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The Case of the Indian Research Information Network System (IRINS)

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The Case of the Indian Research Information Network System (IRINS) Pre-print submitted to the Journal of Research Management and Administration (JoRMA) The Rise of Current Research Information Systems (CRIS): The Case of the Indian Research Information Network System (IRINS) Pablo de Castro 1,2 * http://orcid.org/0000-0001-6300-1033 Siva Shankar Kimidi 3 https://orcid.org/0000-0002-7629-1305 Kannan Palavesm 4 http://orcid.org/0000-0002-4121-5919 1 euroCRIS, Heyendaalseweg 141, 6525 AJ Nijmegen, The Netherlands 2 Information Services Directorate, University of Strathclyde, 101 St James Road, Glasgow G4 0NS, Scotland, United Kingdom 3 Information and Library Network (INFLIBNET) Centre, Infocity, Gandhinagar, Gujarat 382421, India 4 Central University of Punjab Library, Mansa Rd, Bathinda, Punjab 151001, India Corresponding author: [email protected] Abstract The paper describes the rapid arising of a national-level research information management infrastructure (RIM) in India as a case study for a bottom-up Current Research Information System (CRIS) implementation strategy. Less than a year and a half after its first launch, the Indian Research Information Network System (IRINS) has become a widespread institutional RIM asset with over 180 instances at Indian research-performing organisations. As a result, India is currently leading the classification by number of CRIS per country in the euroCRIS Directory of Research Information Systems (DRIS), followed by Norway and the United Kingdom. As a background to the case study, the broad international CRIS context is also analysed. The causes for the quick rise of such systems are examined, together with their national-level implementation models in various countries and the differences between CRIS and expert finder systems. Keywords: research information management; current research information systems; CRIS; Indian Research Information Network System; IRINS; India 1. The emergence of Current Research Information Systems The past twenty years or so have seen a remarkable increase in the implementation of so- called Current Research Information Systems or CRIS. These CRIS systems, also known as Research Information Management Systems or RIM systems (Wikipedia 2019), aim to capture as comprehensive a snapshot as possible of the research activity conducted at an institution (usually a university or a research centre), a geographic aggregation thereof (for regional or national CRISs) or by a specific research funder. The way this information is captured is by collecting in a single platform as much metadata as possible on the multiple areas that make up the research effort: people (researchers and academics), organisations (faculties, departments, schools, research institutes, research units, research groups), research projects, research outputs (publications, research data, software, patents), equipment (research instruments and facilities) and many others. All these categories are called 'entities' in the relational data model that underpins CRIS systems. This data model is called the Common European Research Information Format (CERIF) (euroCRIS 2014) and is maintained by a non-profit organisation based in the Netherlands called euroCRIS that was founded in 2002. All these entities are connected to each other forming a so-called research graph: for instance, a publication (say a journal article) is produced by a group of persons (researchers) associated to their organisational units and (potentially) funded by one or several research projects granted by one or various research funders. A research dataset typically underpins the publication and is shared as supplementary material for the article, data that has resulted from the use of a research instrument or facility. The CERIF model is flexible and extensible, meaning that it allows to capture potentially very valuable information for reporting and analysis purposes such as the number of PhD students associated to a specific organisational unit and the number of dissertations produced by such a unit in a given time span. Or the research collaboration patterns for a specific unit with other institutions and research groups, including with industry. Very interesting works are starting to be produced already from the analysis of these data-driven patterns (Elsevier 2015), and this trend will only become more intense in forthcoming years. There are multiple reasons why these CRIS systems have seen such a significant growth in the past few years, some of which are: a post-industrial knowledge economy privileges areas of activity associated to data- driven analysis and reporting ; increased awareness for the need for transparency and accountability for the public funding that supports the vast majority of the research activity carried out at universities and research centres (De-Castro 2017); need for accurate and comprehensive data on research activity for evidence-based decision-making by the relevant stakeholders (governments, research funders); subsequent reporting requirements by research funders – for their funding programmes – and by governments via national-level research assessment exercises used to support the funding distribution to universities and research centres; internal reporting requirements at such institutions for decision-making processes including promotion; via their front-end platforms, often called research portals, these systems allow research-performing organisations to showcase the research activity they conduct as well as its results. This is important for attracting talent and students, for promoting research collaborations and for highlighting their contribution to society; increased discoverability of research work and experts helps research funders identify suitable reviewers for the project proposals they receive and allows interested stakeholders (often Industry) to identify possible collaborators for public-private partnerships; need for a system that allows cradle-to-grave funded project management, i.e. from the preparation of a project proposal to the final research and economic reporting to a specific research funder; CRIS systems are proving critical pieces of the distributed e-infrastructure required for the implementation of open science. Because institutions need researchers to systematically record their research activity in them, they contain a great deal of information on research publications and data that can be processed by the adequate institutional units (usually research libraries) in order to foster openness and re- usability where appropriate. The growth of CRIS systems has been particularly significant in Europe, where countries are frequently running research assessment exercises (Sivertsen 2017). These mean that research-performing organisations such as universities need to rely on all-encompassing data gathering systems to report to the government on the quality of their research activity. The way this is done varies across countries: in the United Kingdom, the institutional reporting for the national-level Research Excellence Framework (REF) is composed of lists of the best publications produced at an institution during a period of typically 7 years together with the so-called impact case studies, where a more qualitative approach to the social and economic impact of a given research line is followed via the drafting of specific case studies (HEFCE 2015). The information backing such case studies (research collaborations started, project funding earned, collaborations with industry made possible by a given research effort) is systematically collected from these CRIS systems that gather all the data for the institutional research activity. It's subsequently in Europe where most of the CRIS implementations are based that are collected in the Directory of Research Information Systems (DRIS) maintained by euroCRIS (euroCRIS 2020), with countries like Norway, the UK, Italy Poland, Spain or Germany showing a large number of mostly institutional CRISs. It's interesting however to see that in the distribution of available CRISs by country in the euroCRIS DRIS, the country that tops the list is not a European one: it's India. This is due to the very successful and rapid implementation of the Indian Research Information Network System (IRINS) developed at INFLIBNET in Gandhinagar and at the Central University of the Punjab (Siva-Shankar and Kannan 2020). At the time of writing (early June 2020) IRINS already has 184 implementations of its system at Indian research- performing organisations and keeps growing. This nominally makes it the most successful CRIS system in the world, were it not for the fact that it's not CERIF-compliant, meaning that it's not currently able to exchange information across platforms via the regular system interoperability mechanisms that are applied by most CRIS systems in Europe. This paper examines the remarkable expansion of IRINS in India, together with the system features that may allow research institutions to better keep track of their research activity and with the next steps to be taken in order for such a comprehensive system infrastructure to result in a better research administration and management in the country. Why system interoperability is a key feature of CRISs In order for the wealth of research information metadata held in this layer of CRIS systems across institutions and countries to be adequately mined and exploited, information exchange standards need to be in place that allow this data to be aggregated. These interoperability mechanisms should allow a more comprehensive snapshot
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