Sheeba Samuel

Researcher/PhD Candidate

Ernst-Abbe-Platz 2

Room: 3211

E:

ORCID: 0000-0002-7981-8504

Curriculum Vitae

Past Positions:

Member of Technical Staff II – Aruba, a Hewlett Packard Enterprise Company (July 2013-December 2015)

Graduate Technical Intern – Aruba, a Hewlett Packard Enterprise Company (January 2013-June 2013)

Education:

Master of Technology (M Tech), Information Technology, International Institute of Information Technology, Bangalore, India (2011-2013)

Bachelor of Technology (B Tech), Computer Science and Engineering, Cochin University of Science and Technology (CUSAT), India

Awards

  • ProChance 2017 Grant, Friedrich Schiller University Jena
    Promotion of the scientific interaction of young female researchers.

Work

More Information about my work is available here

Professional Activities

Co-organizer of the workshop “Fostering reproducible science – What data management tools can do and should do for you“, 2017, Germany.

Research Area

My research area includes:

  • Scientific Data Management and processing
  • Reproducibility of Scientific Experiments
  • Semantic Web
  • Data provenance

Publications

2018

The Story of an Experiment:A Provenance-based Semantic Approach towards Research Reproducibility
Sheeba Samuel, Kathrin Groeneveld, Frank Taubert, Daniel Walther, Tom Kache, Teresa Langenstück, Birgitta König-Ries, H. Martin Bücker and Christoph Biskup
11th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4HCLS 2018)
Antwerp, Belgium 5.12.2018
ProvBook: Provenance-based Semantic Enrichment of Interactive Notebooks for Reproducibility
Sheeba Samuel and Birgitta König-Ries
The 17th International Semantic Web Conference (ISWC) Demo Track 2018
Monterey, California, USA 10.10.2018
Combining P-Plan and the REPRODUCE-ME Ontology to Achieve Semantic Enrichment of Scientific Experiments using Interactive Notebooks
Sheeba Samuel and Birgitta König-Ries
15th Extended Semantic Web Conference (ESWC) Posters & Demo 2018
Crete, Greece 6.6.2018

2017

Integrative Data Management for Reproducibility of Microscopy Experiments
Sheeba Samuel
14th Extended Semantic Web Conference (ESWC) 2017
Portoroz, Slovenia 28.5.2017
REPRODUCE-ME: Ontology-based Data Access for Reproducibility of Microscopy Experiments
Sheeba Samuel, Birgitta König-Ries
14th Extended Semantic Web Conference (ESWC) 2017
Portoroz, Slovenia 28.5.2017

2016

Towards Reproducibility of Microscopy Experiments
Sheeba Samuel, Frank Taubert, Daniel Walther, Birgitta König-Ries and H. Martin Bücker
First International Workshop on Reproducible Open Science, 2016 co-located with TPDL
Hannover, Germany 9.9.2016

Talks

2018

The Story of an Experiment: A Provenance-based Semantic Approach towards Research Reproducibility
11th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4HCLS 2018)
Antwerp, Belgium 4.12.2018
Provenance-based Semantic Approach for the Reproducibility of Scientific Experiments
ICEI2018 - The 10th International Conference on Ecological Informatics
Jena, Germany 27.9.2018

2017

Integrative Data Management for Reproducibility of Microscopy Experiments
14th Extended Semantic Web Conference (ESWC) 2017 PhD Symposium
Portoroz, Slovenia 29.5.2017

2016

Towards Reproducibility of Microscopy Experiments
First International Workshop on Reproducible Open Science (RepScience 2016)
Hannover, Germany 9.9.2016

Teaching

Current Projects

Project Z2 of CRC ReceptorLight: Integrative Data Management and Processing
Project Z2 of CRC ReceptorLight is jointly carried out by the Jena University Hospital and Friedrich Schiller University Jena within the framework of the Collaborative Research Centre (CRC) "High-end light microscopy elucidates membrane receptor function (Receptor Light)" established in 2015. CRC ReceptorLight is funded by the German Research Foundation (DFG) and consists of around 20 research projects from various institutions located in Jena and Würzburg. It will apply and develop light microscopy techniques with highest resolutions in space and time. The volume of the resulting datasets will be large, expected to be in multi-petabyte data. The overall goal of project…
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