Getting Started
To start exploring the biological data available, open your web browser and visit https://search.gfbio.org/. This site provides a straightforward search interface where you can begin by typing your search terms directly into the search bar. If you're looking for more specific results, you can use the filters on the left side of the page. These filters help narrow down your search results by various criteria, making it easier to find the data that's most relevant to your needs. For a more nuanced search, the platform offers a semantic search option. When you use this feature, the system enhances your keyword search by adding information from the GFBio vocabulary service's ontology (https://terminologies.gfbio.org/). This means if your search term matches a term in the ontology, the search will automatically include related terms. For instance, searching for a species by its scientific name will additionally search for its common names. This approach can be used to add results that are closely related to your original search query, providing a more comprehensive search outcome.
This approach helps in finding data that's more closely related to your search query, ensuring a more comprehensive search outcome.
RDC Integration
The search functionality is supported by an API that, as of now, is being used and assessed internally. This API is a key tool for enabling smooth interaction between different parts of the Research Data Commons (RDC). It's built to ensure that various components within the NFDI4Biodiversity framework can easily access and query the vast index of biological data that's available. The main goal of this API is to support the seamless flow of information across different platforms and databases, making it simpler for researchers and other users to find and utilize the data they need.
Customization
An exemplary implementation of the GFBio search tool can be observed at https://search.dda.gfbio.dev/. This instance showcases the potential of the GFBio search platform when customized for a specific scientific domain. By setting up their customized index, scientific organizations can curate the data available for search, ensuring that users have access to the most relevant and high-quality datasets. Furthermore, the ability to apply custom branding means that institutions can integrate the search tool seamlessly into their existing digital infrastructure, providing a consistent user experience that aligns with their visual identity and user interface design standards.
User Guide
You can use the search bar to perform a keyword based search. When using the semantic search button your search term is extended by further information when there is a match with a term in an ontology of the GFBio vocabulary service. This allows to find relevant data more reliably, e.g., extending scientific names of species with common names. On the left hand side of the search UI you can find various categories for filtering like the data center, regions and the date of data collection. This allows you to narrow down your keyword-based search in order to obtain only the search results that are most relevant to you. Each search item shows some information including a title, description, license and citation. If you click on the title you can even get more detailed information (e.g. additional media files like images).
Developer Guide
The UI component itself is implemented in Angular and combined with a thin backend layer written in Node.js, which is responsible for data processing. Developers can clone the repository and adapt the source code to their needs. A test instance of the search can be built for local testing using the start script included in the repository. The script builds the UI and the backend and runs the search interface in a dockerized environment available for your exploration and development via the browser. You can find the source code published here: https://gitlab-pe.gwdg.de/gfbio/search.gfbio.org.
References
Shafiei, F., Löffler, F., Thiel, S., Opasjumruskit, K., Grabiger, D., Rauh, P., König-Ries, B.: [Dai:Si] - A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data, Proceedings of the Joint Ontology Workshops (JOWO), 2021, url = https://ceur-ws.org/Vol-2969/paper4-s4biodiv.pdf