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- Developing a metadata application profile for the daily hire labourPublication . Sen, Sangeeta; Raza, Nishat; Dutta, Animesh; Malta, Mariana Curado; Baptista, Ana AliceEMPOWER SSE is a Fundação para a Ciência e Tecnologia (FCT, Portugal) and Department of Science & Technology (DST, India), financed research project that aims to use the Linked Open Data Framework to empower the Social and Solidarity Economy (SSE) Agents. It is a collaborative project between India and Portugal that is focused on defining a Semantic Web framework to consolidate players of the informal sector, enabling a paradigm shift. The Indian economy can be categorized into two sectors: formal and informal. The informal sector economy differs from the formal as it is an unorganized sector and comprised of economic activities that are not covered by formal arrangements such as taxation, labor protections, minimum wage regulations, unemployment benefits, or documentation. The major economy in India depends on the skilled labor of this informal sector such e.g. daily labor, farmers, electricians, food production, and small-scale industries (Kalyani, 2016). The informal sector is mainly made of skilled people that follow their family job traditions, sometimes they are not even formally trained. This sector struggles with the lack of information, data sharing needs and interoperability issues across systems and organizational boundaries. In fact, this sector does not have any visibility to the society not having the possibility to do business as most of the agents of this sector do not reach the end of the chain. This blocks them from getting proper exposure and a better livelihood.
- State-of-the-art approaches for meta-knowledge assertion in the web of dataPublication . Sen, Sangeeta; Malta, Mariana Curado; Dutta, Biswanath; Dutta, AnimeshThe integration of meta-knowledge on the Web of data is essential to support trustworthiness. This is in fact an issue because of the enormous amount of data that exists on the Web of Data. Meta-knowledge describes how the data is generated, manipulated, and disseminated. In the last few years, several approaches have been proposed for tracing and representing meta-knowledge efficiently on a statement or on a set of statements in the Semantic Web. The approaches differ significantly; for instance, in terms of modelling patterns, the number of statements generation, redundancy of the resources, query length, or query response time. This article reports a systematic review of the various approaches of the four dimensions (namely time, trust, fuzzy, and provenance) to provide an overview of the meta-knowledge assertion techniques in the field of the Semantic Web. Some experiments are conducted to analyze the actual performance of the approaches of meta-knowledge assertion considering the provenance dimension. These experiments are based on specific parameters such as graph size, number of statements generation, redundancy, query length, and query response time. All the experiments are done with real-world datasets. The semantics of the different approaches are compared to analyze the methodology of the approaches. Our study and experiments highlight the advantages and limitations of the approaches in terms of the parameters mentioned above.