the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Dec 2024
GC Insights: Breaking the silos – leveraging NLP to encourage interdisciplinary interaction at the EGU
Abstract. Thousands of abstracts from various geoscience sub-fields are presented annually at the EGU General Assembly (GA), offering a rich resource for tracking scientific progress. However, rigid session groupings can limit cross-disciplinary exploration. Here, we show that participants focusing only on their broad disciplinary session miss an average of 44 % of the 10 most relevant contributions. To break this compartmentalization, we propose using natural language processing (NLP), enabling the geoscience community to explore the full breadth of knowledge beyond traditional disciplinary boundaries.
- Preprint
(1286 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 12 Feb 2025)
-
RC1: 'Comment on egusphere-2024-3430', Lina Stein, 17 Jan 2025
reply
The authors present an analysis of all abstracts submitted to the EGU General Assembly in the last five years. The abstracts are clustered according to semantic similarity of the abstract text. For each scientific division, the distribution of abstracts across the cluster space is evaluated to demonstrate that similar research is submitted across different scientific divisions within the EGU GA. The authors claim, that since attendees primarily attend sessions from their own scientific division, this means attendees might miss relevant research (bubble effect). I found the overview of abstract similarity across scientific divisions very informative. It demonstrates that the scientific divisions have more overlap than the strict separation necessary for conference organization might suggest.
Additionally, the authors propose a webtool, which can recommend EGU GA submissions based on similarity to a search string. I have actually used the prototype during the 2024 EGU and found it immensely helpful.
Overall, I find this article timely, relevant, and well-written. I only have a few minor suggestions for improvement.
Specific comments:
Your main assumption is that people will not attend presentations of research similar to their own submission due to it being in another scientific division. E.g. Line 10 “We hypothesize that this compartmentalization may inadvertently create knowledge silos, as EGU GA attendants tend to focus on their own scientific divisions, potentially missing relevant developments from other disciplines.” From my own (probably biased) experience I would say that cross-division attendance does take place a lot during EGU. And the EGU website does already offer a search tool that allows people to find abstracts across scientific divisions according to keyword searches. However, text similarity offers a much better tool to identify presentations of interest. Simple keyword searches often still produce a large number of results. While it is, of course, impossible to quantify which scientific division sessions are attended by whom during the GA, it would help your claim to offer some more numbers to demonstrate the infeasibility of manually checking all sections for relevant contributions. How many abstracts are submitted per section? How many sessions are registered per section?
On thing I found irritating is that the 22 scientific divisions or scientific sections are referred to as sessions. There are multiple sessions organised within each scientific division. But the authors split their data into scientific divisions and called them session. That the selection on the EGU GA website offers “Disciplinary sessions” is not a name, but means that they are the session related to one specific division.
Please clarify in the abstract and text what you mean by participant exploration or participant focus. It should be stated early on and more clearly, that you refer to choice of session/division attendance during the GA. (And not, for example, choice of session during the abstract submission process).
Lastly, it would be nice to add the number of people who have used the webtool to find relevant sessions during EGU24.
Citation: https://doi.org/10.5194/egusphere-2024-3430-RC1
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 252 | 90 | 6 | 348 | 1 | 1 |
- HTML: 252
- PDF: 90
- XML: 6
- Total: 348
- BibTeX: 1
- EndNote: 1
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1