Master's degree, Computer Software Engineering.
Bachelor of Engineering, Automation Engineer Technology/Technician.
Things I work with:
Mariya Dimitrova, Viktor E Senderov, Teodor Georgiev, Georgi Zhelezov, Lyubomir Penev
https://doi.org/10.3897/BDJ.9.e67671
OpenBiodiv is a biodiversity knowledge graph containing a synthetic linked open dataset, OpenBiodiv-LOD, which combines knowledge extracted from academic literature with the taxonomic backbone used by the Global Biodiversity Information Facility. The linked open data is modelled according to the OpenBiodiv-O ontology integrating semantic resource types from recognised biodiversity and publishing ontologies with OpenBiodiv-O resource types, introduced to capture the semantics of resources not modelled before.
Mariya Dimitrova, Jorrit Poelen, Georgi Zhelezov, Teodor Georgiev, Donat Agosti, Lyubomir Penev
https://doi.org/10.3897/biss.4.59036
Scholarly literature is the primary source for biodiversity knowledge based on observations, field work, analysis and taxonomic classification. Publishing such literature in semantically enhanced formats (e.g., through Extensible Markup Language (XML) tagging) helps to make this knowledge easily accessible and available to humans and actionable by computers. A recent collaboration between Pensoft Publishers and Global Biotic Interactions (GloBI) (Poelen et al. 2014) demonstrates how semantically published literature can be used to extract species interactions from tables published in the article narratives.
Streamlined Conversion of Omics Metadata into Manuscript Facilitates Publishing and Reuse of Omics Data
Mariya Dimitrova, RaΓ―ssa Meyer, Pier Luigi Buttigieg, Teodor Georgiev, Georgi Zhelezov, Seyhan Demirov, Vincent S. Smith, Lyubomir Penev
https://doi.org/10.3897/biss.4.59041
Data papers have started to gain popularity as a publishing format that allows easy and quick publishing of research data (Chavan and Penev 2011, Penev et al. 2017). They describe single or multiple datasets and the methodologies required for their generation. Similar to traditional research articles, data papers and the underlying datasets are peer-reviewed. In this poster, we demonstrate how data papers can be used to incentivise researchers producing omics datasets to increase the quality of the metadata descriptors and the data itself through the journal authoring, peer review and publication process, thus improving data visibility, discoverability, sharing and reuse.
Mariya Dimitrova, Georgi Zhelezov, Teodor Georgiev, Lyubomir Penev
https://doi.org/10.3897/biss.4.59042
Digitisation of biodiversity knowledge from collections, scholarly literature and various research documents is an ongoing mission of the Biodiversity Information Standards (TDWG) community. Organisations such as the Biodiversity Heritage Library make historical biodiversity literature openly available and develop tools to allow biodiversity data reuse and interoperability. For instance, Plazi transforms free text into machine-readable formats and extracts collection data and feeds it into the Global Biodiversity Information Facility (GBIF) and other aggregators. All of these digitisation workflows require a lot of effort to develop and implement in practice. In essence, what these digitisation activities entail are the mapping of free text to concepts from recognised vocabularies or ontologies in order to make the content understandable to computers.
OpenBiodiv: Linking Type Materials, Institutions, Locations and Taxonomic Names Extracted From Scholarly Literature
Mariya Dimitrova, Viktor Senderov, Teodor Georgiev, Georgi Zhelezov, Lyubomir Penev
https://doi.org/10.3897/biss.3.35089
OpenBiodiv is a knowledge management system containing biodiversity knowledge extracted from scholarly literature: both recently published articles in Pensoft's journals and legacy (taxon treatments extracted by Plazi) (Senderov et al. 2017). OpenBiodiv advances our understanding of the use of scientific names, collection codes and institutions within published literature by using semantic technologies, such as the conversion of XML-encoded text to RDF triples, linked via the OpenBiodiv-O onthology (Senderov et al. 2018). In this poster, we show how OpenBiodiv, currently containing more than 729 million statements, can be used to address a specific use case: finding institutions storing type material specimens of the genus Prosopistoma from various literature sources (Fig. 1). This use case is important for various groups of users: institutions, taxonomists, and curators. Answering this complex question is made possible through the application of semantic technologies within OpenBiodiv.