10 Document and Content Management

Document and Content Management is the eighth Data Management Function in the data management framework shown in Figures 1.3 and 1.4. It is the seventh data management function that interacts with and is influenced by the Data Governance function. Chapter 10 defines the document and content management function and explains the concepts and activities involved in document and content management.

10.1 Introduction

Document and Content Management is the control over capture, storage, access, and use of data and information stored outside relational databases. Document and Content Management focuses on integrity and access.. Therefore, it is roughly equivalent to data operations management for relational databases. Since most unstructured data has a direct relationship to data stored in structured files and relational databases, the management decisions need to provide consistency across all three areas. However, Document and Content Management looks beyond the purely operational focus. Its strategic and tactical focus overlaps with other data management functions in addressing the need for data governance, architecture, security, managed meta-data, and data quality for unstructured data.

As its name implies, Document and Content Management includes two sub-functions:

• Document management is the storage, inventory, and control of electronic and paper documents. Consider any file or record a document; and document management includes records management8. Document management encompasses the processes, techniques, and technologies for controlling and organizing documents and records, whether stored electronically or on paper.
• Content management refers to the processes, techniques, and technologies for organizing, categorizing, and structuring access to information content, resulting in effective retrieval and reuse. Content management is particularly important in developing websites and portals, but the techniques of indexing based on keywords, and organizing based on taxonomies, can be applied across technology platforms. Sometimes, content management is referred to as Enterprise Content Management (ECM), implying the scope of content management is across the entire enterprise.

In general, document management concerns files with less awareness of file content. The information content within a file may guide how to manage that file, but document management treats the file as a single entity. Content management looks inside each file and tries to identify and use the concepts included in a file’s information content.

The context diagram for Document and Content Management is shown in Figure 10.1.

Figure 10.1 Document and Content Management Context Diagram

10.2 Concepts and Activities

The boundaries between document management and content management are blurring as business processes and roles intertwine, and vendors try to widen the markets for their technology products.

The fundamental principles of data management, as outlined in this Guide, apply to both structured and unstructured data. Unstructured data is a valuable corporate asset. Storage, integrity, security, content quality, access, and effective use guide the management of unstructured data. Unstructured data requires data governance, architecture, security meta-data, and data quality.

A document management system is an application used to track and store electronic documents and electronic images of paper documents. Document library systems, electronic mail systems and image management systems are specialized forms of a document management system. Document management systems commonly provide storage, versioning, security, meta-data management, content indexing, and retrieval capabilities.

A content management system is used to collect, organize, index, and retrieve information content; storing the content either as components or whole documents, while maintaining links between components. It may also provide controls for revising information content within documents. While a document management system may provide content management functionality over the documents under its control, a content management system is essentially independent of where and how the documents are stored.

10.2.1 Unstructured Data

Unstructured data is any document, file, graphic, image, text, report, form, video, or sound recording that has not been tagged or otherwise structured into rows and columns or records. Non-tabular data includes unstructured data as well as tagged data. This term has unfair connotations, as there is usually some structure in these formats, for instance, paragraphs and chapters.

According to many estimates, as much as 80% of all stored data is maintained outside of relational databases. Unstructured or semi-structured data presents as information stored in context. Some refer to data stored outside relational databases as “non-tabular” data. Of course, there is always some structure in which data provides information, and this structure may even be tabular in its presentation. No single term adequately describes the vast volume and diverse format of unstructured data.

Unstructured data is found in different kinds of electronic formats, including word processing documents, electronic mail, flat files, spreadsheets, XML files, transactional messages, reports, business graphics, digital images, microfiche, video recordings, and audio recordings. An enormous amount of unstructured data also exists in paper files.

10.2.2 Document / Record Management

Document / Record Management is the lifecycle management of the designated significant documents of the organization. Not all documents are significant as evidence of the organization’s business activities and regulatory compliance.

While some hope technology will one day enable a paperless world, the world of today is certainly full of paper documents and records. Records management manages paper and microfiche / film records from their creation or receipt through processing, distribution, organization, and retrieval, to their ultimate disposition. Records can be physical, e.g. documents, memos, contracts, reports or microfiche; electronic, e.g. email content, attachments, and instant messaging; content on a website; documents on all types of media and hardware; and data captured in databases of all kinds. There are even hybrid records that combine formats such as aperture cards (paper record with a microfiche window imbedded with details or supporting material).

More than 90% of the records created today are electronic. Growth in email and instant messaging has made the management of electronic records critical to an organization. Compliance regulations and statutes, such as the U.S. Sarbanes-Oxley Act and E-Discovery Amendments to the Federal Rules of Civil Procedure, and Canada’s Bill 198, are now concerns of corporate compliance officers who, in turn, have pushed for more standardization of records management practices within an organization.

Due to many privacy, data protection, and identity theft issues, records management processes must not retain, nor transport across international boundaries, certain data about individuals. Both market and regulatory pressures result in greater focus on records retention schedules, location, transport, and destruction.

The lifecycle of Document / Record Management includes the following activities:

• Identification of existing and newly created documents / records.
• Creation, Approval, and Enforcement of documents / records policies.
• Classification of documents / records.
• Documents / Records Retention Policy.
• Storage: Short and long term storage of physical and electronic documents / records.
• Retrieval and Circulation: Allowing access and circulation of documents / records in accordance with policies, security and control standards, and legal requirements.
• Preservation and Disposal: Archiving and destroying documents / records according to organizational needs, statutes, and regulations.

Data management professionals are stakeholders in decisions regarding classification and retention schemes, in order to support business level consistency between the base structured data that relates to specific unstructured data. For example: If finished output reports are deemed appropriate historic documentation, the structured data in an OLTP or warehousing environment may be relieved of storing the report’s base data.

10.2.2.1 Plan for Managing Documents / Records

The practice of documents management involves planning at different levels of a document’s lifecycle, from its creation or receipt, organization for retrieval, distribution, and archiving or disposition. Develop classification / indexing systems and taxonomies so that the retrieval of documents is easy. Create planning and policy around documents and records on the value of the data to the organization and as evidence of business transactions.

Establish, communicate, and enforce policies, procedures, and best practices for documents. Freedom of Information legislation in some jurisdictions establishes governmental agencies that handle citizens’ requests for documents through a very formal process. These organizations also coordinate the evaluation of documents, and even parts of documents, for full or partial release and the timing of any release.

First, identify the responsible, accountable organizational unit for managing the documents / records. That unit develops a records storage plan for the short and long-term housing of records. The unit establishes and manages records retention policies according to company standards and government regulations. It coordinates the access and distribution of records internally and externally, and integrates best practices and process flows with other departments throughout the organization. The unit also creates a business continuity plan for vital documents / records.

Finally, the unit develops and executes a retention plan and policy to archive, such as selected records for long-term preservation. Records are destroyed at the end of their lifecycle according to operational needs, procedures, statutes, and regulations.

10.2.2.2 Implement Document / Record Management Systems for Acquisition, Storage, Access, and Security Controls

Documents can be created within a document management system or captured via scanners or OCR software. These electronic documents must be indexed via keywords or text during the capture process so that the document can be found. Meta-data, such as the dates the document was created, revised, stored, and the creator’s name, is typically stored for each document. It could be extracted from the document automatically or added by the user. Bibliographic records of documents are descriptive structured data, typically in Machine-Readable Cataloging (MARC) format standard that are stored in library databases locally and made available through shared catalogues world-wide, as privacy and permissions allow.

Document storage includes the management of these documents. A document repository enables check-in and check-out features, versioning, collaboration, comparison, archiving, status state(s), migration from one storage media to another, and disposition. Documents can be categorized for retrieval using a unique document identifier or by specifying partial search terms involving the document identifier and / or parts of the expected meta-data.

Reports may be delivered through a number of tools, including printers, email, websites, portals, and messaging, as well as through a document management system interface. Depending on the tool, users can search by drill-downs, view, download / check-in and out, and print reports on demand. Report management can be facilitated by the ability to add / change / delete reports organized in folders. Report retention can be set for automatic purge or archival to another media, such as disk, CD-ROM, etc.

Since the functionality needed is similar, many document management systems include digital asset management. This is the management of digital assets such as audio, video, music, and digital photographs. Tasks involve cataloging, storage, and retrieval of digital assets.

Some document management systems have a module that may support different types of workflows, such as:

• Manual workflows that indicate where the user sends the document.
• Rules-based workflow, where rules are created that dictate the flow of the document within an organization.
• Dynamic rules that allow for different workflows based on content.

Document management systems may have a rights management module where the administrator grants access based on document type and user credentials. Organizations may determine that certain types of documents require additional security or control procedures. Security restrictions, including privacy and confidentiality restrictions, apply during the document’s creation and management, as well as during delivery. An electronic signature ensures the identity of the document sender and the authenticity of the message, among other things. Some systems focus more on control and security of data and information, rather than on its access, use, or retrieval, particularly in the intelligence, military, and scientific research sectors. Highly competitive or highly regulated industries, such as the pharmaceutical and financial sectors, also implement extensive security and control measures.

There are schemes for levels of control based on the criticality of the data and the perceived harm that would occur if data were corrupted or otherwise unavailable. ANSI Standard 859 (2008) has three levels of control: formal (the most rigid), revision, or custody (the least rigid).

When trying to establish control on documents, the following criteria is recommended in ANSI 859. Formal control requires formal change initiation, thorough change evaluation for impact, decision by a change authority, and full status accounting of implementation and validation to stakeholders. Revision control is less formal, notifying stakeholders and incrementing versions when a change is required. Custody control is the least formal, merely requiring safe storage and a means of retrieval. Table 10.1 shows a sample list of data assets and possible control levels.

When determining which control level applies to data assets, ANSI 859 recommends use of the following criteria:

1. Cost of providing and updating the asset.
2. Project impact, when the change has significant cost or schedule consequences.
3. Other consequences of change to the enterprise or project.
4. Need to reuse the asset or earlier versions of the asset.
5. Maintenance of a history of change (when significant to the enterprise or the project).

10.2.2.3 Backup and Recover Documents / Records

The document / record management system needs to be included as part of the overall corporate backup and recovery activities for all data and information. It is critical that a document / records manager be involved in risk mitigation and management, and business continuity, especially regarding security for vital records. Risk can be classified as threats that partially or totally interrupt an organization from conducting normal operations. Use of near-online sites, hot sites, or cold sites can help resolve some of the issues. Disasters could include power outages, human error, network and hardware failure, software malfunction, malicious attack, as well as natural disasters. A Business Continuity Plan (sometimes called a Disaster Recovery Plan) contains written policies, procedures, and information designed to mitigate the impact of threats to all media of an organization’s documents / records, and to recover them in the event of a disaster, to recover them in a minimum amount of time, and with a minimum amount of disruption.

Table 10.1 Sample Levels of Control for Documents per ANSI- 859

A vital records program provides the organization with access to the records necessary to conduct its business during a disaster, and to resume normal business afterward. Vital records must be identified, plans developed for protection and recovery, and the plans must be maintained. Business continuity exercises need to include vital record recovery. Employees and managers responsible for vital records require training. And internal audits need to be conducted to ensure compliance with the vital records program.

10.2.2.4 Retention and Disposition of Documents / Records

A document / records retention and disposition program defines the period of time during which documents / records for operational, legal, fiscal or historical value must be maintained. It defines when the documents / records are not active anymore and can be transferred to a secondary storage facility, such as off-site storage. The program specifies the processes for compliance, and the methods and schedules for the disposition of documents / records.

Documents / records retention presents software considerations. Electronic records may require the use of appropriate combinations of software versions and operating systems to enable access. Installation of new software versions or technological changes can create a risk of system breaches or complete loss of readability / usability.

Document / records managers must deal with privacy and data protection issues, and with identify theft of records. They ensure that there is no retention of personally identifiable data. This brings attention to how the records retention schedules are set up for destruction documents / records.

Legal and regulatory requirements must be considered when setting up document / record retention schedules. The digital data in electronic records make it well-suited for retrieval for civil and criminal legal cases. All types of electronic records listed above can be discovered for evidence, including e-mail, where people are often less careful than they should be.

Non-value-added information should be removed from the organization’s holdings and disposed of to avoid wasting physical and electronic space, as well as the cost associated with its maintenance. Policy and procedures development and conformance are critical to good records management.

Many organizations do not give priority to removing non-value added information because:

• Policies are not adequate.
  • One person’s non-valued-added information is another’s valued information.
  • Inability to foresee future possible needs for current non-value-added physical and / or electronic records
• There is no buy- in for Records Management.
  • Inability to decide which records to delete.
  • Perceived cost of making a decision and removing physical and electronic records.
  • Electronic space is cheap. Buying more space when required is easier than archiving and removal processes.

10.2.2.5 Audit Document / Records Management

Document / records management requires auditing on a periodic basis to ensure that the right information is getting to the right people at the right time for decision making or performing operational activities. An example of sample audit measures is shown in Table 10.2.

Document / Records Management Component	Sample Audit Measure
Inventory	Each location in the inventory is uniquely identified.
Storage	Storage areas for physical documents / records have adequate space to accommodate growth.
Reliability and Accuracy	Spot checks are executed to confirm that the documents / records are an adequate reflection of what has been created or received.
Classification and Indexing Schemes	Meta-data and document file plans are well described.
Access and Retrieval	End users find and retrieve critical information easily.
Retention Processes	The retention schedule is structured in a logical way.
Disposition Methods	Documents / records are disposed of as recommended.
Security and Confidentiality	Breaches of document / record confidentiality and loss of documents / records are recorded as security incidents and managed appropriately.
Organizational understanding of documents / records management	Appropriate training is provided to stakeholders and staff as to the roles and responsibilities related to document / records management.

Table 10.2 Sample Audit Measures

An audit usually consists of:

• Defining organizational drivers and identifying the stakeholders that comprise the “why” of document / records management.
• Gathering data on the process (the “how”), once it is determined what to examine / measure and what tools to use (such as standards, benchmarks, interview surveys).
• Reporting the outcomes.
• Developing an action plan of next steps and timeframes.

10.2.3 Content Management

Content management is the organization, categorization, and structure of data / resources so that they can be stored, published, and reused in multiple ways.

Content includes data / information, that exists in many forms and in multiple stages of completion within its lifecycle. Content may be found on electronic, paper or other media. In the content’s completed form, some content may become a matter of record for an organization and requires different protection in its lifecycle as a record.

The lifecycle of content can be active, with daily changes through controlled processes for creation, modification, and collaboration of content before dissemination. Depending on what type of content is involved, it may need to be treated formally (strictly stored, managed, audited, retained or disposed of), or informally.

Typically, content management systems manage the content of a website or intranet through the creation, editing, storing, organizing, and publishing of content. However, the term content has become broader in nature to include unstructured information and the technologies already discussed in this chapter. Many data management professionals may be involved with the various concepts of this section, such as aspects of XML.

10.2.3.1 Define and Maintain Enterprise Taxonomies (Information Content Architecture)

Many ideas exist about what information content architecture or information architecture is and what an Information Architect does. In general, it is the process of creating a structure for a body of information or content.

For a document or content management system, Content Architecture identifies the links and relationships between documents and content, specifies document requirements and attributes, and defines the structure of content in a document or content management system.

For website management, information content architecture is specific to the production of a website. It identifies the owner(s) of the publishable content, and the publication timeframe. A menu structure of the site is designed using a common navigational model.

When creating the information content architecture, taxonomy meta-data (along with other meta-data) is used. Meta-data management and data modeling techniques are leveraged in the development of a content model.

Taxonomy is the science or technique of classification. It contains controlled vocabulary that can help with navigation and search systems. Ideally, the vocabulary and the entities in an enterprise conceptual data model should coordinate. Taxonomies are developed from an ontological perspective of the world.

Taxonomies are grouped into four types:

• A flat taxonomy has no relationship among the controlled set of categories as the categories are equal. An example is a list of countries.
• A facet taxonomy looks like a star where each node is associated with the center node. Facets are attributes of the object in the center. An example is meta-data, where each attribute (creator, title, access rights, keywords, version, etc.) is a facet of a content object.
• A hierarchical taxonomy is a tree structure of at least two levels and is bi-directional. Moving up the hierarchy expands the category; moving down refines the category. An example is geography, from continent down to address.
• A network taxonomy organizes content into both hierarchical and facet categories. Any two nodes in a network taxonomy link based on their associations. An example is a recommender engine (…if you liked that, you might also like this…). Another example is a thesaurus.

An ontology is a type of model that represents a set of concepts and their relationships within a domain. Both declarative statements and diagrams using data modeling techniques can describe these concepts and relationships. Most ontologies describe individuals (instances), classes (concepts), attributes, and relations. It can be a collection of taxonomies, and thesauri of common vocabulary for knowledge representation and exchange of information. Ontologies often relate to a taxonomic hierarchy of classes and definitions with the subsumption relation, such as decomposing intelligent behavior into many simpler behavior modules and then layers.

Semantic modeling is a type of knowledge modeling. It consists of a network of concepts (ideas or topics of concern) and their relationships. An ontology, a semantic model that describes knowledge, contains the concepts and relationships together.

10.2.3.2 Document / Index Information Content Meta-data

The development of meta-data for unstructured data content can take many forms, mostly and pragmatically based on:

• Format(s) of the unstructured data. Often the format of the data dictates the method to access the data (such as Electronic index for electronic unstructured data).
• Whether search tools already exist for use with related unstructured data.
• Whether the meta-data is self-documenting (as in file systems). In this case development is minimal, as the existing tool is simply adopted.
• Whether existing methods and schemes can be adopted or adapted (as in library catalogs).
• Need for thoroughness and detail in retrieval (as in the pharmaceutical or nuclear industry). Therefore detailed meta-data at the content level might be necessary, and a tool capable of content tagging might be necessary.

Generally the maintenance of meta-data for unstructured data becomes the maintenance of a cross-reference of various local schemes to the official set of enterprise meta-data. Records managers and meta-data professionals recognize long term embedded methods exist throughout the organization for documents / records / content that must be retained for many years, but that these methods are too costly to re-organize. In some organizations, a centralized team maintains cross-reference schemes between records management indexes, taxonomies and even variant thesauri.

10.2.3.3 Provide Content Access and Retrieval

Once the content has been described by meta-data / key word tagging and classified within the appropriate Information Content Architecture, it is available for retrieval and use. Finding unstructured data in the company can be eased through portal technology that maintains meta-data profiles on users to match them with content areas.

A search engine is a class of software that searches for requested information and retrieves websites that have those terms within its content. One example is Google. It has several components: search engine software, spider software that roams the Web and stores the Uniform Resource Locators (URLs) of the content it finds, indexing of the encountered keywords and text, and rules for ranking. Search engines can be used to search within a content management system, returning content and documents that contain specified keywords. Dogpile.com is a search engine that presents results from many other search engines.

Another organizational approach is to use professionals to retrieve information through various organizational search tools. This unstructured data can be used for hearings, ad hoc retrievals, executive inquires, legislative or regulatory reporting needs, or a Securities Commission enquiry, to name a few. Sample meta-data tools include:

• Data models used as guides to the data in an organization, with subject areas assigned to organizational units.
• Document management systems.
• Taxonomies.
• Cross reference schemes between taxonomies.
• Indexes to collections (e.g. particular product, market or installation).
• Indexes to archives, locations, or offsite holdings.
• Search engines.
• BI tools that incorporate unstructured data.
• Enterprise and departmental thesauri.
• File system indexes.
• Project manager control records.
• Published reports libraries, contents and bibliographies, and catalogs.
• Ad hoc or regular management reports collections.
• Indexes of opinion polls.
• Recording management systems for hearings or other meetings.
• Product development archives.

Tim Berners-Lee, the inventor of the World Wide Web, published an article in Scientific American in May of 2001, suggesting the Web could be made more intelligent: a concept known as the Semantic Web. Context-understanding programs could find the pages that the user seeks. These programs rely on natural language, machine-readable information, ‘fuzzy’ search methods, Resource Description Format (RDF) meta-data, ontologies, and XML.

Extensible Markup Language (XML) facilitates the sharing of data across different information systems and the Internet. XML puts tags on data elements to identify the meaning of the data rather than its format (e.g. HTML). Simple nesting and references provide the relationships between data elements. XML namespaces provide a method to avoid a name conflict when two different documents use the same element names. Older methods of markup include SGML and GML, to name a few.

XML provides a language for representing both structured and unstructured data and information. XML uses meta-data to describe the content, structure, and business rules of any document or database.

The need for XML-capable content management has grown. Several approaches include the following:

• XML provides the capability of integrating structured data into relational databases with unstructured data. Unstructured data can be stored in a relational DBMS BLOB (binary large object) or in XML files.
• XML can integrate structured data with unstructured data in documents, reports, email, images, graphics, audio, and video files. Data modeling should take into account the generation of unstructured reports from structured data, and include them in creating data quality error-correction workflows, backup, recovery, and archiving.
• XML also can build enterprise or corporate portals, (Business-to-Business (B2B), Business-to-Customer (B2C)), which provide users with a single access point to a variety of content.

Computer applications cannot process unstructured data / content directly. XML provides identification and labeling of unstructured data / content so that computer applications can understand and process them. In this way, structured data appends to unstructured content. An Extensible Markup Interface (XMI) specification consists of rules for generating the XML document containing the actual meta-data and thus is a ‘structure’ for XML.

Unstructured and semi-structured data is becoming more important to data warehousing and business intelligence. Data warehouses and their data models may include structured indexes to help users find and analyze unstructured data. Some databases include the capacity to handle URLs to unstructured data that perform as hyperlinks when retrieved from the database table.

Keyed RDF structures are used by search engines to return a single result set from both databases and unstructured data management systems. However, using keyed RDF structures is not yet an industry standards-based method.

10.2.3.4 Govern for Quality Content

Managing unstructured data requires effective partnerships between data stewards, data professionals, and records managers, with similar dynamics to the governance of structured data. Business data stewards can help define web portals, enterprise taxonomies, search engine indexes, and content management issues.

The focus of data governance in an organization may include document and record retention policies, electronic signature policies, reporting formats, and report distribution policies. Data professionals implement and execute these and other policies to protect and leverage data assets found in unstructured formats. A key to meeting the business needs of the organization is to maximize the skill set of its records management professionals.

High quality, accurate, and up-to-date information will aid in critical business decisions. Timeliness of the decision-making process with high quality information may increase competitive advantage and business effectiveness.

Defining quality for any record or for any content is as elusive as it is for structured data.

• Who needs the information? Consider the availability to both those who originate the information and those who must use it.
• When is the information needed? Some information may be required with limited regularity, such as monthly, quarterly, or yearly. Other information may be needed every day or not at all.
• What is the format of the information? Reporting in a format that cannot be used effectively results in the information having no real value.
• What is the delivery mechanism? A decision must be made on whether to deliver the information or to make it accessible electronically through, for example, a message or a website.

10.3 Summary

The guiding principles for implementing document and content management into an organization, a summary table of the roles for each document and content management activity, and organization and cultural issues that may arise during document and content management are summarized below.

10.3.1 Guiding Principles

The implementation of the document and content management function into an organization follows three guiding principles:

• Everyone in an organization has a role to play in protecting its future. Everyone must create, use, retrieve, and dispose of records in accordance with the established policies and procedures.
• Experts in the handling of records and content should be fully engaged in policy and planning. Regulatory and best practices can vary significantly based on industry sector and legal jurisdiction.
• Even if records management professionals are not available to the organization, everyone can be trained and have an understanding of the issues. Once trained, business stewards and others can collaborate on an effective approach to records management.

10.3.2 Process Summary

The process summary for the document and content management function is shown in Table 10.3. The deliverables, responsible roles, approving roles, and contributing roles are shown for each activity in the document and content management function. The Table is also shown in Appendix A9.

Activities	Deliverables	Responsible Roles	Approving Roles	Contributing Roles
8.1 Document and Records Management
8.1.1 Plan for Managing Documents / Records (P)	Document Management Strategy and Roadmap	Document System Managers, Records Managers	Data Governance Council	Data Architects, Data Analysts, Business Data Stewards
8.1.2 Implement Document / Record Management Systems for Acquisition, Storage, Access, and Security Controls (O, C)	Document / Record Management Systems (including image and e-mail systems), Portals Paper and Electronic Documents (text, graphics, images, audio, video)	Document System Managers, Records Managers	Subject Matter Experts
8.1.3 Backup and Recover Documents / Records (O)	Backup Files Business Continuity	Document Systems Managers, Records Managers
8.1.4 Retain and Dispose Documents / Records (O)	Archive Files Managed Storage	Document Systems Managers, Records Managers
8.1.5 Audit Document / Record Management (C)	Document / Record Management Audits	Audit Department, Management	Management
8.2 Content Management
8.2.1 Define and Maintain Enterprise Taxonomies (P)	Enterprise Taxonomies (Information Content Architecture)	Knowledge Managers	Data Governance Council	Data Architects, Data Analysts, Business Data Stewards
8.2.2 Document / Index Information Content Meta-data (D)	Indexed Keywords, Meta-data	Document Systems Managers, Records Managers
8.2.3 Provide Content Access and Retrieval (O)	Portals, Content Analysis, Leveraged Information	Document Systems Managers, Records Managers	Subject Matter Experts	Data Architects, Data Analysts
8.2.4 Govern for Quality Content (C)	Leveraged Information	Document Systems Managers, Records Managers	Business Data Stewards	Data Management Professionals

Table 10.3 Document and Content Management Process Summary

10.3.3 Organizational and Cultural Issues

Q1: Where in the organization should records management be placed?

A1: The records management function needs to be elevated organizationally and not seen as a low level or low priority function.

Q2: What are the most important issues that a document and content management professional needs to recognize?

A2: Privacy, data protection, confidentiality, intellectual property, encryption, ethical use, and identity are the important issues that document and content management professionals must deal with in cooperation with employees, management, and regulators.

10.4 Recommended Reading

The references listed below provide additional reading that support the material presented in Chapter 10. These recommended readings are also included in the Bibliography at the end of the Guide.

10.4.1 Document / Content Management

Aspey, Len and Michael Middleton. Integrative Document & Content Management: Strategies for Exploiting Enterprise Knowledge. 2003. IGI Global, ISBN-10: 1591400554, ISBN-13: 978-1591400554.

Boiko, Bob. Content Management Bible. Wiley, 2004. ISBN-10: 0764573713, ISBN-13: 978-07645737.

Jenkins, Tom, David Glazer, and Hartmut Schaper.. Enterprise Content Management Technology: What You Need to Know, 2004. Open Text Corporation, ISBN-10: 0973066253, ISBN-13: 978-0973066258.

Sutton, Michael J. D. Document Management for the Enterprise: Principles, Techniques, and Applications. Wiley, 1996, ISBN-10: 0471147192, ISBN-13: 978-0471147190.

10.4.2 Records Management

Alderman, Ellen and Caroline Kennedy . The Right to Privacy. 1997. Vintage, ISBN-10: 0679744347, ISBN-13: 978-0679744344.

Bearman, David. Electronic Evidence: Strategies for Managing Records in Contemporary Organizations. 1994. Archives and Museum Informatics. ISBN-10: 1885626088, ISBN-13: 978-1885626080.

Cox, Richard J. and David Wallace. Archives and the Public Good: Accountability and Records in Modern Society. 2002. Quorum Books, ISBN-10: 1567204694, ISBN-13: 978-1567204698.

Cox, Richard J. Managing Records as Evidence and Information. Quorum Books, 2000. ISBN 1-567-20241-4. 264 pages.

Dearstyne, Bruce. Effective Approaches for Managing Electronic Records and Archives. 2006. The Scarecrow Press, Inc. ISBN-10: 0810857421, ISBN-13: 978-0810857421.

Ellis, Judith, editor. Keeping Archives. Thorpe Bowker; 2 Sub edition. 2004. ISBN-10: 1875589155, ISBN-13: 978-1875589159.

Higgs, Edward. History and Electronic Artifacts. Oxford University Press, USA. 1998. ISBN-10: 0198236344, ISBN-13: 978-0198236344.

Robek. Information and Records Management: Document-Based Information Systems. Career Education; 4 edition. 1995. ISBN-10: 0028017935.

Wellheiser, Johanna and John Barton. An Ounce of Prevention: Integrated Disaster Planning for Archives, Libraries and Records Centers. Canadian Library Assn. 1987. ISBN-10: 0969204108, ISBN-13: 978-0969204107.

10.4.3 Enterprise Information Portals

Firestone, Joseph M. Enterprise Information Portals and Knowledge Management. Butterworth-Heineman, 2002. ISBN 0-750-67474-1. 456 pages.

Mena, Jesus, Data Mining Your Website, Digital Press, Woburn, MA, 1999, ISBN 1-5555-8222- 2.

10.4.4 Meta-data in Library Science

Baca, Murtha, editor. Introduction to Metadata: Pathways to Digital Information. Getty Information Institute, 2000. ISBN 0-892-36533-1. 48 pages.

Hillman, Diane I., and Elaine L. Westbrooks,. Metadata in Practice. American Library Association, 2004. ISBN 0-838-90882-9. 285 pages.

Karpuk, Deborah. Metadata: From Resource Discovery to Knowledge Management. Libraries Unlimited, 2007. ISBN 1-591-58070-6. 275 pages.

Liu, Jia. Metadata and Its Applications in the Digital Library. Libraries Unlimited, 2007. ISBN 1-291-58306-6. 250 pages.

10.4.5 Semantics in XML Documents

McComb, Dave. Semantics in Business Systems: The Savvy Manager’s Guide. The Discipline Underlying Web Services, Business Rules and the Semantic Web. San Francisco, CA: Morgan Kaufmann Publishers, 2004. ISBN: 1-55860-917-2.

10.4.6 Unstructured Data and Business Intelligence

Inmon, William H. and Anthony Nesavich,. Tapping into Unstructured Data: Integrating Unstructured Data and Textual Analytics into Business Intelligence. Prentice-Hall PTR, 2007. ISBN-10: 0132360292, ISBN-13: 978-0132360296.

10.4.7 Standards

ANSI/EIA859 : Data Management.

ISO 15489-1:2001 Records Management -- Part 1: General.

ISO/TR 15489-2:2001 Records Management -- Part 2: Guidelines.

AS 4390-1996 Records Management.

ISO 2788:1986 Guidelines for the establishment and development of monolingual thesauri.

UK Public Record Office Approved Electronic Records Management Solution.

Victorian Electronic Records Strategy (VERS) Australia.

10.4.8 E-Discovery

http//:www.uscourts.gov/ruless/Ediscovery_w_Notes.pdf

http//:www.fjc.gov/public/home.nsf/pages/196