BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation.This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

Data fusion

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

/pdf/answering-queries-using-views-a-survey-4aug5icc6d.pdf

Answering queries using views: A survey

We witness a rapid increase in the number of structured information sources that are available online, especially on the WWW. These sources include commercial databases on product information, stock market information, real estate, automobiles, and entertainment. We would like to use the data stored in these databases to answer complex queries that go beyond keyword searches. We face the following challenges: (1) Several information sources store interrelated data, and any query-answering system must understand the relationships between their contents. (2) Many sources are not full-featured database systems and can answer only a small set of queries over their data (for example, forms on the WWW restrict the set of queries one can (3) Since the number of sources is very large, effective techniques are needed to prune the set of information sources accessed to answer a query. (4) The details of interacting with each source vary greatly. We describe the Information Manifold, an implemented system that provides uniform access to a heterogeneous collection of more than 100 information sources, many of them on the WWW. IM tackles the above problems by providing a mechanism to describe declaratively the contents and query capabilities of available information sources. There is a clean separation between the declarative source description and the actual details of interacting with an information source. We describe algorithms that use the source descriptions to prune effciently the set of information sources for a given query and practical algorithms to generate executable query plans. The query plans we generate can inolve querying several information sources and combining their answers. We also present experimental studies that indicate that the architecture and algorithms used in the Information Manifold scale up well to several hundred information sources

https://www.seas.upenn.edu/~zives/03s/cis650/lro96.PDF

Querying Heterogeneous Information Sources Using Source Descriptions

The paper proposes a key constraint language for XML and investigates its associated decision problems. The language is defined in terms of regular path expressions extended with downward and upward wildcards, which can not only move down XML document trees, but also upwards. In a uniform syntax it is capable of expressing both absolute keys and relative keys, which are important to hierarchically structured data. In addition, keys defined in the language can be reasoned about efficiently. The paper provides a sound and complete set of inference rules and a cubic time algorithm for determining implication of the keys.

Keys with Upward Wildcards for XML

Access to large numbers of data sources introduces new problems for users of heterogeneous distributed databases. End users and application programmers must deal with unavailable data sources. Database administrators must deal with incorporating new sources into the model. Database implementers must deal with the translation of queries between query languages and schemas. The Distributed Information Search COmponent (Disco) addresses these problems. Query processing semantics are developed to process queries over data sources which do not return answers. Data modeling techniques manage connections to data sources. The component interface to data sources flexibly handles different query languages and translates queries. This paper describes (a) the distributed mediator architecture of Disco, (b) its query processing semantics, (C) the data model and its modeling of data source connections, and (d) the interface to underlying data sources.

https://hal.inria.fr/docs/00/07/39/86/PDF/RR-2704.pdf

Scaling heterogeneous databases and the design of Disco

Accessing many data sources aggravates problems for users of heterogeneous distributed databases. Database administrators must deal with fragile mediators, that is, mediators with schemas and views that must be significantly changed to incorporate a new data source. When implementing translators of queries from mediators to data sources, database implementers must deal with data sources that do not support all the functionality required by mediators. Application programmers must deal with graceless failures for unavailable data sources. Queries simply return failure and no further information when data sources are unavailable for query processing. The Distributed Information Search COmponent (Disco) addresses these problems. Data modeling techniques manage the connections to data sources, and sources can be added transparently to the users and applications. The interface between mediators and data sources flexibly handles different query languages and different data source functionality. Query rewriting and optimization techniques rewrite queries so they are efficiently evaluated by sources. Query processing and evaluation semantics are developed to process queries over unavailable data sources. In this article, we describe: 1) the distributed mediator architecture of Disco; 2) the data model and its modeling of data source connections; 3) the interface to underlying data sources and the query rewriting process; and 4) query processing semantics. We describe several advantages of our system.

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Scaling access to heterogeneous data sources with DISCO

Large scale disasters bring together a diversity of organizations and produce massive amounts of heterogeneous data that must be managed by these organizations. The lack of effective ICT solutions can lead to a lack of coordination and chaos among these organizations, as they track victims' needs and respond to the disaster. The result can be delayed or ineffective response, the potential wastage of pledged support, imbalances in aid distribution, and a lack of transparency. ICT solutions to manage disasters can potentially improve efficiency and effectiveness. Sahana is a free and open source software (FOSS) application that aims to be a comprehensive solution for information management in relief operations, recovery and rehabilitation. This paper addresses the alignment between FOSS development and humanitarian applications, it then describes the anatomy of the Sahana system. We follow up with a case study of Sahana deployment and lessons learned.

Sahana: Overview of a Disaster Management System

In this paper, we focus on finding complex annotation patterns representing novel and interesting hypotheses from gene annotation data We define a generalization of the densest subgraph problem by adding an additional distance restriction (defined by a separate metric) to the nodes of the subgraph We show that while this generalization makes the problem NP-hard for arbitrary metrics, when the metric comes from the distance metric of a tree, or an interval graph, the problem can be solved optimally in polynomial time We also show that the densest subgraph problem with a specified subset of vertices that have to be included in the solution can be solved optimally in polynomial time In addition, we consider other extensions when not just one solution needs to be found, but we wish to list all subgraphs of almost maximum density as well We apply this method to a dataset of genes and their annotations obtained from The Arabidopsis Information Resource (TAIR) A user evaluation confirms that the patterns found in the distance restricted densest subgraph for a dataset of photomorphogenesis genes are indeed validated in the literature; a control dataset validates that these are not random patterns Interestingly, the complex annotation patterns potentially lead to new and as yet unknown hypotheses We perform experiments to determine the properties of the dense subgraphs, as we vary parameters, including the number of genes and the distance.

/pdf/dense-subgraphs-with-restrictions-and-applications-to-gene-1ldpa03um7.pdf

Dense subgraphs with restrictions and applications to gene annotation graphs

Topic detection with large and noisy data collections such as social media must address both scalability and accuracy challenges. KeyGraph is an efficient method that improves on current solutions by considering keyword cooccurrence. We show that KeyGraph has similar accuracy when compared to state-of-the-art approaches on small, well-annotated collections, and it can successfully filter irrelevant documents and identify events in large and noisy social media collections. An extensive evaluation using Amazon’s Mechanical Turk demonstrated the increased accuracy and high precision of KeyGraph, as well as superior runtime performance compared to other solutions.

Louiqa Raschid

Papers

Scaling heterogeneous databases and the design of Disco

Scaling access to heterogeneous data sources with DISCO

Sahana: Overview of a Disaster Management System

Dense subgraphs with restrictions and applications to gene annotation graphs

A Graph Analytical Approach for Topic Detection