Data Development
Financial Research Data Infrastructure
The Financial Research Data Infrastructure provides users with financial data and additional services to boost financial research.
Description
The project „Financial Research Data Infrastructure“ aims to solve two fundamental problems of empirical research in the financial sector. First, the lack of research-ready pan-European financial data sets implies that many financial researchers analyze US data sets instead. The findings of their studies are therefore not easily transferable to the European financial markets. Second, empirical financial researchers often use proprietary data sets and their incentives to share such data sets with other researchers are low, which weakens empirical research in the financial sector. Therefore, our team build the Financial Research Data Infrastructure. We generate new research-ready European financial data sets and enriche them to put them into the context of research. We focus on innovating on our platform to create incentives for our users to share research data or metadata to best fulfill the FAIR principles (Findable, Accessible, Interoperable, Reusable).
- Data Production
- Data Enrichment
- Data Visualization
- FAIR Principles
Description of ETL Process
We implement Extract-Transform-Load (ETL) processes to automatically collect, process, publish and update research data. Our flexible ETL processes cope with unstable links and various data formats and standardize research data to provide the best access to our users.
Description of Data Visualization
Our users can put research data and papers into context using our network visualization, which displays how papers and data are connected. They can also use this visualization to search for research data and papers via adjusting the metadata, which are used to build the network, and the number of nodes (Co-occurences). Finally, they can download all metadata of the research data and papers in the network at once to get a fast overview of the most important papers in a specific research area.
Description of Data Visualisation
Our users can put research data and papers into context using our network visualization, which displays how papers and data are connected. They can also use this visualization to search for research data and papers via adjusting the metadata, which are used to build the network, and the number of nodes (Co-occurences). Finally, they can download all metadata of the research data and papers in the network at once to get a fast overview of the most important papers in a specific research area.
Working Tasks
Data Production
We implement ETL processes to automatically collect, archive and provide research-ready financial European data sets.
Securities Lending
We produce data of the public sector purchase programme (PSPP) and the corporate sector purchase programme (CSPP).
Eurex Repo
We produce data on the Baskets of the GC Pooling Market.
European Historical Data
We provide data on the historical money and capital database.
Data Enrichment
In order to put data into context, we enrich them via metadata to make them more findable and accessible.
Basic Metadata
We provide the standard documentation including description of data, authors, date, etc.
Advanced Metadata
We generate metadata for research data based on the research papers, which use such data including keywords, classifications and references.
Innovative Metadata
We implement machine learning methods to extract latent topics of research data to make them more comprehensive and easily understandable.
Data Visibility
To improve the users‘ experience on our platform, we visualize all our data and let users easily download their most important findings.
Network Visualization
Our metadata connect all research data and papers and thus put them into context. Users can adjust the visible network via their selection of metadata.
Efficient Searching
Once our users generate their optimal network around a research data set or paper, they can quickly download the most relevant connected research data or papers.
Recommender Tool
We develop a recommender tool which provides relevant papers and potential journals based on a papers text and metadata.
Contact
Lennart Kraft
lennart.kraft[at]wiwi.uni[hyphen]frankfurt.de
Address
Raum 1.202 im RuW-Gebäude
Theodor-W.-Adorno-Platz 4
D-60323 Frankfurt am Main