SAE GEIA-HB-859-2006 Implementation Guide for Data Management (Formerly TechAmerica GEIA-HB-859).pdf

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4、0 (outside USA) Fax: 724-776-0790 Email: CustomerServicesae.org SAE WEB ADDRESS: http:/www.sae.org SAE values your input. To provide feedback on this Technical Report, please visit http:/www.sae.org/technical/standards/GEIAHB859 TECHNICAL REPORT GEIA-HB-859 Issued 2006-01 Implementation Guide for Da

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14、y be occasioned by changes in technology, industry practice, or government regulations, or for other appropriate reasons. (Formulated under the cognizance of the GEIA Data and Configuration Management Committee (G-33).) Published by 2010 TechAmerica Standards they are what is done throughout the ent

15、erprise to manage the configuration of its products and maintain its data assets. CM and DM activities involve personnel from many corporate and functional groups and teams. The focus of the GEIA standards and handbooks is more on the functions that must be performed and not on who is tasked to perf

16、orm them. GEIA does not endorse any specific organizational relationships. It is GEIA policy that standards and handbooks reflect methods available to each enterprise, which then determines how to allocate their resources and distribute these tasks. Any reference to how organizations are, or should

17、be, comprised is the province of each individual enterprise. In the above CM and DM documents, any reference to specific organizational relationships are strictly for example purposes. They may illustrate typical situations, but such references should not be construed as necessarily appropriate or c

18、orrect for any given enterprise. viiGEIA-HB-859 How to Use This Handbook ANSI/GEIA-859 is a principles-based standard, organized according to the focus of the principles. This handbook is organized according to the activities in the traditional data management life cycle. This life cycle should be f

19、amiliar to data managers and should provide a context for applying the principles articulated in the standard. ANSI/GEIA-859 principle Application of principle in handbook 1Define the enterprise-relevant scope of data management Section 32Plan for, acquire, and provide data responsive to customer re

20、quirements Sections 3 and 43Develop DM processes to fit the context and business environment in which they will be performed Section 3. 4Identify data products and views so that their requirements and attributes can be controlled Section 45Control data, data products, data views, and metadata using

21、approved change control processes Section 56Establish and maintain an identification process for intellectual property, proprietary, and competition-sensitive data Annex B7Retain data commensurate with value Section 68Continuously improve data management Annex C9Effectively integrate data management

22、 with knowledge management Annex DHow the Handbook Was Developed This handbook was developed under the auspices of GEIAs Data Management Panel, a joint industry-government group. It incorporates lessons learned by industry and government practitioners and managers from the aerospace, transportation,

23、 defense, and other communities. Leadership of this effort was sponsored by the Office of the Secretary of Defense, Acquisition, Technology and Logistics, Systems Engineering, Enterprise Development in partnership with Logistics Systems Modernization. Companion Documents ANSI/GEIA-859 and this handb

24、ook are part of a family of standards and handbooks that, taken together, cover most of the aspects of complex systems design, engineering, and production: ANSI/EIA-632-1999, Processes for Engineering a System ANSI/EIA-649-A-2004, National Consensus Standard for Configuration Management GEIA-HB-649,

25、 Handbook for EIA-649, National Consensus Standard for Configuration Management” EIA-836, Configuration Management Data Exchange and Interoperability. viiiGEIA-HB-859 1.0 Introduction Data management is an area of discipline oriented to ensuring that data and information are available and usable whe

26、n and where they are needed. Data management is most visibly practiced in challenging information environmentsthose in which the volume of data is large, the useful life of the data far exceeds the useful life of storage media, and there is a complex mix of types of data, a broad user base, and many

27、 levels and categories of access rights. Data management comprises the activities needed to plan, develop, implement, and administer systems for the acquisition, storage, and retrieval of data. Mandatory in many federal activities since the 1960s, data management is widely used in the aerospace indu

28、stry. It is also used commercially in industries with challenging data environments, such as the automotive industry, the pharmacological industry, the nuclear power industry, and medicine and clinical settings. Many of the examples in this handbook originate in the aerospace community, but the prin

29、ciples in ANSI/GEIA-859 and the practices in this handbook can be applied in other contexts. Traditional DM approaches were based on the divide between the customer (often a government agency) and the supplier. Standards and guidance focused on how a customer specified the data to be supplied, data

30、formats, frequency of delivery, etc., to ensure that data products (often in physical forms such as paper) were delivered and on-hand to support engineering and program management decisions. The traditional role of the data manager in the customer organization has been to specify data to be delivere

31、d, contracting for that delivery, and monitoring the data delivered. For sometime we have been in transition; as a result of changes in acquisition (performance-based contracts, capabilities-based acquisition, and contracted logistics support), only minimal data may be physically delivered to the cu

32、stomer. Suppliers may build, operate, and maintain the system for its useful life. When data are delivered to the customer, delivery is frequently via electronic access to supplier-maintained information systems. The DM standards must recognize this new business environment and allow for the transit

33、ion from the traditional to newer acquisition approaches and new information delivery methods. To accommodate the range of acquisition approaches, ANSI/GEIA-859 provides the underlying principles of effective data management to be applied in traditional, transitional, or new DM environments. The pri

34、nciples are as follows: 1. Define the enterprise relevant scope of data management 2. Plan for, acquire, and provide data responsive to customer requirements 3. Develop DM processes to fit the context and business environment in which they will be performed 1GEIA-HB-859 4. Identify data products and

35、 views so that their requirements and attributes can be controlled 5. Control data, data products, data views, and metadata using approved change control processes 6. Establish and maintain an identification process for intellectual property, proprietary, and competition-sensitive data 7. Retain dat

36、a commensurate with value 8. Continuously improve data management 9. Effectively integrate data management with knowledge management The principles can be applied to managing data regardless of the environment; they apply to traditional paper-based delivery of data, to electronically maintained and

37、delivered data, and to performance-based acquisition, including contractor logistics. 1.1 Data Management Overview Figure 1-1 shows, at the highest level of abstraction, the DM process in a complex engineering program environment. The process begins when a complex engineering program is contemplated

38、specifically, when the requirements for the engineered product are being developed. At this time, the customer for the product plans for the product and its maintenance, the evolution of its systems to read and use the data provided by the supplier, and the measures needed to ensure that both produc

39、t development and data proceed according to plan. The DM process uses the inputs, facilitators, and good data management practices to deliver all needed outputs within constraints. 2GEIA-HB-859 Figure 1-1. Top-Level Process Model of Data Management DATA MANAGEMENT PROCESSINPUTSOUTPUTS,RESULTSProgram

40、 initiationEnterprise architectureUser requirementsLogistics and maintenance plansData status and performance measurementsCONSTRAINTSTimingResourcesLaw, policyRFP/contractInfrastructureMECHANISMS/FACILITATORSManagement support,facilities, resources, trainingDefined processes/proceduresEffective work

41、ing relationshipsAcquisition and support strategiesList of required data in contract, descriptions of required dataRegulations, manuals, handbooks and standardsHistory/lessons learnedCommercial practicesTools/technologyDocumented DM process DM concept of operations or DM StrategyRFP and Contract dat

42、a reqmts defined, scheduled and pricedStandard descriptions of common data productsUpdated list of required dataKnown data status Data provided at point of use; or available for access when neededData archived/disposed per planDM performance measured and continuously improvedLessons learnedProgram i

43、mage enhanced; user support improvedFigure 1-2 is a high-level depiction of DM activities. To be successful, the data manager must plan and manage the DM program, determine what data are needed by whom and when, acquire and provide stewardship over the data, and deliver, provide access to, and prope

44、rly dispose of the data. 3GEIA-HB-859 Figure 1-2. Top-Level Activity Model of Data Management Access rulesPlan often, customers bought more data than needed due to an inability to predict specifically and in detail what types of data would be needed. Due to acquisition reform and the explosion in in

45、formation systems and networks that facilitate data sharing between customer and supplier, this approach is no longer effective. 1.2 Benefits of Enterprise Data Management By conducting DM activities according to the principles of ANSI/GEIA-859, enterprises reduce the risk of not having needed data

46、available when and where they are needed. Having the right data available supports better design and development decisions, supports faster decision processes, provides early-warning information, and reduces costs associated with hard-copy data delivery. Providing electronic access to the authoritat

47、ive source for a given data product, for example, ensures data integrity in a way not possible in the old environment where multiple hard-copy documents were delivered over the life cycle. The enterprise DM process, aided by new computing and networking support, makes information available more quic

48、kly and facilitates collaboration among customers and suppliers. It controls the digital format and the procedures necessary to exchange, index, store, and distribute or provide access to data. It offers a wide range of benefits that contribute to improvements in the cost, schedule, performance, and

49、 support of complex engineered systems. 4GEIA-HB-859 A small case study can help managers understand the impacts of approaching data management from the enterprise perspective illustrated in ANSI/GEIA-859: In a defense supplier manufacturing facility, electronic circuit board manufacture is supported by schematics supplied electronically to the shop floor. Elsewhere in the DM infrastructure,