Synthesis Infrastructures - User contributions [en]

Sci2sci

2022-11-12T11:01:52Z

An libertine:

Sci2sci is building an electronic lab notebook and a publishing platform in one interface. This will allow to store all experimental data and metadata in one place, and quickly release it in public access with one click.

In a nutshell, sci2sci offers full stack data publishing - from the experiment planning through raw data acquisition and analysis to the final research report - all in a single platform, with a number of benefits that cannot be offered by a current journal pdf manuscript:
{| class="wikitable"
|+
!PDF journal publication:
!sci2sci publishing:
|-
|Data is not standardized, so it’s hard to analyze, reproduce and compare
|Standardization and interoperability of the data due to pre-made experimental templates
|-
|Text and images are not AI-native: parsing and knowledge extraction are difficult
|ML-ready design of research papers
|-
|Static figures and graphs
|Dynamic and interactive tools for data visualization
|-
|No chance of statistical reanalysis
|Possibility for reanalysis as the “source code” of the experiments is always available
|-
|Pre-publication peer review takes 90 days on average;
Only 2-3 experts participate in review;

Updates to the study after publishing are almost impossible
|Open source-like collaboration flow
|-
|Contribution tracking is as obscure as this description of it
|Digital CVs for researchers showcasing their expertise
|-
|It takes days to prepare and publish data
|One-click data sharing
|-
|Data reuse is not possible
|Data reuse is encouraged
|}
Sci2sci is aiming at creating software that will make principles of FAIR (Findable, Accessible, Interoperable, Reusable) data a default in scientists’ daily routine. Sci2sci mission is to make research data openly available for reuse and collaboration by academic researchers, the industry and the public.

The larger vision and inspiration behind the project is described in this [https://medium.com/@leery.rowdy/notes-on-web3-science-from-analogue-to-ai-powered-digital-science-85aef529f2a article].

Sci2sci

2022-11-12T10:59:54Z

An libertine: Description of sci2sci project was added

At sci2sci, we are building an electronic lab notebook and a publishing platform in one interface. This will allow to store all experimental data and metadata in one place, and quickly release it in public access with one click.

In a nutshell, we offer full stack data publishing - from the experiment planning through raw data acquisition and analysis to the final research report - all in a single platform, with a number of benefits that cannot be offered by a current journal pdf manuscript:
{| class="wikitable"
|+
!PDF journal publication:
!sci2sci publishing:
|-
|Data is not standardized, so it’s hard to analyze, reproduce and compare
|Standardization and interoperability of the data due to pre-made experimental templates
|-
|Text and images are not AI-native: parsing and knowledge extraction are difficult
|ML-ready design of research papers
|-
|Static figures and graphs
|Dynamic and interactive tools for data visualization
|-
|No chance of statistical reanalysis
|Possibility for reanalysis as the “source code” of the experiments is always available
|-
|Pre-publication peer review takes 90 days on average;
Only 2-3 experts participate in review;

Updates to the study after publishing are almost impossible
|Open source-like collaboration flow
|-
|Contribution tracking is as obscure as this description of it
|Digital CVs for researchers showcasing their expertise
|-
|It takes days to prepare and publish data
|One-click data sharing
|-
|Data reuse is not possible
|Data reuse is encouraged
|}
We aim at creating software that will make principles of FAIR (Findable, Accessible, Interoperable, Reusable) data a default in scientists’ daily routine. Our mission is to make research data openly available for reuse and collaboration by academic researchers, the industry and the public.
Our larger vision and inspiration is described in this [https://medium.com/@leery.rowdy/notes-on-web3-science-from-analogue-to-ai-powered-digital-science-85aef529f2a article].