BeeSpace Software

1
BeeSpace Software

• Plans, Design, and Development

2
Outline

• Goals
• Context
• Approach
• Software Process
• Functionality
• Design
• Implementation Details
• Future Prospects

3
Project Goals Parameters

• This project will analyze social behavior using
  Apis Mellifera as the model organism.
• Goal support research and analysis of the
  Western honey bee.
• Using biology research (that) will generate a
  unique database of gene expressions and
  microarray experiments (that will) utilize the
  recently sequenced genome, supported by
  state-of-the-art statistics.
• Goal support application of biological methods
  and techniques for exploratory analysis.
• And using informatics research (that) will
  develop an interactive environment to analyze all
  information sources relevant to bee social
  behavior.
• Goal support application of language processing
  methods for exploratory analysis.
• The BeeSpace environment will enable users to
  navigate a uniform space of diverse databases and
  literature sources for hypothesis development and
  testing. (Ref http//www.beespace.uiuc.edu/)
• Goal support dual analysis methodologies via an
  integrated analysis environment.
• Parameter 5 years to complete project, includes
  research, development, deployment, outreach and
  documentation.
• Parameter annual milestones and workshops
  expected.

4
Context

• There are voluminous amounts of biomedical and
  genomic literature containing valuable knowledge
  and research results.
• Implication Too much for human processing and
  not in a machine-ready format for reasoning based
  systems.
• There exist novel language processing techniques
  that have been primarily applied in niche
  applications.
• Implication Emerging technologies (NLP, TM,
  etc.) can provide backbone for strategic
  solution, but their risks must be mediated thru
  controlled developmental cycles.
• There exist numerous, but currently isolated,
  tools for data processing of bioinformatics.
• Implication Opportunities exist for
  interoperability with disparate systems, but
  success hinges on standardization.
• The web is seeing an increase in smaller, highly
  focused communities-of-interest.
• Implication Opportunities exist for supporting
  the creation and management of localized
  knowledge-spaces.

5
Context Related Tools Projects

• 3rd Millennium Inc. development of an
  integration framework for genomic, gene
  expression, and interaction data (protein-protein
  well as protein-DNA) from multiple sources and
  model organisms that can enable the display of
  the relationships between biochemical objects
  into the context of biological pathways and
  networks.
• iHOP Information Hyperlinked Over Proteins
  supports lookup and summarization of
  genes/proteins. In general more than 90 of all
  active relations between proteins in the
  literature are expressed syntactically as
  protein verb protein. Ref.
• IntAct Database IntAct provides a freely
  available, open source database system and
  analysis tools for protein interaction data. All
  interactions are derived from literature curation
  or direct user submissions and are freely
  available.
• Entrez eUtils A web services (SOAP) interface
  for programmatically querying and interacting
  with NCBI databases.

6
Software Process

• System Development Life Cycle (SDLC)
• Identify project goals and critical success
  factors.
• Investigate current methodologies and tools that
  have functional or domain overlap with project
  objectives.
• Research the applicability of novel analysis
  techniques for extracting deeply embedded and
  stratified knowledge structures.
• Build an integrated software suite that will
  allow for interactive analysis and augmentation
  of rich data sets.
• Test and deploy software to focused user groups.
• Document and publish research results.
• Re-iterate above process for continuous quality
  improvement.

7
Functionality

• Should be web-based system supporting lightweight
  GUI components and having minimal end-user
  requirements.
• Should accommodate user-directed
  query-by-navigation (QBN) of concept space.
• Should extract and normalize concepts as
  equivalence classes of things with highly
  similar meaning. Should recognize and denote
  entities.
• Should allow user to drill-down, drill-up and
  drill-across concept space. E.g.
  text-to-concept, concept-to-concept,
  concept-to-theme, and the reverse directions as
  well.
• Should allow user to perform encyclopedia-style
  lookup of entities.
• Should provide hooks for tie-in to 3rd party
  bioinformatics tools.

8
Design Principles

• Maintainability
• Portability
• Extensible
• Efficiency
• Organized
• Interoperability
• Configurability
• Ease-of-use
• Trusted
• Quality without a Name
• References Code Complete, 2nd ed.,
  Pattern-Oriented Software Architecture, volume
  1.

9
Design Use Case Diagram
10
Design - Component Diagram
11
Design - Deployment Scenarios
12
Design Class Diagram
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Implementation Details

• The current system is being constructed as
  follows
• The (v1.0) application is being developed as a
  web-based application.
• Design Decision The interface is built on top of
  lightweight technologies (e.g. HTML, DHTML
  JavaScript). Typical web-app challenges, such as
  sessioning and security, need to be addressed.
• The output of the data processing pipeline is a
  set of indices and annotated data files that the
  client application depends on.
• Design Decision There is a clear
  separation-of-concerns between the server-side
  processing and the client-side interface. XML is
  being fully utilized to as a data interchange
  format between software components.
• The pipeline is composed of independent software
  components, but these components need to be
  inter-connected.
• Design Decision Components are called as
  executables with defined interfaces.
• Some components need to be able to store their
  data aggregations persistently (and other
  components may need access to this data).
• Design Decision Currently each component handles
  this problem independently. Better, long term
  solution is to extract out this concern and
  address it globally for example, using ORDBMS.

14
Future Implementation Details

• Support both a web interface (HTML, CSS, DHTML,
  JavaScript) and a full-blown GUI interface (Java
  Web Start app).
• Consistent Java implementation for portability,
  maintainability, RAD, etc.
• Incorporate a DBMS for consistent handling of
  persistent storage.
• Library extensions for communication between
  distributed, heterogeneous applications (perhaps
  KIF).
• Optimized data processing and communication.

15
Climbing the Pyramid
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Future Prospects

• Generalize the system so that it is NOT
  domain-specific and can be readily applied to
  other domains.
• Allow for persistent sessioning and sharing of
  sharing of knowledge-spaces amongst
  communities-of-interest.
• Support a visual query system (VQS) interface
  and/or a query-by-example (QBE) interface.
• Support all kinds of hypothesis generation
  deduction, abduction induction.
• Support personalized annotations. (What
  constitutes a good KR structure clarity,
  logic, expressive?).
• Smooth the integration between the BeeSpace
  Navigator and the myriad number of web-based
  tools.
• Support n-ary, semantically rich relations as
  opposed to just dyadic.

17
Future BeeSpace Components
18
Snake Space?