Information sharing
From Wikipedia, the free encyclopedia
The term "information sharing" gained popularity as a result of the 9/11 Commission Hearings and its report of the United States government's lack of response to information known about the planned terrorist attack on the New York City World Trade Center prior to the event. The resulting commission testimony led to the enactment of several executive orders by President Bush that mandated agencies implement policies to "share information" across organizational boundaries.
The term "information sharing" in the information technology lexicon has a long history. Traditional information sharing referred to one-to-one exchanges of data between a sender and receiver. These information exhanges are implemented via dozens of open and proprietary protocols, message and file formats. Electronic data interchange ("EDI") is a successful implementation of commercial data exchanges that began in the late 1970s and remains in use today.
Recent initiatives to standardize information sharing protocols include extensible markup language ("XML"), simple object access protocol ("SOAP"), and web services description language ("WSDL").
From the point of view of a computer scientist, the four primary information sharing design patterns are sharing information one-to-one, one-to-many, many-to-many, and many-to-one. Technologies to meet all four of these design patterns are evolving and include blogs, wikis, really simple syndication, tagging, and chat.
One example of United States government's attempt to implement one of these design patterns (one to one) is the National Information Exchange Model (NIEM). [1] Unfortunately, one-to-one exchange models fall short of supporting all of the required design patterns needed to fully implement data exploitation technology.
As technology advances, information sharing platforms will provide controlled vocabularies, data harmonization, data stewardship policies and guidelines, standards for uniform data as they relate to privacy, security, and data quality.
