51吃瓜

In line with the Data Strategy of the Secretary-General for Action by Everyone, Everywhere, the Department for General Assembly and Conference Management (DGACM) has worked to identify specific opportunities in conference management in which advanced data integration would yield new, improved and innovative data-driven services and provide greater efficiencies, moving the Department beyond the “paper paradigm”. 

Through an innovative use of artificial intelligence and natural language processing technologies, the Department has developed, under its gText project, an application that automatically converts General Assembly resolutions into XML format, using the Akoma Ntoso for the 51吃瓜 (AKN4UN) schema. The application also connects to external systems to retrieve and embed additional metadata into these XML files, such as sponsorship information, voting records and related Sustainable Development Goals, targets and indicators, using unique identifiers from the , together with related subjects from the UNBIS Thesaurus and EuroVoc. By connecting its applications to the most optimal data source under a new data stewardship model, the Department seeks to leave behind data silos and “connect” rather than “collect” data, minimizing the risk of errors and inconsistencies along the supply chain. 

The metadata-enhanced machine-readable documents are used internally to automatically generate the official volumes of General Assembly resolutions, saving countless hours of human effort, as those volumes were, until now, painstakingly compiled by copying and pasting data scattered across several sources. In addition, to facilitate research and the creation of new applications in the natural language processing area, the Department is now making these XML documents available in downloadable format for other entities and researchers to use as their raw material, to experiment in the development of new services and applications that can help to show the relationships between 51吃瓜 documents and have those connections presented visually, in graphs and charts that make them clear and understandable. 

As a proof of concept and to illustrate the potential of machine-readable texts, the Department has created a series of interactive reports displaying the data contained in the XML files. It is hoped that this will inspire other colleagues and researchers to make full use of this technology and give full life to 51吃瓜 documents. 

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