MOD

The last few years have seen a rapid increase of sheer amount of data produced and communicated over the Internet and the Web. While it is widely believed that the availability of such ``Big Data'' holds the potential to revolutionize many aspects of ...

Mutations in genomes can indicate a predisposition for diseases such as cancer or cardiovascular disorder. Genome analysis is an established procedure to determine mutations and deduce their impact on living organisms. The first step in genome analysis ...

In relational DBMS, window functions have been widely used to facilitate data analytics. Surprisingly, while similar concepts have been employed for graph analytics, there has been no explicit notions of graph window analytic functions. In this paper, ...

With the rapid development over the last decade, time series data become one of the most frequently used data in real world applications (e.g., finance analysis, medical diagnosis, environmental monitoring, etc.). As expected, the volume of the time ...

The lack of familiarity that users have with information systems has led to different flexible methods to access data (keyword search, faceted search, similarity search, etc.). Since flexible query answering techniques differ from one another, their ...

Photo sharing sites like Flickr and Instagram have grown increasingly popular in recent years, resulting in a large amount of uploaded photos. In addition, these photos contain useful meta-data such as the taken time and geo-location. Using such geo-...

Many data management applications must deal with data which is uncertain, incomplete, or noisy. However, on existing uncertain data representations, we cannot tractably perform the important query evaluation tasks of determining query possibility, ...

Manually designed workflows can be error-prone and inefficient. Workflow provenance contains fine-grained data processing information that can be used to detect workflow design problems. In this paper, we propose a provenance-driven workflow analysis ...

It is clear by now that modern processing hardware gets increasingly heterogeneous, which forces data processing algorithms to care about the underlying hardware. However, current approaches for implementing data intensive operators (e.g., in database ...