PCP on Web: Professorial Career Patterns of the Early Modern History

Development of a scientific method for research on online available and distributed research databases of academic history.

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Summary

The Leipzig University of Applied Science (HTWK Leipzig) with the research group Agile Knowledge Engineering and Semantic Web (AKSW) and the Herzog August Library in Wolfenbüttel (HAB) run the research project, in cooperation with partners from the Working Group of German Professor catalogs and the European research network for academic history - Héloïse. The project uses independent online databases for research in the field of prosopography, which is the study and evaluation of collected information on groups of historical persons. This project focuses on German professors' career patterns during the 18th and 19th centuries. The proposed research employs databases that have previously been produced by both project partners, namely the Catalogus Professorum Lipsiensium and the Professorum Helmstadiensium. This proposed project will develop a new research method that combines well-known research methods from the humanities and computer science. In preliminary work AKSW proposed the Heloise Common Research Model (HCRM) for cross-project research in the field of university history, within the European research network Heloise. HCRM is conceived as a layered architecture, framing the research within the following abstract layers: the Repository Layer, the Application Layer and the Research Interface Layer. As part of the proposed research project a method will be developed based on HCRM and be evaluated by studying the research question.

About PCP on Web

PCP on Web is a project within the field of Digital Humanities founded by the German Research Foundation (DFG) and started on March 1st, 2017. The consortium consists of HTWK Leipzig (coordinator, Germany) and Herzog August Bibliothek in Wolfenbüttel (Germany).

  • Duration: 03/2017–02/2020
  • Funding Programme: DFG - German Research Foundation

Publications

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News

SANSA 0.7.1 (Semantic Analytics Stack) Released ( 2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann)

2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann

We are happy to announce SANSA 0.7.1 – the seventh release of the Scalable Semantic Analytics Stack. SANSA employs distributed computing via Apache Spark and Flink in order to allow scalable machine learning, inference and querying capabilities for large knowledge graphs. Read more about "SANSA 0.7.1 (Semantic Analytics Stack) Released"

More Complete Resultset Retrieval from Large Heterogeneous RDF Sources ( 2019-12-05T15:46:09+01:00 Andre Valdestilhas)

2019-12-05T15:46:09+01:00 Andre Valdestilhas

Over recent years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laundromat and SPARQL endpoints provide access to hundreds of thousands of RDF datasets, representing billions of facts. Read more about "More Complete Resultset Retrieval from Large Heterogeneous RDF Sources"

DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released ( 2019-09-24T22:41:46+02:00 by Simon Bin)

2019-09-24T22:41:46+02:00 by Simon Bin

Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released"

DBpedia Day @ SEMANTiCS 2019 ( 2019-08-01T10:35:05+02:00 Sandra Bartsch)

2019-08-01T10:35:05+02:00 Sandra Bartsch

 We are happy to announce that SEMANTiCS 2019 will host the 14th DBpedia Community Meeting at the last day of the conference on September 12, 2019. Read more about "DBpedia Day @ SEMANTiCS 2019"

LDK conference @ University of Leipzig ( 2019-03-22T09:21:41+01:00 by Julia Holze)

2019-03-22T09:21:41+01:00 by Julia Holze

With the advent of digital technologies, an ever-increasing amount of language data is now available across various application areas and industry sectors, thus making language data more and more valuable. Read more about "LDK conference @ University of Leipzig"