Research Data Architectures in Research Institutions IG

Introduction

The Research Data Architectures in Research Institutions Interest Group is primarily concerned with technical architectures for managing research data within universities and other multi-disciplinary research institutions. It provides insight into the approaches being taken to the development and operation of such architectures and their success or otherwise in enabling good practice.

An institution’s research data management infrastructure consists of more than just a data repository and discovery mechanisms. It includes the underlying storage technologies, the networking, hardware, system interfaces, authentication mechanisms, data brokers, monitoring platforms, semantic interoperability tools, long-term preservation services, high-performance and high-throughput computing facilities, data science platforms, and potentially many other technologies that process data and control the flows of data and metadata between systems.

Seamless data interoperability and movement between different systems both local and in national or disciplinary services is a particular challenge at present, given the need to provide researchers with a smooth and efficient user experience – a key requirement for any research data service. Governance and policies, project management environments, and communications platforms are also vital elements in shaping and informing IT architectures, as is the management of business information associated with research.

This IG seeks to understand the various architectures used by institutions globally, identify pain points within those architectures, and learn from those who have overcome or avoided those pain points.
The general approach of this IG is to encourage discussion about architectures and enable interested parties to collaborate and learn from one another. Many institutions are at present planning and working towards overarching data management architectures, and there is a legitimate concern that without such a forum as is provided by this IG institutions will relive the same experiences and repeat the same mistakes as their peers.
 

With the one word, this is about nuts and bolts of the research data infrastructures used in the local research infrastructures.

User scenario(s) or use case(s) the IG wishes to address

The Research Data Architectures Interest Group treats the following user scenarios:

• Knowledge support for research data infrastructure architects, and project and service managers
• Knowledge sharing regarding enterprise architecture best practises  at multi-disciplinary research institutions
• Development of a greater understanding of objectives and goals between different stakeholders at research institutions, including  management, infrastructure developers, research data engineers,  IT systems architects, and technology vendors.

Objectives

The main themes of the IG are

• Exploring how diverse tools, technologies, and services can be integrated to meet the evolving needs of researchers in research institutions.
• Considering interoperability between institutional research data infrastructures and (inter)national or discipline-based infrastructures
• Understanding the different institutional approaches to governance structures and business processes in responding to research ICT demands (e.g. capacity planning/forecasting for storage)
• Sharing case studies of solutions developed by data infrastructure projects in research institutions
• Presenting technical innovations and ideas that can further the development of integrated research data infrastructures
• Agreeing best practice relating to research data architectures in research institutions

Meeting Agenda:

Collaborative Meeting Notes Link:

https://docs.google.com/document/d/15_cDBZjBsCO_vMAcc4_MiPrTno8Gtk0F2r4A...

Participation

The target audience of this IG includes anyone involved in research data infrastructure planning projects or services as well as researchers with an interest in systems, technologies and data flows at the institutions level. This includes research data infrastructure project managers, ICT architects, senior managers with responsibility for research IT services, developers, data managers, data engineers, and data scientists. Also representatives of the service or technology vendors and data industry are welcome.