As a result of the project, the following two tools have been developed:
SiSOB workbench: This is an analysis tool that has been designed as a knowledge worker’s workbench. Its user interface allows the user to combine different components for data conversion, analysis and visual representation. More information.
Download source code
Download user manual
Access workbench
SiSOB data extractor: This system can be used for information crawling and extraction. It can be feed with either bibliographic data sources, such as Scopus or Web of Knowledge, or crawling information directly from the web through search engines. Its main goal is to extract curricular items from a set of researchers from their full names and expertise area. More information.
Download source code
Access data extractor
SISOB Data Exchange Format:
Download API
SISOB Visualization Tool:
Download visualization tool
The project LeMo (monitoring of learning processes on personalizing and non-personalizing learning management systems) aims to develop a prototype of a web based Learning Analytics application, which provides detailed information on user navigational patterns within learning management systems and identifies needs for enhancement and revision of the learning offer. Target groups are content-provider, teacher and researcher. The prototype will support personalizing learning management systems that require a login for access as well as online encyclopedias that are non-personalizing, where neither login nor registration is needed to access content. In this project three Berlin universities cooperate with four partners in the elearning sector.
M-Lab provides the largest collection of open Internet performance data on the planet. As a consortium of research, industry, and public-interest partners, M-Lab is dedicated to providing an ecosystem for the open, verifiable measurement of global network performance. Real science requires verifiable processes, and M-Lab welcomes scientific collaboration and scrutiny. This is why all of the data collected by M-Lab’s global measurement platform are made openly available, and all of the measurement tools hosted by M-Lab are open source. Anyone with time and skill can review and improve the underlying methodologies and assumptions on which M-Lab’s platform, tools, and data rely. Transparency and review are key to good science, and good science is key to good measurement.