Professorale Karrieremuster der Frühen Neuzeit Early Modern Professorial Career Patterns
Entwicklung einer wissenschaftlichen Methode zur Forschung auf online verfügbaren und verteilten Forschungsdatenbanken der Universitätsgeschichte. Methodological research on online databases of academic history

PartnerPartners


​Hochschule für Technik, Wirtschaft und Kultur Leipzig (HTWK) University of Applied Science ForschungsgruppeResearch Group Agile Knowledge Engineering and Semantic Web

  • Thomas Riechert
  • Edgard Marx

Herzog August Bibliothek Wolfenbüttel (HAB)

  • Ulrike Gleixner
  • Hartmut Beyer
  • Jennifer Blanke

Netzwerk deutscher ProfessorenkatalogeNetwork of german professors catalogs

  • Catalogus Professorum Lipsiensium
  • Professorenkatalog Universität Helmstedt
  • Bamberger Professorinnen- und Professorenkatalog
  • Kieler Gelehrtenverzeichnis

Das Projekt ist gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer: 317044652

The project is funded by Deutsche Forschungsgemeinschaft (DFG) - Project-number: 317044652

ProjektzieleObjectives


Die Fragestellung nach Karrieremustern deutscher Professoren im 16. bis 18. Jahrhundert ist beispielhaft für die prosopographische Forschung, in welcher die Auswertung von gesammelten Informationen über Gruppen historischer Personen erfolgt. Dabei bezieht sich die Fragestellung auf eine Epoche, welche durch die Professorenkataloge der im Projekt kooperierenden Partner, den Catalogus Professorum Lipsiensium und den Helmstedter Professorenkatalog, abgedeckt ist. Innerhalb des geplanten Projektes soll eine Methode entwickelt werden, welche bekannte Forschungsmethoden aus den Geisteswissenschaften und der Informatik zusammenführt. Eine Vorarbeit stellt hier der Vorschlag für das Heloise Common Research Modell (HCRM) zur projektübergreifenden Forschung im Bereich der Universitätsgeschichte im Europäischen Netzwerk Heloise dar. Das HCRM, konzipiert als Schichtenarchitektur, erlaubt die unabhängige Forschung und Entwicklung auf den drei Abstraktionsebenen Repository Layer, Application Layer und Research Interface Layer. Im Rahmen des geplanten Forschungsvorhabens soll eine Methode auf dem HCRM entwickelt und durch die Beantwortung der Forschungsfrage evaluiert werden.

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 from 16th until 18th century. 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.

DatasetDataset


The project is producing a unique dataset and ontology that can be used and further extended for historian research.
The current dataset consists of data about scholars at the universities of Helmstedt and Leipzig in the Early Modern period (16th to 18 century).
The data was extracted from the Leipzig Professor's Catalogue and the Helmstedt Portal, i.a. the Helmstedt Professor's Catalogue:

Furthermore, it contains data extracted from the VD16, VD17, and VD18 datasets:

The easiest way of querying and accessing the dataset is by KBox, a distributed data catalogue publishing system that enables to share and query RDF knowledge graphs. For more information on KBox, access http://github.com/AKSW/KBox. For querying the PCP-On-Web data, download KBox v0.0.2-alpha and use the following command to create your own SPARQL endpoint using the project datasets:

java -jar kbox-v0.0.2-alpha.jar -server -kb "http://purl.org/pcp-on-web/ontology,http://purl.org/pcp-on-web/dataset,http://purl.org/pcp-on-web/vd" -install

Write your SPARQL queries directly on the Web-Client accessible by http://localhost:8080.

Notice that the command above includes three datasets:

  • The PCP-on-Web ontology:  http://purl.org/pcp-on-web/ontology;
  • The PCP-on-Web dataset: http://purl.org/pcp-on-web/dataset;
  • and the VD16, VD17, VD18 datasets: http://purl.org/pcp-on-web/vd.

You can also query different datasets by restricting -kb command line e.g.  -kb "http://purl.org/pcp-on-web/vd" in case you want to query only the VD datasets.

There is also the option of querying the dataset via command-line:

java -jar kbox-v0.0.2-alpha.jar -query "select ?s ?p ?o where {?s ?p?o}" -kb "http://purl.org/pcp-on-web/ontology,http://purl.org/pcp-on-web/dataset,http://purl.org/pcp-on-web/vd" -install

In the example above, we list all triples (?s ?p ?o) from the dataset. You can also download or report issues in our Github repositories:

If you are a hardcore user and want to download the dataset dump files or keep track of its changes, you can download the dataset at:

PublikationenPublications


Collaborative Research on Academic History using Linked Open Data: A Proposal for the Heloise Common Research Model. CIAN-Revista de Historia de las Universidades, (19)02016.

Kollaborative Forschung über Linked Open Data Forschungsdatenbanken der Universitätsgeschichte - Implementierung des Heloise Common Research Model. Abstraktband der Jahreskonferenz des Digital Humanities im deutschsprachigen Raum (DHd) e. V. Bern 2017, 2017.

Triple Scoring Using a Hybrid Fact Validation Approach - The Catsear Triple Scorer at WSDM Cup 2017. WSDM Cup, co-located with the 10th ACM International Conference on Web Search and Data Mining, 2017.

KBox: Distributing Ready-to-query RDF Knowledge Graphs. Proceedings of ESWC Posters and Demos, 2017.

A Decentralized Architecture for SPARQL Query Processing and RDF Sharing: A Position Paper. Semantic Computing (ICSC), 2018 IEEE 12th International Conference on, 274--277, 2018.

Semantic Search User Interface Patterns: An Introduction. Human Computer Interaction (HCI-Europe) 2017, Plzen, Czech Republic, 2017.

The Neural SPARQL Machine Telegram Chatbot. Workshop on Linked Data Management co-located with the W3C WEBBR 2018, 2018.

Generating a Large Dataset for Neural Question Answering over the DBpedia Knowledge Base. Workshop on Linked Data Management, co-located with the W3C WEBBR 2018, 2018.

KontaktContact