How does Rich Data Services differ from other solutions?

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We built Rich Data Services based on our many years of experience collaborating with data producers, archives, researchers, and scientists, and our involvement in data/metadata standards. RDS modernizes access to data through the use of industry-standard web services and metadata. The platform’s core objectives are to empower information systems, reduce data and code wrangling, and foster the adoption of best practices.

There are naturally other platforms available that may at first be perceived as similar in nature or purpose. RDS' role, however, is often to supplement existing tools, and for example is a great add-on option for your databases, or complement to data catalog tools such as DataVerse, CKAN, IHSN NADA, and the likes.

When it comes to other data publications platforms, such as Socrata, Statista, Nesstar, or Kaggle, RDS' key differentiators include:

1. Concurrent delivery of data and metadata: this is a fundamental aspect of the platform. RDS not only delivers data, but includes information about variable/field names, code and value labels, data source/provenance, and more. This is essential for ensuring the effective and responsible use of the data.

2. Built as a web service (API): RDS is first and foremost an API designed to concurrently deliver data and metadata as a service, drive analysis, and empower information systems, web portals, visualizations, and applications. Other platforms' APIs on the other hand are commonly designed to drive proprietary user interfaces, limiting or constraining capabilities.

3. Deployable in cloud or on-premise: RDS can be deployed in any cloud environment or on-premise. Other solutions may be bound to a specific cloud vendor or proprietary data storage, not only constraining operational environment, features, migration, or scalability, but also raising barriers in terms of meeting data security compliance or legal requirements.

4. Data back-end independence: RDS relies on external database servers for storing and querying the data. This decouples our systems from the database engines, offering a broad range of options to meet your needs or budget, from entry-level or open-source servers to clusters or data lakes for big data or high-performance purposes.

5. Driven by standards and best practices: The RDS web services use industry-standard REST API and documented using OpenAPI specification and Postman. The RDS underlying metadata models are based on domain standards advocated by Research Data Alliance, HLG-MOS, DDI Alliance, GO FAIR, and the like.

6. Backed by both IT and data management experts: We are not only a skilled software development team. Through project collaboration with numerous data producers, archives, and research organizations around the globe, we have extensive experience in data/metadata management and a deep understanding of the issues surrounding data publication and quality.

In addition to the above, we aim to offer fair and competitive pricing, and are willing to work personally with our clients to ensure that RDS provides them with the value they are looking for. We see each project as an opportunity to collaborate and modernize access to data, positively impact research/analysis, support evidence-based decisionmaking, and foster best practices.

Further, we are working closely with Postman, the world's leading collaboration platform for API development, to ensure data published through RDS is easily accessible and understandable by developers and data scientists worldwide.