Discussion 3: Richard Grant, 13th September 2010
Duration: 1 hour 25 mins 12 secs
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About this item
| Description: | Richard Grant is a scientist and author of the blog “Confessions of a (former) Lab Rat”. He is Associate Editor and contributor to The Scientist/Faculty_of_1000. Richard is a scientist with interests in scientific publishing, copyright, and Open Data. |
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| Created: | 2011-01-31 10:47 | ||||
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| Collection: | Panton Discussions | ||||
| Publisher: | University of Cambridge | ||||
| Copyright: | University of Cambridge | ||||
| Language: | eng (English) | ||||
| Distribution: |
World
(downloadable)
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| Credits: |
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| Explicit content: | No | ||||
Transcript
Transcript:
Panton Arms, Cambridge
Monday 13th September, 2010
Present: Richard Grant, Peter Murray-Rust (Adam Thorn - recording)
1. RG explaining the difference between "The Scientist" and "Faculty of 1000"
2. RG continues to describe "Faculty of 1000": how the subscription model works, detailing recruitment to the Faculty, benefits of being a Faculty member
3. RG asks: "How did you get involved in open data, and where did it start from?". PMR responds with a brief historial overview.
4. PMR continues with a description of how ideas about open data differ between different fields of science, e.g. astrophysics, crystallography, and the biological sciences
5. RG asks (in the context of submitting data with publications): "Biologists have been doing this for some time now. What kind of data could I submit?" PMR responds with a discussion of how different fields cope, and how different fields are moving towards a "pipeline of data", from raw data through different types of data processing.
6. RG: "How do people respond when they come across the whole idea of open data?"
7. RG: "Have you had any opposition to open data from scientists who are funded privately?" PMR discusses the dangers of partially publishing small aspects of an experiment without releasing their data (for example, due to confidentiality)
8. A discussion about "carrots" and "sticks" to persuade publically-funded scientists to release their data, who might otherwise feel that giving away too much information will do them harm in the long run.
9. RG: "How are people getting on with DOIs for data?" PMR responds by describing some of the difficulties with data sets, such as their time-varying nature.
10. A discussion of using DOIs/URIs for blog posts, as they're becoming part of the scientific record.
11. RG: "Are you having pushback from paid journals about making the data that is referenced in their papers available?" PMR discusses the "long-tail", where most papers produces a small amount of science, and the importance of making supplental data available. For example, some journals insist upon data submission as part of the publication process to aid in validation of the research.
12. Discussion of publications based upon fradulent data, and how open data can combat such publications - e.g., checkCIF used to look for potential problems with crystallographic data.
13. RG: "Do you think that people are going to move away from publishing discrete articles in journals, especially if you've got all the data available?" PMR responds by discussing the conservative nature of publishing. He also raises the point that a great deal of important work occurs outside academia, using crowdsourcing as an example.
14. RG introduces the Posters project, whereby conference attendees are encouraged to submit their poster to a searchable, free-to-access index. PMR emphasises the benefits of CC-BY for such projects
15. PMR asks "How does one make a commercial business from open material?".
16. RG's document clearing house.
17. PMR discusses the vision of semantic publishing, and Chem4Word. Also a discussion on the merits of having a standard mechanism for submission of images to journals.
18. RG: "What about funders?" Leads to a brief discussion of Climategate as an example of why publically-funded research needs to make their data open
19. A discussion of the importance of instilling the importance of data management at an early stage in undergraduate teaching. The example of using the Electronic Notebook to manage data is discussed, along with the manipulation of digital images.
20. A continuation of the discussion about electronic notebooks, and the importance of the role of such tools in providing an audit trail to ensure that recorded data is a complete record of an experiment.
21. A discussion of the semantic web and machine learning - for example, automatically extracting chemical reactions from raw documents
22. Automatic patent analysis, and the importance of ensuring that historical data is not lost because of potential difficulties with analysing old documents
Monday 13th September, 2010
Present: Richard Grant, Peter Murray-Rust (Adam Thorn - recording)
1. RG explaining the difference between "The Scientist" and "Faculty of 1000"
2. RG continues to describe "Faculty of 1000": how the subscription model works, detailing recruitment to the Faculty, benefits of being a Faculty member
3. RG asks: "How did you get involved in open data, and where did it start from?". PMR responds with a brief historial overview.
4. PMR continues with a description of how ideas about open data differ between different fields of science, e.g. astrophysics, crystallography, and the biological sciences
5. RG asks (in the context of submitting data with publications): "Biologists have been doing this for some time now. What kind of data could I submit?" PMR responds with a discussion of how different fields cope, and how different fields are moving towards a "pipeline of data", from raw data through different types of data processing.
6. RG: "How do people respond when they come across the whole idea of open data?"
7. RG: "Have you had any opposition to open data from scientists who are funded privately?" PMR discusses the dangers of partially publishing small aspects of an experiment without releasing their data (for example, due to confidentiality)
8. A discussion about "carrots" and "sticks" to persuade publically-funded scientists to release their data, who might otherwise feel that giving away too much information will do them harm in the long run.
9. RG: "How are people getting on with DOIs for data?" PMR responds by describing some of the difficulties with data sets, such as their time-varying nature.
10. A discussion of using DOIs/URIs for blog posts, as they're becoming part of the scientific record.
11. RG: "Are you having pushback from paid journals about making the data that is referenced in their papers available?" PMR discusses the "long-tail", where most papers produces a small amount of science, and the importance of making supplental data available. For example, some journals insist upon data submission as part of the publication process to aid in validation of the research.
12. Discussion of publications based upon fradulent data, and how open data can combat such publications - e.g., checkCIF used to look for potential problems with crystallographic data.
13. RG: "Do you think that people are going to move away from publishing discrete articles in journals, especially if you've got all the data available?" PMR responds by discussing the conservative nature of publishing. He also raises the point that a great deal of important work occurs outside academia, using crowdsourcing as an example.
14. RG introduces the Posters project, whereby conference attendees are encouraged to submit their poster to a searchable, free-to-access index. PMR emphasises the benefits of CC-BY for such projects
15. PMR asks "How does one make a commercial business from open material?".
16. RG's document clearing house.
17. PMR discusses the vision of semantic publishing, and Chem4Word. Also a discussion on the merits of having a standard mechanism for submission of images to journals.
18. RG: "What about funders?" Leads to a brief discussion of Climategate as an example of why publically-funded research needs to make their data open
19. A discussion of the importance of instilling the importance of data management at an early stage in undergraduate teaching. The example of using the Electronic Notebook to manage data is discussed, along with the manipulation of digital images.
20. A continuation of the discussion about electronic notebooks, and the importance of the role of such tools in providing an audit trail to ensure that recorded data is a complete record of an experiment.
21. A discussion of the semantic web and machine learning - for example, automatically extracting chemical reactions from raw documents
22. Automatic patent analysis, and the importance of ensuring that historical data is not lost because of potential difficulties with analysing old documents