Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Digital Libraries

arXiv:2211.11252 (cs)
[Submitted on 21 Nov 2022]

Title:OSDG 2.0: a multilingual tool for classifying text data by UN Sustainable Development Goals (SDGs)

Authors:Lukas Pukelis, Nuria Bautista-Puig, Gustė Statulevičiūtė, Vilius Stančiauskas, Gokhan Dikmener, Dina Akylbekova
View PDF
Abstract:Despite concrete indicators and targets, monitoring the progress of the UN Sustainable Development Goals (SDGs) remains a challenge, given the many different actors, initiatives, and institutions involved. OSDG, an open-source classification tool aims to help navigate the SDG related ambiguities through a simple and easy to use application. The tool allows to map and connect activities to the SDGs by identifying SDG -relevant content in any text. This paper presents OSDG 2.0, a new iteration of the partnership's work, which marks a significant improvement in the tool's methodology, as well as support for content in 15 languages.
Subjects: Digital Libraries (cs.DL)
Cite as: arXiv:2211.11252 [cs.DL]
  (or arXiv:2211.11252v1 [cs.DL] for this version)
  https://doi.org/10.48550/arXiv.2211.11252

Submission history

From: Lukas Pukelis Dr [view email]
[v1] Mon, 21 Nov 2022 08:41:57 UTC (790 KB)
Full-text links:

Access Paper:

  • View PDF
  • Other Formats
license icon view license
Current browse context:
cs.DL
< prev   |   next >
new | recent | 2022-11
Change to browse by:
cs

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)