Immunization saves millions of lives against vaccine-preventable diseases. Yet, 24 million children born every year do not receive proper immunization during their first year. UNICEF and WHO have emphasized the need to strengthen the immunization surveillance and monitoring in developing countries to reduce childhood deaths. In this regard, we present a software application called Jeev to track the vaccination coverage of children in rural communities. Jeev synergistically combines the power of smartphones and the ubiquity of cellular infrastructure, QR codes, and national identification cards. We present the design of Jeev and highlight its unique features along with a detailed evaluation of its performance and power consumption using the National Immunization Survey datasets. We are in discussion with a non-profit organization in Haiti to pilot test Jeev in order to study its effectiveness and identify socio-cultural issues that may arise in a large-scale deployment.

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We propose a new way of indexing a large database of small and medium-sized graphs and processing exact subgraph matching (or subgraph isomorphism) and approximate (full) graph matching queries. Rather than decomposing a graph into smaller units (e.g., paths, trees, graphs) for indexing purposes, we represent each graph in the database by its graph signature, which is essentially a multiset. We construct a disk-based index on all the signatures via bulk loading. During query processing, a query graph is also mapped into its signature, and this signature is searched using the index by performing multiset operations. To improve the precision of exact subgraph matching, we develop a new scheme using the concept of line graphs. Through extensive evaluation on real and synthetic graph datasets, we demonstrate that our approach provides a scalable and efficient disk-based solution for a large database of small and medium-sized graphs.

In this paper, we address the problem of fast processing of SPARQL queries on a large RDF dataset, where the RDF statements are quadruples (or quads). Quads can capture provenance or other relevant information about facts. This is especially powerful in modeling knowledge graphs, which are becoming increasingly important on the Web to provide high quality search results to users. We propose a new approach called RIQ that employs a decrease-and-conquer strategy for fast SPARQL query processing. Rather than indexing the entire RDF dataset, RIQ identifies groups of similar RDF graphs and creates indexes on each group separately. It employs a new vector representation for RDF graphs and locality sensitive hashing to construct the groups efficiently. It constructs a novel filtering index on the groups and compactly represents the index as a combination of Bloom and Counting Bloom Filters. During query processing, RIQ employs a streamlined approach. It constructs a query plan for a SPARQL query (containing one or more graph patterns), searches the filtering index to quickly identify candidate groups that may contain matches for the query, and rewrites the original query to produce an optimized query for each candidate. The optimized queries are then executed using an existing SPARQL processor that supports quads to produce the final results. We conducted a comprehensive evaluation of RIQ using a real and synthetic dataset, each containing about 1.4 billion quads. Our results show that RIQ can outperform its competitors designed to support named graph queries on RDF quads (e.g., Jena TDB and Virtuoso) for a variety of queries.

Immunization saves millions of lives against vaccine-preventable diseases. Yet, 24 million children born every year do not receive proper immunization during their first year. UNICEF and WHO have emphasized the need to strengthen the immunization surveillance and monitoring in developing countries to reduce childhood deaths. In this regard, we present a software application called Jeev to track the vaccination coverage of children in rural communities. Jeev synergistically combines the power of smartphones and the ubiquity of cellular infrastructure, QR codes, and national identification cards. We present the design of Jeev and highlight its unique features along with a preliminary evaluation of its performance. We plan to pilot test Jeev in a rural population to study its effectiveness and identify socio-cultural issues that may arise in a large-scale deployment.