Welcome to your Semantic Co-Working Space!

The SODa Semantic Co-Working Space (SCS) is a digital infrastructure made up of various tools for diverse tasks across the collections data lifecycle. It offers many ways to connect, research, and learn. It was developed as part of the SODa project and is the technical foundation for the services, best practices, and content offered there.

Support for your collections data lifecycle

Users have access to various applications that allow them to model, develop, transform, migrate, analyze, visualize, store, publish, enrich, or process data with programming code.

Concept & planning

Conceptualizing and planning indexing and digitization projects is supported within the Semantic Co-Working Space by a collaborative office environment (Nextcloud). Integration of OnlyOffice and draw.io broadens the use case. Responsibilities can be organized via projects in the SCS.

Preparation & enrichment

Preparing data in substance includes, among other things, contextualization through metadata, annotations, and relationships between objects. Ontologies can be edited in WebProtégé, while OpenRefine supports data cleaning and enrichment.

Creating structured data

Structured creation of object and collection data is enabled for users through the ontology-based virtual research environment WissKI (Wissenschaftliche Kommunikationsinfrastruktur). Data are stored in an SQL database and a triple store and can be analyzed via JupyterHub.

Legal & ethical aspects

With regard to legal and ethical aspects, copyright and personality rights, data protection, and usage rights must in particular be reviewed and documented. Where possible, open licences should be applied, and ethical requirements observed by marking and protecting sensitive content.

Data quality & compatibility

The quality and compatibility of data are improved through the use of standards, authority data, and linked open data. In WissKI, modelling is typically based on the ISO standard CIDOC CRM. For the base data model in the SCS (an implementation of the minimal dataset recommendation for museums and collections), this has been extended.

FAIR long-term availability

Long-term availability is ensured by WissKI repositories, which—through ontology-based storage of data, automatic generation of persistent identifiers (PIDs), and provision of data via interfaces—enable durable, FAIR-compliant access to structured collection data.

Applications within a few clicks for you and your team

It is designed for people who work with academic university collections. To use the Semantic Co-Working Space, you need to register for a new account. Access to all applications and instances is managed for each user via a Keycloak account. In addition, as part of an IAM4NFDI incubator grant, login via didmos (DAASI IdM with open source) was implemented, enabling connection to the authentication and authorization infrastructure of the German Research Network (DFN-AAI).

This makes the SCS an integrated web environment that provides proven applications for digital work with collection data. It allows users to get started quickly, supports collaboration in complex contexts, and increases efficiency through preconfigured systems. Access can be extended to projects. That way you can easily share access to your applications with other users in the SCS without laboriously creating user accounts and managing their credentials. 

Simple collaboration and data integration

Web apps such as WissKI and cloud services such as Nextcloud let you work on your projects at the same time and share data via shared folders with applications and people. You can use Nextcloud to create, edit, and manage office files, make them easily available in a shared folder in your JupyterHub, process them there with Python or OpenRefine, and import and publish them in WissKI or other databases.  

Professional support from competent partners

In addition to regular workshops on using the SCS, our infrastructure team is available for any questions about the SCS. Furthermore, the options in the SCS are tailored to the requirements and skills of our subject matter experts. They support you on substantive questions across the collections data lifecycle and how to implement it in the SCS. For an introduction, please contact our infrastructure team, the helpdesk, or the relevant subject matter experts.

Available applications and environments

JupyterHub is your personal data science workspace and a powerful, interactive environment where you can analyze data, create visualizations, and conduct research without needing to install any software on your computer. When you access your JupyterHub environment, you get a complete toolkit for data analysis and research that includes everything you need to get started immediately.
MariaDB is an open-source relational database management system that serves asside of the OpenGDB triplestore as on of the primary data storage engines for structured data. MariaDB is a drop-in replacement for MySQL, offering high performance, security, and scalability for storing application data, user information, and system configurations.
Nextcloud is a file storage and collaboration platform that functions as your personal cloud workspace. It operates as a shared service where you receive an account rather than a dedicated environment, providing you with access to online storage and office productivity tools through a web interface.
OpenGDB is an RDF4J-based triplestore that extends the standard RDF4J server with comprehensive user management and security features. The system builds upon RDF4J's core functionality by adding a Django-based authentication layer, repository management capabilities, and network security controls through a specialized proxy that prevents internal network access via SPARQL queries. The entire solution is packaged for deployment using Docker containers.
WebProtégé is a free, open-source, web-based platform for collaborative ontology development that enables users to create, edit, and share OWL 2 ontologies directly through a web browser. The platform eliminates the need for local software installations while providing comprehensive tools for knowledge modeling and collaborative ontology engineering.
WissKI (Wissenschaftliche KommunikationsInfrastruktur - Scientific Communication Infrastructure) is a specialized content management system built on Drupal that serves as a digital platform for managing cultural heritage objects, museum collections, and scholarly research data. In this system, WissKI is preconfigured to record and manage (university) collections and ships with a OpenGDB triplestore, MariaDB database, and with a default data model and module setup (WissKI Default Barrel).