I took the mission and vision statements from geological societies and surveys at International, European and National levels then semantically clustered in a word cloud. The colours are words grouped by similarity (share similar words). A few themes emerge (my interpretation): 1. Red - Using knowledge to address humanities challenges for a sustainable planet 2.... Continue Reading →
The grand challenges of geoscience
I created this blog exactly 8 years ago in mid 2015. The aim was to share ideas, research, technologies and methods on text analytics, search and data management applied to geoscience. This would hopefully stimulate and accelerate the exploitation of geoscience information by practitioners for the benefit of industry and society. It has gone from... Continue Reading →
Using Natural Language Processing to detect historical flooding events and risk reduction projects from newspapers
I came across this fascinating open access research paper by Lai et al (2022). Using NLP to extract street flooding events (green) and risk reduction projects (red) from hundreds of thousands of newspaper articles in the United States. By spatially viewing this data gaps in governmental strategies could be identified. I found this passage of... Continue Reading →
Fossil horse teeth (molars) from Peace River, Florida
A brief change from the virtual world of geoscience digital search and text analytics to the physical world! Some Pleistocene (Ice Age) horse teeth - molars- my family and I found recently from the Peace River in Florida. You can find out more about what you can find in the river bed here: https://fossilhuntingtours.com/types-of-fossils-found-in-the-peace-river-area/
Information Exploitation: Conceptual Model using digital technologies tied to educational objectives and work tasks.
The conceptual model repurposes Blooms Taxonomy (Armstrong 2010). A work in progress - still evolving. Contribution - help organisations identify gaps in their exploitation strategies for the organisational 'exobrain' - large volumes of unstructured data and AI. Abstract currently submitted to EAGE. If accepted I'll post the full extended abstract here. The presentation will tie... Continue Reading →
New research on geoscience natural language processing
Some new research published on geoscience text analytics. Research driven from China and Canada. Predominant focus on mining, using vectorspace and knowledge graphs on automatically extracted entities and concepts. Looking at associations to predict new deposits. Lawley et al (2023). Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling. Natural Resources Research.... Continue Reading →
Data Management and Artificial Intelligence II
Data Management and Artifical Intelligence. Final model from my presentation this week at the Society for Professional Data Managers using the Cynefin framework (Snowden) for aiding decision making in various situations applied to data management through semi fictitious examples. Key points: 1. Perspective: Being a data manager is so much more than just clicking a... Continue Reading →
Data Management and Artificial Intelligence
Data Management and Artificial Intelligence. One of the models from my presentation at the Society for Professional Data Managers yesterday. Two sides of the same coin. Evolving nature of the role. Excellently put together, the online SPDM conference is still ongoing, great presentations and debate recommend to drop in and listen or join the discussion!... Continue Reading →
Large Language Models, Semantic Search, Vectors and Petroleum Systems
Language Models, Search, Vectors and Petroleum Systems: I’ve conducted some research on how well sentence transformers and other approaches are able to match a user query to sentences in order to answer questions and summarise. It’s a continuation from other posts I’ve made recently. A question was posed “Where are the potential hydrocarbon traps?”, with... Continue Reading →
Data Management and ChatGPT: Answering queries from a database of no predefined schema.
Transformers over pre-trained Large Language Models (LLM) can be applied to facts expressed in natural language 'sentences' to answer certain queries. They can perform the selections, joins and projections required. An advantage of this approach is that 'the database' has no predefined schema and queries can be written as people prefer. Take these 3 sentences... Continue Reading →