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About T2C2

The Timely and Trustworthy Curating and Coordinating Data Framework (T2C2) project aims to dramatically reduce the materials-to-device process, which can currently span 20 years. Through the DIBBs program, funded by the National Science Foundation CISE Directorate and their Advanced Cyber-Infrastructure Division (ACI), T2C2 will develop a new framework and system that focuses on the potential of capturing, curating, correlating and coordinating materials-to-devices digital data in a real-time and trusted manner before fully archiving and publishing the data for wide access and sharing. The software developed in this project is useful throughout the materials science and device fabrication fields, by automatically collecting, archiving, and providing collected information on all phases of materials and device fabrication development.


4CeeD

The project develops the Timely and Trusted Curation and Coordination (T2C2) Data Framework, consisting of two data blocks:

1)The  4CeeD Curator, providing real-time acquisition and curation of digital data from selected materials-making / characterization and device-fabrication instruments in the collaborative research units at the university, the Material Research Lab (MRL) and the Micro-and-Nanotechnology Lab (MNTL) , and
2) The 4CeeD Coordinator, where collected data are filtered, correlations among data and dependency relations are identified, and the results are connected to other data processing capabilities. The goal of the T2C2 framework is to enable reduction of the development time and cost of materials-making /characterization to device-making processes.

Through open-source software licenses and training programs, the project impacts material science, device fabrication and other fields within the university, and other interdisciplinary research institutions and their materials design and manufacturing processes. Through courses, tutorials, workshops, and outreach, the project develops interdisciplinary scientists, teaches the next generation of students, and informs broader audiences about the potential of timely and trusted data collection, curation, spatio-temporal analytics, and correlations between material-making/characterization and device-fabrication processes.

4CeeD Product Page

Latest Updates: Jupyter Notebook Integration, Mobile friendly design, updated visualization/dashboards, LDAP login integration, metadata templates.

This research is funded by the National Science Foundation, NSF ACI 1443013, project title “CIF21 DIBBs: T2-C2: Timely and Trusted Curator and Coordinator Data Building Blocks.”  Any results and opinions are our own and do not represent views of National Science Foundation.


Bracelet

The 4CeeD tool can only function when the instrument’s operating system (OS) is Windows 7 or higher, allowing instruments to have the computational capability and network speed to be part of a distributed cloud platform, and to have all the necessary security patches to be connected to the campus network. However, more than half of the major scientific instruments on our campus and their software tools run Windows XP, Windows NT, Windows 2000, and Windows 3.11, and thus are set offline because they cannot operate at the network speed of a powerful cloud and are not patched with the latest security patches.

BRACELET: Robust Cloudlet Infrastructure for Scientific Instruments’ Lifetime Connectivity

This research was funded by the National Science Foundation (award number 1659293). The opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of the National Science Foundation.


Senselet

The cloud service 4Ceed and the edge device BRACELET accelerates the process of making scientific discoveries by providing researchers with the convenience to upload, examine, and process their experimental data (e.g., microscope images) and metadata (e.g., microscope settings). For researchers, an equally important information towards correct scientific experimentation, besides instrument raw data and metadata, is  sensory data around the instruments when experiments are conducted. For example, the ability to capture and control laboratory environmental sensory information such as temperature, humidity, vibration is crucial for nano-fabrication. In some laboratories we have few stand-alone sensors to collect humidity data. However, it is very time consuming to manually collect and correlate those parameters with our fabrication process.

SENSELET: a Sensory Network infrastructure for Scientific Lab Environments

This research was funded by the National Science Foundation (award number 1827126). The opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of the National Science Foundation.