‘Have you made your due diligence?’ These six words induce fear and fear in any person involved in finance, with the underlying threat that great danger may be about to wrap it if the necessary task has not been done. The due diligence in the commercial sphere is a hygiene factor: a basic audit, if detailed, at risk to ensure that all possible results have been evaluated so that nothing from the carpentry comes out once an investment has been made.
The question, however, is equally important for academic institutions that seek to verify data on their research programs: Have you done your due diligence? that? If not, then a database linked as Dimensions It can help you.
Strategic objectives
In a Discussion of the recent panel organized by Times Higher Education (The) in Association with Digital Science When optimizing the research strategy, the issue of due diligence was framed when observing the life cycle of academic research and the challenges that emanate from the greatest amount of data now accessible to universities. More specifically, how universities could extract and use verified data from the growing number of sources that had at their disposal.
Speaking on the panel, the Technical Products Solutions Manager of Digital Science, Ann Campbell, believes that there are numerous benefits when using new data modes to overcome the problems associated with data overload. “It is important to think in an integral way, not only of the different systems that are involved here, but also of the different departments and interested parties,” he said. “It is better to have a general data model or a perspective when observing the life cycle of the research instead of separate research silos or different data silos that are within these systems.”
The panel acknowledged that the self -report for academics could lead to gaps in the data, while different impact data can also be lost due to the lack of knowledge or understanding in the name of the members of the Faculty.
Digital Science seeks to address these problems by adding some power to your database linked to its dimensions in the form of Google Bigquery. By marrying this computer power with the size and scope of dimensions, academics and research managers are empowered to identify specific data from all stages of the research life cycle. This allows researchers to combine external data without problems with their own internal data sets, giving them the holistic vision of the research identified by Ann Campbell in the discussion.
Wise of data
The issue of improving the capacities of higher education institutions when it comes to the use of data has been vividly described by Ann Campbell in its November presentation to the Conference of Digital Universities of Higher Education of Times in Barcelona in October. Memorably, he compared the use of universities with the plot of the popular television drama Game of Thrones. Teachers like dragons? Rival departments as families at war? Well, not quite, but what Ann observed was that there are many competitors within IEI (research management, research information, academic culture, library) and above them there is a high management that have key questions that can only be answered using data and ideas in all of them:
- What faculties have a high impact? Should we invest more in them?
- What faculties have a high potential but are under delay?
- How can we promote our areas of excellence?
- How can we identify departments with strong links with the industry?
- What real research impact on the world can we take our curriculum again?
- Are we mitigating the risk of potential reputation through openness and transparency?
Gathering these disparate challenges requires a narrative, which is another reason why the game analogy works as well as we see that for all the moving parts of history to work, a coherent story is required. This may be how the institution’s research culture strategy is working with an increase in early career collaborations, how an increase in new financing opportunities followed an impulse to increase the impact classification position due to the increase in SDG -related research.
Any good story needs to have the right ingredients, and where digital science can really help an institution is to gather those ingredients from an organization in visible and manageable narratives.
Counting stories
But the general panorama is not the whole story, of course. There are other smaller narratives that swirle through Heis at any time that reflect the different specialties, hot issues or university approach areas. Three of these focus areas that are most commonly found in modern universities are the integrity of research, industry associations and the impact of research, and these were recently discussed in another collaborative web seminar between digital science and science: Data use to offer research integrity, industry associations and impact.
This discussion panel was a bit more granular and caused some specific challenges for institutions when it was data use. For the integrity of research, certain data related to authorship can be used as ‘trusted markers’, based on authorship, reproducibility and transparency. Representation of Digital Science, Technical Product Solutions Manager Kathryn Weber -Ber, went through the trusted markers that form the base of the Integrity of dimensions research Solution for universities.
But why are these trusted markers important? The discussion of the panel also explained that the scope of interest outside universities, both financiers and editors were increasingly interested in the integrity of research and the origin of research emanating from universities. As such, products like Dimensions Research Integrity were forming a key part of the data management arsenal that universities needed in the modern research financing environment.
In addition, the use and scrutiny of these data can help move the dial in other important areas, such as changing the culture of research and integrity. Interested parties want to trust the research that is being done, know that it can be reproduced and also see that there is a level of transparency. All these factors influence the promotion and implementation of more open research activities.
Another important aspect of research integrity and data use is not just having information about where data is shared in what is also. Yeah It is shared as registered as, and where is it in fact lying. As noted in the discussion, Dimensions is a “set of data set data” and allows the cross reference of these pieces of information to understand whether the investigation integrity data points are aligned.
Positive perspective
Discussions on the integrity of data research and management can often be shadow issues, but there is some degree of optimism now there is a growing number of products in the markets to help IEI to meet their objectives and objectives in these spheres of activity. The effective use of the data, without a doubt, will be one of the critical success factors for universities in the future, and will not be only for the effective management of issues such as integrity or reputation of research. With rapid ray, Adoption of generative in the research space And the increase in interest in issues such as the security of international research and collaboration, the use of data, and the universities with which universities are associated to optimize it, has never been higher on the agenda.
You can see the web seminars here in Use of new data modes and Delivering research integrity.
About the author
Simon LinacreContent Manager, Brand & Press | Digital science
Simon has 20 years of experience in academic communications. He has given conferences and published on the issues of the Bibliometry, the ethics of the publication and the impact of the research, and has recently written a book on predatory publications. Simon is an ALPSP tutor and has also served as COPE trustee.
#Put #data #heart #organizational #strategy
