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CHAPTER FIVE
The Future
If the future of imaging had to be expressed in one word, that word would be integration. For imaging, integration has several different connotations. There is integration within a department (e.g., the claims processing department or the clerk’s office) that combines imaging with data processing, word processing, communications, and other functions performed by computers at a given location as noted earlier in this report. There is integration throughout an enterprise (e.g., a company or court) that combines these functions as performed on a departmental computer with functions performed on other computers in the organization. And there is integration that goes beyond the enterprise and embraces many organizations or enterprises.
Now consider the future from another perspective. Assume you are a court user who has installed an imaging system. Aside from imaging itself (and excluding the JEDDI data exchange emerging technology discussed earlier in this report), what changes might you encounter? Each office now has access to imaged case records and can enter pleadings and other information electronically using the case processing and imaging systems. For courts that cover large geographic areas, this could lead to more branch courthouses and work from judges’ offices not located in the courthouse. Similarly, attorneys could file pleadings from their offices using fax machines, remote scanners, and PCs. Official signed documents could be assembled and disseminated electronically by integrated imaging, word processing, and case processing systems without physically routing the documents to the judge and other participants. Financial transactions involving invoices, vouchers, and credit cards could be handled electronically. Appeals could be made with the electronic transfer of trial court records, thereby avoiding the transfer of voluminous records from the trial court to the appellate court. These are only some of the possibilities. They have obvious implications regarding security, authenticity of signatures, definition of official records, and other issues. Since they may be in your future if you use imaging, you should be prepared.
As you can see from these examples, integration of technologies will play a major role in the future. The integration should go beyond simply having these technologies on the same computers and networks (see Figure 6). It should encompass the time integration of applications, so that parts of data from data processing systems, parts of word processing documents, parts of imaged documents--perhaps even parts of voice messages --can be combined into the same document or screen presentation.
How will integration manifest itself in terms of the imaging functions discussed throughout this report? We can see this best by looking at open architecture, client/server and desktop computing, workflow, OCR, text retrieval, and compound documents relative to the future of imaging.
Open architecture is a hot topic throughout today’s computer industry. It means equipment, software, and communications from Vendor X must work with equipment, software, and communications from Vendor Y because an organization may be able to get the best combination of price and performance by using some items from Vendor X and other items from Vendor Y. (This assumes both vendors are major companies with products that conform to computer industry standards.) It also means the organization’s equipment, software, and communications would work with those of another organization that uses the industry-standard products of Vendor Z. In the old days, organizations tended to buy proprietary products from a single vendor, and these products would work only with other products from that same vendor. That is a rapidly vanishing practice.
In imaging, open architecture means (1) the imaging system can receive images from and send them to standard networks and computers and (2) the networks and computers can process the images. In each case, a language--called a protocol--exists to make sure both sender and receiver know what is being sent, how long the transmission is, where it is going, and other transmission characteristics. Standard networks and computers use standard protocols and network setups, which are the keys to getting an image to its destination. Once at the destination, in order for the receiving computer to be able to process the image, the image must be in a standard format that can be understood by this computer.
Clearly, little integration of the multiple-vendor installations that are becoming prevalent today--in both imaging and computers in general--could be easily accomplished without open architecture.
Figure 6: Integration of Imaging and Case Management System Components
V.B. Client/Server and Desktop Computing
Until recently, when a new system was contemplated, the instinctive reaction was to put it on the mainframe computer. Organizations lived by their massive mainframe computers. Those days are gone. Computing is getting smaller. Much of it is moving from the mainframe to the user departments and desktops. PCs and LANs make this possible. Powerful server PCs control LANs and coordinate network functions such as communications, database management, and printouts. Other PCs--called client PCs--are devices in the LAN that enable individuals to use the network’s functions and to perform individual user applications, such as case processing, and desktop functions, such as word processing and spreadsheets. Client/server computing integrates the server and client functions so that each user can perform work on his or her desktop using graphical interfaces (as in windows) without concern about which computer contains the programs and data needed for a particular user application and network function. Stand-alone PCs perform desktop functions independently of a network. Whereas in the past there was only the mainframe, now there is a triumvirate consisting of the mainframe, client/server networks, and stand-alone PCs.
Organizations are moving toward a more balanced processing approach in which some systems belong on the mainframe, some belong on networks, and some belong on PCs. The same will happen to imaging as it becomes more fully integrated into the organizations’ other computer functions.
Here is a key element in the downsizing movement toward many smaller computers instead of one huge computer: the organization must decide which functions belong on each type of computer. Just as an instinctive gravitation toward the mainframe usually is inappropriate, so too is an unthinking bias toward client/server networks. This applies to computing in general and imaging as it becomes one of the functions offered, in an integrated fashion, on client/server networks and desktops.
The fact that the mainframe still should be part of any analysis of computer applicability does not reduce the profound significance and impact of client/server and desktop computing. The potential benefits are enormous. In imaging, think of the benefits to be gained from being able to retrieve and work on text from all types of documents, form compound documents, and define and use document workflows from your own PC through the LAN. Since these imaging capabilities would be represented by icons you could select, just as you now select word processing and spreadsheets, imaging would be fully integrated with the other client/server and desktop functions.
In addition to potentially improving functionality, appropriate downsizing of imaging to the desktop probably would reduce costs just as it seems to be reducing the costs of computing in general. (While the initial costs of client/server computing usually are less than mainframe computing, client/server technology is too new to assess its long-term costs.) One of the defining characteristics of imaging has been its cost. Downsizing has the potential to lessen this obstacle.
But note that imaging downsizing must be appropriate. Analogous to computers in general, it may be some time before client/server and desktop imaging will be sufficiently powerful and versatile to accommodate the massive organization-wide imaging functions. They should remain on mainframe computers in the meantime.
As described earlier, automated workflow routes imaged documents around to workstations for processing (see Figure 7). There are two levels of workflows: organizational and workgroup. An organization may be the entire enterprise (e.g., a company or court) or a department within the enterprise (e.g., the claims processing department or clerk’s office). A workgroup connotes a smaller group of workers doing the same type of work (e.g., the judge, law clerks, and secretary in a judge’s office).
The organizational workflow in a department is most prevalent today, and it usually is processed on a mainframe computer. Use of workgroup workflows will grow as the capability becomes more common in client/server networks and desktop PCs.
Mainframe automated workflow products will be more widely used as their capabilities and flexibility are improved to (1) replicate the actual processes through which documents are routed and (2) accommodate exceptions to the normal workflow. The products should perform functions such as sending work to whoever is available and qualified to work on it, modifying priorities of work that needs to be expedited, creating subtasks when unanticipated situations arise, and recording information about workflow performance for later reporting.
Figure 7: Example of Automated Workflow
Client/server automated workflow products will be moving toward the graphical interfaces that are prevalent in PC windows. In these interfaces, icons that represent specific functions (e.g., word processing and spreadsheet) appear on the PC screen and are selected to activate a function. In the workflow function, icons will be created to represent document processes. These icons then can be manipulated and linked to define the workflow for a given document or group of documents. After the workflow is defined and validated through simulation, it is ready for use in the workgroup. Steadily improving products that perform these workflow functions are appearing on the market.
These client/server workflow products will function as an integral part of client/server and desktop computing. In many respects, workflow will be the agent for integration since it will define work to be done on a document (e.g., convert using OCR, combine data and text with images to form a compound document) and will be linked, using icons, to the document.
Workflow is not unique to imaging. It applies to almost anything that goes from workstation to workstation for processing--such as preparation, review, and modification of an opinion prepared by several judges using word processing. In fact, many organizations are using automated workflow as a vehicle for re-engineering because it brings work processes into sharper focus and helps standardize them. Workflow reaches its full usefulness when imaging, data processing, word processing, and other technologies are integrated so that users can easily perform whatever work is required regardless of the technology.
Because of its wide applicability, workflow software is improving rapidly and being more widely used. Mainframe and client/server workflow products will provide more functionality, conform to previously undefined standards, and contain better workflow performance monitoring.
OCR is one of the keys to the future because it permits imaged characters (e.g., letters, numbers, and punctuation marks) to be converted by the computer to a form that can be recognized by other types of systems such as data processing and word processing systems. This avoids manual reentry of these characters. For example, OCR could be applied to parts of imaged pleadings to update the case processing system and to supply parts of court orders produced with word processing.
While, as noted earlier, OCR is improving, it has not yet reached its full potential. Two methods that have great promise are neural OCR and contextual intelligence. Conventional OCR attempts to match each individual character, or that character’s features (e.g., lines, loops, and curves), with predefined characters or collections of features that infer the character’s identity. Neural OCR, on the other hand, collects information about the character and attempts to deduce the character’s identity by "learning" about the character, much like the human brain. Contextual intelligence deduces additional information about the character based on factors such as frequently used phrases or character combinations in the document, syntax and semantics, and document topics.
Some larger imaging systems, such as the one being developed for the federal Internal Revenue Service, increase the accuracy of OCR conversion by passing imaged characters through multiple converters with algorithms that key on different character features. Presumably, the complementary effect of these multiple converters will increase the probability of a correct OCR conversion.
If you are working with a document, you may want to see the document as it originally appeared and not simply a summary of the document or only its text. Data processing systems can index a document and display a summary of its contents but cannot easily display the complete document. If the document happens to be in your word processing system, you can retrieve its text, but you cannot display the document as it originally appeared. Imaging, integrated with data and word processing, opens a wider universe of possibilities for document retrieval and display.
Specifically, the three integrated technologies needed to input, index, store, retrieve, and distribute documents are text retrieval, imaging, and database management. Imaging and text retrieval, respectively, permit original documents and only their text to be input into a computer. Text retrieval permits the document to be completely indexed, using full text if necessary, and stored and retrieved, usually in full-text form. Using document locators obtained from text retrieval, imaging permits documents to be stored and displayed as they originally appeared. Database management provides the underlying control and support for the documents and indexes in storage.
This addresses problems such as finding information by subject or title as opposed to by case number or some other numerical identifier. While indexes or summary database records will lead you to some information, you often need to search the actual documents to find the correct subject or title. We all have experienced this need with our manual files. Working with its index, text retrieval permits a full-text search as a preliminary screening, followed by a display of those documents for which matches were found. This process can be repeated until the number of matches is manageable. Finally, using imaging, the document(s) that you need are retrieved and displayed.
Text retrieval will greatly enhance the value of imaged documents as integral parts of multi-media repositories from which, for example, information stored in imaging, data processing, and word processing files can be retrieved and used.
Much of the integration reaches fruition in compound documents in which parts of documents and data from imaging, word processing, and data processing systems can be combined into a single document without cumbersome format conversions or other manipulations. OCR will make this a reality, as noted above, by converting images into a format that is common to word processing and data processing.
For example, in preparing a court order, a judge may use the case processing system index to identify similar orders. Then he or she may retrieve the imaged orders (text retrieval and imaging), review and combine parts of them with data from the case processing system and new text, using word processing to create the desired order as a compound document. These steps may be predefined by a workflow linked to the order creation function.
Carrying the integration two steps further, if the above documents, or their parts, can be reduced to graphics similar to the icons in today’s client server and desktop computing, it may be possible to create a compound document by manipulating the icons instead of lengthy text. Finally, with open architecture and the computer and network integration that it promotes, compound documents could be created across networks of computers as would be done by supreme court justices researching, writing, reviewing, and editing an opinion from their offices scattered around the state.