and full-text data of large quantities of manuscript and printed letters from the period 1500-1800.”
Liliana holds a PhD in Information Science from the Carlos III University in Madrid, in which she investigated scholarly annotations and crowdsourcing for audiovisual content. She has a bachelor in Library studies and a Masters degree in Digital Libraries awarded by Oslo University College, Tallinn University and Parma University. She has actively been involved in facilitating digital humanities research in The Netherlands in the past years. She worked between 2016 and March 2020 as a postdoctoral researcher at the University of Amsterdam and Utrecht University for the CLARIAH project, the Dutch digital infrastructure for the arts and the humanities. Her main research topic was scholarly annotations for audiovisual content, collaborating with the team building the CLARIAH scholarly annotations infrastructure.
At SKILLNET Liliana supports researchers in their data-related tasks, mostly focused on the semi-automatic extraction, harmonization, reconciliation and linking of historical person and place names using prosopographical data sets from the 16th, 17th and 18th centuries. These processes facilitate the two methodological endeavours of the research group, which are to perform: (1) large-scale social network analysis to unravel the social structure of this network and its development over time, and, (2) to analyse, semi automatically, a large corpus of texts to trace changes in the semantics of key ethical concepts across time and space.
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ORCID (publications): https://orcid.org/0000-0003-2003-4200