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`Merrill Communications LLC
`d/b/a Merrill Corporation
`Exhibit 1003
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`Petition for Inter Partes Review of U.S. Patent No. 9,268,748
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`UNITED STATES PATENT AND TRADEMARK OFFICE
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`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`MERRILL COMMUNICATIONS LLC d/b/a MERRILL CORPORATION,
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`Petitioner,
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`v.
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`E-NUMERATE SOLUTIONS, INC.,
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`Patent Owner.
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`Patent No. 9,268,748
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`Issue Date: February 23, 2016
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`Title:
`SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR
`OUTPUTTING MARKUP LANGUAGE DOCUMENTS
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`DECLARATION OF ANDREW DAVID HOSPODOR, PhD
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`Petition for Inter Partes Review of U.S. Patent No. 9,268,748
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`TABLE OF CONTENTS
`INTRODUCTION ....................................................................................... 1
`I.
`QUALIFICATIONS .................................................................................... 1
`II.
`III. MATERIALS CONSIDERED ..................................................................... 4
`IV. DEFINITIONS AND STANDARDS ........................................................... 4
`V.
`STATE OF THE ART ................................................................................. 7
`VI. THE ’748 PATENT ..................................................................................... 8
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`VII. CLAIM CONSTRUCTION ......................................................................... 9
`A.
`“Semantic Tags” ................................................................................ 9
`B.
`“Mapping” ........................................................................................11
`C.
`“Validation” ......................................................................................11
`VIII. ANALYSIS OF PRIOR ART .....................................................................12
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`I, Andrew D. Hospodor, make this declaration in connection with the
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`proceeding identified above.
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`I.
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`INTRODUCTION
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`1.
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`I have been retained by counsel for Merrill Communications LLC
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`d/b/a Merrill Corporation (“Merrill”) as a technical expert in connection with the
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`proceeding identified above. I submit this declaration in support of Merrill’s
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`Petition for Inter Partes Review (“Petition”) of United States Patent No. 9,268,748
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`(“the ’748 patent”).
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`II. QUALIFICATIONS
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`2. My complete qualifications and professional experience are described
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`in my curriculum vitae, a copy of which is attached as Exhibit 1004 to the Petition.
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`Following is a brief summary of my relevant qualifications and professional
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`experience:
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`3.
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`I received a Bachelor of Science degree in Computer Engineering
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`from Lehigh University in 1981, a Master of Science degree in Computer Science
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`from Santa Clara University in 1986, and a Ph.D. in Computer Engineering from
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`Santa Clara University in 1994. My Ph.D. emphasis was in storage architecture
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`and systems. My dissertation was entitled: “A Study of Prefetch in Caching SCSI
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`Disk Drive Buffers.”
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`4.
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`I have been part of the computer industry for over 25 years and
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`involved in engineering storage, networking and processing systems. I have also
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`focused on simulation and implementation of new technologies at Quantum Corp.
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`5.
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`I have taught graduate and undergraduate courses at Santa Clara
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`University. After receiving my Master’s degree in 1986, I joined the Institute for
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`Information Storage Technology as an Adjunct Lecturer, then later as a Research
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`Fellow. I have taught courses in Computer Architecture, Storage Architecture,
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`Hard Disk and Floppy Disk Controller Design, and Grid Computing. I was most
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`recently the Executive Director of the Storage Systems Research Center at
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`University of California, Santa Cruz. There, I oversaw the research of faculty,
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`graduate students, post-doctoral scholars, and I worked with industrial sponsors in
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`the data storage industry as well as the National Science Foundation (NSF). I am
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`presently a consultant to NSF.
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`6.
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`I am a named inventor on nineteen U.S. patents. I have authored
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`numerous publications in reference journals, industry periodicals, and am often
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`cited by my peers in textbooks and journal publications. I have presented to the
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`American National Standards Institute (ANSI) committee on the Small Computer
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`Systems Interface (SCSI), the National Association of Broadcasters (NAB), the
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`SCSI Forum, the Institute of Electrical and Electronic Engineers (IEEE) Systems
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`Design and Network Conference, and many other related conferences.
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`7. My experience in the design of and implementation of systems using
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`markup languages, such as HyperText Markup Language (HTML) and Extensible
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`Markup Language (XML) began while working for Quantum Corp. in Milpitas,
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`California from 1993 to 1999. At Quantum, I managed the Operating Systems,
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`Simulation and Performance group responsible for building models of hard disk
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`drives to study the impact of new features, such as cache sizes and prefetch
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`algorithms. Quantum already used Matlab software and I explored the use of XML
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`for data exchange. I also interacted with Microsoft regarding their SQL-Server
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`database products, and their interest in optimizing data storage devices for their
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`enterprise customers. Later, in 2001, I returned to Santa Clara University to take a
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`graduate class in Advanced Database Systems that included both Software Query
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`Langage (SQL) and noSQL databases.
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`8.
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`In 2001 I was also an expert in the matter of Matlab v. Comsol, where
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`I examined source code that connected Matlab to the libraries of the Java
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`programming language. These libraries included functions for the parsing and
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`processing of XML data that form the basis of structured data interchange used in
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`many modern computer systems. In 2013, I introduced the UC-Share program for
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`sharing of genomic data, specifically the cancer data of patients, across the five UC
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`hospitals and cancer centers. UC medical centers deployed software from EPIC to
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`manage health care records that are shared as XML documents. Genomic data
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`would become an XML extension to EPIC that enables UC clinicians to view
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`whole genome sequences along with entire patient records, while UC researchers
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`would access only de-identified patient data to search for clues across patients with
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`genetically similar diseases.
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`9.
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`In summary,
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`I have a deep
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`familiarity with
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`the storage,
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`manipulation/processing/analysis, transfer, and communication of data, and had
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`first-hand experience with these technologies at and before the time the application
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`for the ʼ748 patent was filed.
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`III. MATERIALS CONSIDERED
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`10.
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`In preparing this declaration, I have reviewed, among other things, the
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`following materials: (a) the ʼ748 patent and its prosecution history; (b) Mastering
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`Access 97 published by Sybex in 1997 (“Mastering Access”); (c) The XML
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`Handbook published by Prentice Hall in 1998 (“XML Handbook”); and (d) the
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`Petition.
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`IV. DEFINITIONS AND STANDARDS
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`11.
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`I have been informed and understand that claims are construed from
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`the perspective of one of ordinary skill in the art at the time of the claimed
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`invention, and that during this proceeding, claims are to be given their broadest
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`reasonable construction consistent with the specification.
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`12.
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`I have been informed and understand that a claim is invalid because of
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`anticipation when every element of the claim is described in a single prior art
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`reference, such that the elements are arranged as required by the claim. I have
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`been informed and understand the description of a claim element in a prior art
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`reference can be express or inherent. For a prior art reference to describe a claim
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`element inherently, the claim element must be necessarily present. Probabilities
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`are not sufficient to establish inherency.
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`13.
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`I have also been informed and understand that the subject matter of a
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`patent claim is obvious if the differences between the subject matter of the claim
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`and the prior art are such that the subject matter as a whole would have been
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`obvious at the time the invention was made to a person having ordinary skill in the
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`art (POSITA) to which the subject matter pertains. I have also been informed that
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`the framework for determining obviousness involves considering the following
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`factors: (i) the scope and content of the prior art; (ii) the differences between the
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`prior art and the claimed subject matter; (iii) the level of ordinary skill in the art;
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`and (iv) any objective evidence of non-obviousness. I understand that the claimed
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`subject matter would have been obvious to one of ordinary skill in the art if, for
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`example, it results from the combination of known elements according to known
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`methods to yield predictable results, the simple substitution of one known element
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`for another to obtain predictable results, use of a known technique to improve
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`similar devices in the same way or applying a known technique to a known device
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`ready for improvement to yield predictable results. I have also been informed that
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`the analysis of obviousness may include recourse to logic, judgment, and common
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`sense available to the person of ordinary skill in the art that does not necessarily
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`require explication in any reference.
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`14.
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`In my opinion, a person of ordinary skill in the art pertaining to the
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`ʼ748 patent in the 1999 time frame would have been someone with at least a
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`bachelor’s or graduate degree in computer science, computer engineering, or a
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`related field, and at least 3 to 5 years of work experience in developing software
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`for data communication, manipulation, and reporting.
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`15.
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`I have been informed that the earliest possible relevant date for
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`considering the patentability of the claims of the ʼ748 patent is May 21, 1999. I
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`have not analyzed whether the ʼ748 patent is legally entitled to this filing date. I
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`shall refer to this time frame as the “relevant date” or the “relevant time frame.”
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`Based on my education and experience in the field of computer science set forth
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`above, I believe I am more than qualified to provide opinions about how one of
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`ordinary skill in the art by the relevant date in 1999 would have interpreted and
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`understood the ʼ748 patent and the prior art discussed below.
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`V. STATE OF THE ART
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`16. By about 1998, data communication, manipulation and reporting were
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`commonplace and well understood. Organizing data into a database using a
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`schema that defined data types present within a given document (i.e. Document
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`Type Definitions or DTDs), along with associated query languages to access the
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`database, was supported in software packages available from a variety of vendors,
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`including IBM and Microsoft. Structuring of data into a database became the basic
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`tool for large organizations to manage business-critical data and perform analysis,
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`manipulation and reporting of it. However, each vendor’s operating system, and
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`often applications running on that operating system, stored data in files with
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`different formats. This made the exchange and reporting of data tedious and time
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`consuming. Oracle subsequently introduced a new database that was not bound to a
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`particular operating system, rather, it initially supported the VAX/VMS and UNIX
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`operating systems in the 1980s. The World Wide Web Consortium (W3C) first
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`published HyperText Markup Language (HTML) (and later published eXtensible
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`Markup Language (XML)) as ISO standard 8879 in 1986. XML was immediately
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`adopted as a means to structure data outside of a database. Because XML was also
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`operating system independent, it rapidly became the preferred method for data
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`interchange. By 1998, the relevant time frame, Fortune 500 companies had
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`necessitated that their complex applications must communicate with each other
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`across their enterprise, in order to remain competitive. Although Sales,
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`Accounting, Resource Planning, Business Intelligence, Reporting and other
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`applications often came from different vendors and ran on different operating
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`systems, they could all use XML as a mechanism for structured data interchange.
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`Oracle offered their first database with complete XML support in 1999. Today,
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`even common Microsoft Office applications like Word, Excel and PowerPoint rely
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`upon XML to store structured user data in files with .docx, .xlsx and .pptx formats.
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`Likewise, the Securities Exchange Commission (SEC) has allowed publically
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`traded companies to file their 10-K statements using eXtensible Business maRkup
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`Language (XBRL) – which is based upon XML technology – since 2005.
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`Companies report XBRL filings to SEC via the Electronic Data Gathering,
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`Analysis, and Retrieval system (EDGAR).
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`VI. THE ’748 PATENT
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`17. The asserted claims of the ’748 patent are directed to an apparatus that
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`uses XML, an apparatus that contains a computer program to process XML data
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`and a method that receives, processes, outputs and stores XML data. However, the
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`ʼ748 patent lacks any description of an actual implementation. Rather, the ʼ748
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`patent focuses on abstract concepts and relies heavily upon generic figures. It lacks
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`detailed flowcharts or pseudo-code to describe the interactions of the contents
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`within the figures. One skilled in the art would realize that a generic figure of a
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`computing system is not sufficient for a POSITA to implement a “System, Method,
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`And Computer Program Product For Outputting Markup Language Documents.”
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`The ’748 patent essentially describes creating a schema for XML, something that
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`was well understood by a POSITA in the 1998 timeframe.
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`VII. CLAIM CONSTRUCTION
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`A.
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`“Semantic Tags”
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`18. Claim 1 of the ʼ748 patent includes the phrase “a plurality of
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`computer-readable semantic tags that describe a semantic meaning of the data
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`values.” Claims 11 and 19 use the term “semantic tags” repeatedly, including as
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`part of the phrase “receiving a user selection of one or more computer-readable
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`semantic tags.”
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`19. The specification of the ’748 patent includes a Glossary, which
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`defines “[t]agging” as “adding metadata.” (ʼ748 patent at 2:56; see also 15:55-56.)
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`I understand that when a patent applicant “acts as his own lexicographer” and
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`defines a term in the patent specification, that definition should be used even if it
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`conflicts with the normal meaning of the term or phrase.
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`20. The term “metadata” itself was well-known in the computer industry
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`by the 1999 timeframe. The Microsoft Computer Dictionary (4th ed. 1999) defines
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`“metadata” as “[d]ata about data.” (Microsoft Computer Dictionary at 288.) The
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`specification of the ’748 patent uses the term “metadata” consistently with that
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`definition. For example, the ʼ748 patent includes the following example of some
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`of the metadata that may be used in the system:
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`The image database 226 contains document metadata that references
`the original document table or flat file in the original database 230.
`Documentation information contained in the image database 226 is
`added to this data. It further includes line item set metadata for the
`set of line items, documentation that is typically of a more technical
`nature and applies to the line item set as a whole. Examples of such
`information is table types, field definitions (“x values”) and
`hyperlinks that apply to the line item set as a whole. (A line item set
`may be generally analogous to a table; it is a collection of line items,
`which are analogous to records in the database world.)
` (ʼ748 patent at 16:34-48 (emphasis added).)
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`21. The term “semantic” was also widely used in the computer industry
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`by the 1999 timeframe. “Semantics” is defined by Microsoft Computer
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`Dictionary (4th ed. 1999) to mean “1. In programming, the relationship between
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`words or symbols and their intended meanings.” (Microsoft Computer Dictionary
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`at 402.) The specification of the ’748 patent uses the term “semantics” in this
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`same way, to refer to the underlying meaning of data:
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`Semantics refers to the fact that RDML provides generic tags in which
`indicators of the “meaning” of the numbers, including the
`vocabularies of other SGML and XML markup languages, can be
`placed. This allows RDML to act as a “wrapper” for data from other
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`markup language documents. Semantic meaning is also conveyed in
`text-based attributes: legends, titles, labels, footnotes, etc.
`(ʼ748 patent at 46:11-18.)
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`22. Putting these terms together, the broadest reasonable interpretation of
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`“semantic tag” is “a reference that adds data describing the meaning of the data.”
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`B.
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`“Mapping”
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`23. Claims 11 and 19 include the phrase “mapping the one or more of the
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`computer-readable semantic tags to the one or more of the original values.”
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`24. The term “mapping” was well-known in the computer industry by the
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`1999 timeframe. The Microsoft Computer Dictionary (4th ed. 1999) defines
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`“map” as “[t]o translate one value into another.” (Microsoft Computer Dictionary
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`at 281.) Based on my review of the ʼ748 patent’s specification and prosecution
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`history, the patent uses “mapping” consistently with this definition. Accordingly,
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`the broadest reasonable interpretation of “mapping” is “translating one value into
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`another.”
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`C.
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`“Validation”
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`25. Claim 1 includes the phrases “validation of the at least one computer-
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`readable XML-compliant data document,” “datatype rule for validation of a type of
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`data values,” “calculation rule for validation of a calculation involving data
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`values,” and “unit rule for validation of a unit of data values.”
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`26. As with the previous terms, “validation” was well-known in the
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`computer industry by the 1999 timeframe. The Microsoft Computer Dictionary
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`(4th ed. 1999) defines “validity check” as “[t]he process of analyzing data to
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`determine whether it conforms to predetermined completeness and consistency
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`parameters.” (Microsoft Computer Dictionary at 464.) Based on my review of the
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`ʼ748 patent’s specification and prosecution history, the patent uses “validation”
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`consistently with
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`this definition.
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` Accordingly,
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`the broadest reasonable
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`interpretation of “validation” is “analyzing data to determine whether it conforms
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`to predetermined completeness and/or consistency parameters.”
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`VIII. ANALYSIS OF PRIOR ART
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`27. Mastering Access discloses the use of a commercially available
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`software database product (Microsoft Access 97) that organized, structured and
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`managed data within a database. A POSITA would have understood that the
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`Access 97 product was an executable program stored as code on a computer-
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`readable medium (such as a hard disk), loaded into memory (RAM), and run by a
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`computer processor.
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`28.
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`In the relevant timeframe, the Access 97 database could import and
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`output data in HTML format. (See Mastering Access at 125-126, 237-240.) At
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`that time, a POSITA could use free, publicly-available software, such as “The
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`Microsoft XSL processor” or “docproc,” to convert between XML and HTML.
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`(See XML Handbook at 156, 397-398.) A POSITA would have found it obvious
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`to use such tools to import XML data into the Access 97 database. A POSITA
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`would have understood that these tools could have been run as stand-alone
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`applications or could be incorporated into a database program such as Access 97
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`using standard coding, database query, or macro techniques. Such techniques are
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`discussed in Mastering Access. (See Mastering Access at 357-416 (queries), 731-
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`764 (macros), 853-868 (coding in Visual Basic for Applications).)
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`29. Both HTML and XML were derivatives of the SGML language and
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`published by
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`the same organization,
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`the World Wide Web Consortium
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`(W3C.ORG), before the relevant timeframe. (See XML Handbook at xxxix-xl.)
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`XML was designed to expand the capabilities of HTML and to provide an
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`application-independent file format to make it easier to share information between
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`different applications. (See id. at xxxv-xl.) This common origin and structure
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`would have provided a POSITA with additional motivation to convert between
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`HTML and XML (which the publicly-available tools in fact did).
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`30. The fact that a fundamental purpose of XML was to provide an
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`application-independent file format for easier sharing of information was itself
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`strong motivation for POSITAs to translate all manner of file formats into XML.
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`This is not hypothetical – as discussed, from its inception, XML has been used to
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`store all manner of data files, and has been incorporated into a wide variety of data
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`formats. Doing so would have been particularly easy (and obvious) for a program
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`like Microsoft Access that already had the ability to import and export data in
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`HTML format.
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`31. A POSITA desiring to add XML file support and functionality to a
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`program like Microsoft Access would look to well-regarded publications about
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`XML and its applications, such as The XML Handbook. Thus, a POSITA would
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`have been motivated (and it would have been obvious) to add the XML features
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`and functionality taught by The XML Handbook to expand the set of file types
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`compatible with the Access 97 software described in Mastering Access.
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`32. Conversely, The XML Handbook teaches embedding SQL database
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`queries in an XML document to access and pull data from a SQL database. (See,
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`e.g., XML Handbook at 248-249 and Figure 18-3.) A POSITA seeking to
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`implement the teachings of The XML Handbook would look to known databases
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`supporting SQL queries to do so. Microsoft Access is one such SQL database
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`platform. (See, e.g., Mastering Access at 186 (“An SQL statement is an expression
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`that defines an SQL (Structured Query Language) command. Access uses SQL
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`statements behind the scenes to interpret any queries you create in the query design
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`window.”).) The XML Handbook thus provides an express motivation to be
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`combined with references describing the structure and operation of SQL databases,
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`like Mastering Access.
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`33. Mastering Access teaches that the Access 97 software can import or
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`link database records from tables stored in text, spreadsheet, HTML, or other
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`database files. (See Mastering Access at 209-240.) When Access imports or links
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`a table, each row in the table corresponds to an individual record (except the first
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`row, which may be used to specify the field names), and the columns correspond to
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`the individual data fields within each record.
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`34. The difference between importing and linking data is that an imported
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`table is copied into the Access database. In contrast, a linked data source is read
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`by Access from its original location. (See Mastering Access at 219-239.) If the
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`data in a linked data source is changed, Access will read the changed data the next
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`time it looks up the information from the data source. Mastering Access teaches
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`that Access 97 could create similar dynamic links in output documents, such as
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`reports or tables published to the World Wide Web. (See id. at 126, 247-250.)
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`Those dynamically-linked documents would execute a query back to Access to
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`obtain fresh data whenever they were browsed. (See id.)
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`35. Mastering Access also teaches outputting data from the database as
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`“reports.” (See Mastering Access at 445-472.) The “report” described in
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`Mastering Access is actually a set of dynamic instructions or template for building
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`the final reporting document that a casual recipient might call a “report.” (See id.)
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`Mastering Access teaches “previewing” and “printing” the report in order to view a
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`static instance of the report. (See, e.g., id. at 470-471.) The report itself remains
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`dynamic, and can be modified to present the data in different ways the next time it
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`is previewed or printed. (See id.) A POSITA would have understood that if a
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`report was based on a linked source document, and the data in the source document
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`changed, Access would pull the updated data from the source document and
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`include it in the next instance of the report when the report was printed or
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`previewed.
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`36. Mastering Access explains that “a database can contain many tables.”
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`(Mastering Access at 43.) One of the advantages to storing information in multiple
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`tables within the database is that “it’s easier to manage data if all the information
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`about a particular subject is in its own table.” (Id.) A POSITA would have
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`understood that the instructions provided in Mastering Access to importing and
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`linking data from external tables (text, spreadsheet, HTML, etc.) could simply be
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`repeated to add multiple tables to the database.
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`37. Mastering Access explains that Access 97 can perform operations on
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`the data in database records by using field names to identify the specific data fields
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`at issue. For example, Mastering Access describes the creation of “a macro that
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`adds 7.75 percent sales tax to a total sale but only if the sale is made in the state of
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`California.” (Mastering Access at 742.) The database records for this example
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`contain fields named “State,” “SubTotal,” “SalesTaxRate,” “SalesTax,” and
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`“TotalSale,” the last two of which are “calculated fields.” (Id.) Mastering Access
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`teaches that the macro initially sets the “SalesTaxRate” value for each record to 0,
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`and then subsequently changes that value to 0.775 for the subset of records tagged
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`with “CA” in the “State” field. (See id. at 744.) A POSITA would have
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`understood that Access recognizes the sales tax rate associated with a particular
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`subtotal based on the field name, as well as the two-letter state identifier stored in
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`the “State” field of each record.
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`38.
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`In another example, Mastering Access teaches the use of database
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`queries to select records based on field names and other tags. (See Mastering
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`Access at 357-442.) Figure 10.2 in Mastering Access illustrates the creation of a
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`query that “[s]elect[s] records in which the order was placed in February 1997 and
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`the quantity times the unit price ([Quantity] *[Order Details]! [Unit Price]) is
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`greater than $75.” (Id. at 364.) In this example, the field names “OrderDate,”
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`“Quantity,” and “UnitPrice” are all semantic tags identifying the meaning of the
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`associated data. The query selects records based on the values associated with
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`those tags.
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`39.
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`In yet another example, Mastering Access teaches that a user may
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`select a semantic tag, such as a “Last Name” data field name, by clicking on any
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`data associated with that tag. (See Mastering Access at 74.) Once the selection has
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`been made, a user may perform operations on the records containing data
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`associated with the selected tag, such as executing a “Sort Ascending” command to
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`sort the records alphabetically by last name. (See id.)
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`40. Similarly, Mastering Access teaches that a user may select data, such
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`as the value “WA” in a “State/Province” field, by clicking on it. (See Mastering
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`Access at 74.) Once the selection has been made, a user may perform operations
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`on the records containing that data value associated with the same tag, such as
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`executing a “Filter By Selection” command to display only the records with WA in
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`the “State/Province” field. (See id.)
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`41. Mastering Access teaches that the database records (the line items in a
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`database table) may have multiple hierarchical relationships between them. (See
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`Mastering Access at 422-426.) For example, Figure 11.5 shows a database form
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`graphically illustrating the hierarchy within a database between line items for a
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`business’s customers, orders, and order details. (See id. at 423.) Each customer
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`line item may be associated with multiple order line items (each customer places
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`multiple orders), and each order line item may be associated with multiple “order
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`detail” line items (a single order may be for multiple different products). (See id.)
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`While this example is presented using “one-to-many” database relationships (a link
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`from one line item connects to multiple other line items), a POSITA would
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`understand that the teaching applies equally to simpler “one-to-one” relationships
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`(each link connects to only one other line item).
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`42. Mastering Access also teaches the use of validation rules, which were
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`well known in computer programming long before the 1999 timeframe. (See, e.g.,
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`Mastering Access at 166-167, 239-241, 298-299, 1067-1068.) For example,
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`Mastering Access teaches that Access will report an error in the “ImportErrors”
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`table for an imported document if “[t]he data in a text file or spreadsheet field is
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`the wrong type for the corresponding table field. For instance, the table field may
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`be a Currency type, but the data contain a person’s name.” (Id. at 241; see also,
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`e.g., id. at 298.) This operation validates both the data type (e.g., currency) and the
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`acceptable units for that data type (a text string is not an acceptable unit of
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`currency).
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`43. Similarly, Mastering Access teaches the use of validation rules to
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`identify fields in a record being imported that contain data whose values are out of
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`bounds for the acceptable limits of the corresponding data field. For example,
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`Mastering Access teaches that Access will report an error in the “ImportErrors”
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`table for the imported document if “[t]he data in a numeric field is too large for the
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`field size of a table field. For example, Access can’t import a record if the table
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`field has a Field Size property of Byte but the data contains a value greater than
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`255.” (See Mastering Access at 241.)
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`44. Mastering Access also teaches the creation of additional validation
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`rules for particular fields by a user, along with corresponding “Validation Text”
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`error messages. (See, e.g., Mastering Access at 166-167, 299, 1067-1068.)
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`“Validation rules put limits on a field or form, such as insisting that a control
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`contain data, be greater than a minimum value, or that two or more fields contain
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`data that is not mutually exclusive.” (Id. at 1067.) A POSITA would have
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`understood that any of these validation rules is equally applicable to fields in which
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`the user manually enters data, fields containing data imported from external source
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`documents, and fields containing values calculated by Access based on other
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`fields.
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`45. The XML Handbook, authored by Charles Goldfarb, the inventor of
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`SGML and Paul Prescod, a member of the of the World Wide Web Consortium
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`XML team, describes what a markup language is, what XML is, how it works, and
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`its advantages to uses of the World Wide Web. (See generally XML Handbook;
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`see also id. “About the Authors” (back cover).) The XML Handbook teaches the
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`structure and function of XML. (See, e.g., id. at 33-47.) For example, The XML
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`Handbook explains that XML is used for digital representation of documents,
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`using “elements” to represent the logical components of a document, “attributes”
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`to describe properties of the ele
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