Accessing online services requires users to choose from a growing set of identity providers, including social logins (e.g., Google), national eID providers (e.g., CIE), and recently, under the revised electronic Identification, Authentication and Trust Services regulation (eIDAS 2.0), “Log in with Digital Wallet”. In self sovereign identity settings, this choice worsens the “NASCAR problem”: users must select among many wallets, while relying parties face significant integration and maintenance costs. The W3C Digital Credentials API shifts selection from the wallet to the specific credential required by the relying parties, enabling a simpler and more interoperable user journey. To achieve this, the API mediates requests and responses through both web and operating system interfaces. Yet this multi-party, cross layer architecture, which spans user agents, operating systems, and wallets, expands the attack surface. This paper presents a preliminary threat model for the Digital Credentials API to identify and mitigate potential threats, thereby supporting a secure, privacy preserving, and interoperable self sovereign identity ecosystem.
Since the 1980's, there has existed a heated argument in the circle of higher education in China regarding whether higher education should be oriented for the market or whether it should face the market. It has remained an issue of major concern. The purpose of this paper is to provide a discussion of the merits and demerits of the two different views.
Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology. These tasks assess statistical data and are implemented in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods for evaluating structured non-relational information on COVID-19 in Wikidata, and its applicability in collaborative ontologies and knowledge graphs more broadly. We show the advantages and limitations of our proposed approach by comparing it to the features of other methods for the validation of linked web data as revealed by previous research.
Subset of Wikidata obtained using this Shape Expression: https://github.com/kg-subsetting/datasets-biohackathon2022/blob/main/GeneWiki/GeneWiki.shex And the wdsub tool version 0.0.28: https://github.com/weso/wdsub The input dump is: wikidata-20180115-all And the dumpformat is JSON
