David Mizell

Patent Trials and Appeals Board

Dec 11, 2019

13827321 - (D) (P.T.A.B. Dec. 11, 2019)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
13/827,321 03/14/2013 David Mizell 0324758080US 1516
25096 7590 12/11/2019
PERKINS COIE LLP - SEA General
PATENT-SEA
P.O. BOX 1247
SEATTLE, WA 98111-1247
EXAMINER
ZHAO, YU
ART UNIT PAPER NUMBER
2169
NOTIFICATION DATE DELIVERY MODE
12/11/2019 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
patentprocurement@perkinscoie.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte DAVID MIZELL
____________

Appeal 2018-004092
Application 13/827,321
Technology Center 2100
____________

Before MAHSHID D. SAADAT, ERIC B. CHEN, and CARL L.
SILVERMAN, Administrative Patent Judges.

SAADAT, Administrative Patent Judge.

DECISION ON APPEAL1

Pursuant to 35 U.S.C. § 134(a), Appellant2 appeals from the
Examiner’s decision to reject claims 1, 7, and 13, which are all the claims
pending in this application. We have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.

1 An oral hearing scheduled on November 5, 2019, for this appeal has been
waived.
2 We use the word “Appellant” to refer to “applicant” as defined in
37 C.F.R. § 1.42(a) (2017). Appellant identifies the real party in interest as
Cray, Inc. Appeal Br. 1.
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STATEMENT OF THE CASE
Introduction
Appellant’s disclosure is directed to a system that submits a query in
Simple Protocol and RDF Query Language (SPARQL) – a query language
developed for sematic databases that comply with Resource Description
Framework (RDP) format. See Spec. ¶ 3. The disclosed system allows non-
SPARQL systems to interface with SPARQL front ends without needing a
separate mapper for each SPARQL system. See Spec. ¶ 8.
Claim 1 is illustrative of the invention and reads as follows:
1. A computing system for executing SPARQL
Protocol and Resource Description Framework ("RDF") Query
Language ("SPARQL") queries generated by a SPARQL
system, the SPARQL system having a SPARQL front end and a
SPARQL query engine, the computing system comprising:
an RDF data store;
a non-SPARQL query engine that
receives commands in a format specific to the non-
SPARQL query engine, the commands for
accessing the RDF data store;
performs instructions for accessing the RDF data
store in accordance with the commands; and
provides results of accessing the RDF data store;
and
a translated SPARQL processor that
receives from the SPARQL query engine a
translated SPARQL query representation of a
SPARQL query, the translated SPARQL query
expressed using a SPARQL algebra;
processes the translated SPARQL query to
generate commands in a format specific to the non-
SPARQL query engine, the commands for
directing the non-SPARQL query engine to access
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the RDF data store for execution of the SPARQL
query;
sends to the non-SPARQL query engine the
generated commands;
receives from the non-SPARQL query engine
results of the generated commands; and
provides the results to the SPARQL front end
wherein the translated SPARQL processor is adapted to
execute SPARQL queries for different types of SPARQL
systems that output translated SPARQL queries expressed in
the SPARQL algebra.
Appeal Br. 20 (Claims App.).
The Examiner’s Rejections
Claim 1 stands rejected under 35 U.S.C. § 101 as directed to non-
statutory subject matter. See Non-final Act. 6–7.
Claims 1, 7, and 13 stand rejected under 35 U.S.C. § 103(a) as being
unpatentable over Krishnamoorthy (US 2009/0138437 A1; pub. May 28,
2009), Liu (US 2011/0295906 A1; pub. Dec. 1, 2011), Elliott (A Complete
Translation from SPARQL into Efficient SQL, July 9, 2009), and ARQtick
(Basic Federated SPARQL Query, July 27, 2007). See Non-final Act. 8–17,
24.
ANALYSIS
SECTION 101 REJECTION
We have reviewed the Examiner’s rejection in light of Appellant’s
contentions and the evidence of record. We concur with Appellant’s
contention that the Examiner erred.
Rejection and Arguments
The Examiner finds claim 1 recites elements such as a computing
system, a SPARQL system, SPARQL front end, SPARQL query engine,
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translated SPARQL processor, non-SPARQL query engine, and RDF data
store, which “would lead one of ordinary skill to the conclusion that the
‘system,’ ‘engine,’ ‘processor’ and ‘data store’ as used in claim 1 are
software or program or a person.” Non-final Act. 7. The Examiner further
explains:
The claims lack the necessary physical articles or objects
to constitute a machine or a manufacture within the meaning of
35 USC 101. They are clearly not a series of steps or acts to be
a process nor are they a combination of chemical compounds to
be a composition of matter. As such, they fail to fall within a
statutory category. They are, at best, functional descriptive
material per se.
Applicant is suggested to include at least one hardware
component (e.g. computer processor and computer memory)
and explain how the at least one hardware component can be
utilized within the claimed system.
Id.
Appellant contends the recited computing system is described in the
Specification as including “a central processing unit and local memory,” and
therefore, “[o]ne skilled in the art would understand upon reading
appellant’s specification that a ‘computing system’ is a machine.” Appeal
Br. 6 (citing Spec. ¶ 15). According to Appellant, the claim does recite
hardware components, as required by the Examiner, such as a “data store” or
memory. Appeal Br. 7. Appellant adds that the applied prior art,
Krishnamoorthy, describes a similar computing system having an RDF data
store, which implies that such data store is “a hardware repository for storing
the RDF graphs.” Appeal Br. 7–8.
Legal Principles
Section 101 of the Patent Act provides “[w]hoever invents or
discovers any new and useful process, machine, manufacture, or
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composition of matter, or any new and useful improvement thereof, may
obtain a patent therefor, subject to the conditions and requirements of this
title.” 35 U.S.C. § 101. However, the Supreme Court has long interpreted
35 U.S.C. § 101 to include implicit exceptions: “[l]aws of nature, natural
phenomena, and abstract ideas” are not patentable. E.g., Alice Corp. Pty.
Ltd. v. CLS Bank Int’l, 573 U.S. 208, 216 (2014) (internal quotation marks
and citation omitted).
In determining whether a claim falls within an excluded category, we
are guided by the Supreme Court’s two-step framework, described in Mayo
and Alice. Id. at 217–18 (citing Mayo Collaborative Servs. v. Prometheus
Labs., Inc., 566 U.S. 66, 75–77 (2012)). In accordance with that framework,
we first determine what concept the claim is “directed to.” See Alice, 573
U.S. at 219 (“On their face, the claims before us are drawn to the concept of
intermediated settlement, i.e., the use of a third party to mitigate settlement
risk.”); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) (“Claims 1 and 4
in petitioners’ application explain the basic concept of hedging, or protecting
against risk.”).
Concepts determined to be abstract ideas, and, thus, patent ineligible,
include certain methods of organizing human activity, such as fundamental
economic practices (Alice, 573 U.S. at 219–20; Bilski, 561 U.S. at 611);
mathematical formulas (Parker v. Flook, 437 U.S. 584, 594–95 (1978)); and
mental processes (Gottschalk v. Benson, 409 U.S. 63, 67 (1972)). Concepts
determined to be patent eligible include physical and chemical processes,
such as “molding rubber products” (Diamond v. Diehr, 450 U.S. 175, 191
(1981)); “tanning, dyeing, making water-proof cloth, vulcanizing India
rubber, smelting ores” (id. at 182 n.7 (quoting Corning v. Burden, 56 U.S.
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252, 267–68 (1853))); and manufacturing flour (Benson, 409 U.S. at 69
(citing Cochrane v. Deener, 94 U.S. 780, 785 (1876))).
In Diehr, the claim at issue recited a mathematical formula, but the
Supreme Court held that “a claim drawn to subject matter otherwise
statutory does not become nonstatutory simply because it uses a
mathematical formula.” Diehr, 450 U.S. at 187; see also id. at 191 (“We
view respondents’ claims as nothing more than a process for molding rubber
products and not as an attempt to patent a mathematical formula.”). Having
said that, the Supreme Court also indicated that a claim “seeking patent
protection for that formula in the abstract . . . is not accorded the protection
of our patent laws, . . . and this principle cannot be circumvented by
attempting to limit the use of the formula to a particular technological
environment.” Id. (citing Benson and Flook); see, e.g., id. at 187 (“It is now
commonplace that an application of a law of nature or mathematical formula
to a known structure or process may well be deserving of patent
protection.”).
If the claim is “directed to” an abstract idea, we turn to the second
step of the Alice and Mayo framework, where “we must examine the
elements of the claim to determine whether it contains an ‘inventive
concept’ sufficient to ‘transform’ the claimed abstract idea into a
patent-eligible application.” Alice, 573 U.S. at 221 (citation omitted). “A
claim that recites an abstract idea must include ‘additional features’ to
ensure ‘that the [claim] is more than a drafting effort designed to
monopolize the [abstract idea].’” Id. (quoting Mayo, 566 U.S. at 77).
“[M]erely requir[ing] generic computer implementation[] fail[s] to transform
that abstract idea into a patent-eligible invention.” Id.
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The PTO recently published revised guidance on the application of
§ 101. USPTO, 2019 REVISED PATENT SUBJECT MATTER ELIGIBILITY
GUIDANCE, 84 Fed. Reg. 50 (Jan. 7, 2019) (“Guidance”). Under the
Guidance, we first look to whether the claim recites:
(1) any judicial exceptions, including certain groupings of
abstract ideas (i.e., mathematical concepts, certain methods of
organizing human activity such as a fundamental economic
practice, or mental processes) (Step 2A, Prong 1); and
(2) additional elements that integrate the judicial exception into
a practical application (see MANUAL OF PATENT EXAMINING
PROCEDURE (“MPEP”) § 2106.05(a)–(c), (e)–(h)) (9th Ed., Rev.
08.2017, 2018) (Step 2A, Prong 2).
Only if a claim (1) recites a judicial exception and (2) does not integrate that
exception into a practical application, do we then look to whether the claim:
(3) adds a specific limitation beyond the judicial exception that
is not “well-understood, routine, conventional” in the field (see
MPEP § 2106.05(d)); or
(4) simply appends well-understood, routine, conventional
activities previously known to the industry, specified at a high
level of generality, to the judicial exception. (Step 2B.)
See Guidance, 84 Fed. Reg. at 54–56.
Discussion
Claim 1 recites functions performed by a “non-SPARQL query
engine” including receiving “commands in a format specific to the non-
SPARQL query engine,” performing “instructions for accessing the RDF
data store,” and providing “results of accessing the RDF data store.”
Additional functions are recited that are performed by “a translated
SPARQL processor” such as receiving “translated SPARQL query
expressed using a SPARQL algebra,” processing “the translated SPARQL
query to generate commands in a format specific to the non-SPARQL query
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engine, the commands for directing the non-SPARQL query engine to access
the RDF data store for execution of the SPARQL query,” sending the
generated commands to the non-SPARQL query engine, and providing the
received “results of the generated commands” to the “SPARQL front end.”
Claim 1 also recites that the translated SPARQL processor “is adapted to
execute SPARQL queries for different types of SPARQL systems that
output translated SPARQL queries expressed in the SPARQL algebra.” See
Appeal Br. 20 (Claims App.).
Even if the recited functionalities shown above are directed to an
abstract idea (such as mental processes recited in the limitations related to
receiving commands, performing instructions, and providing results), the
Federal Circuit explains the “directed to” inquiry is not simply asking
whether the claims involve a patent-ineligible concept:
The “directed to” inquiry . . . cannot simply ask whether the
claims involve a patent-ineligible concept, because essentially
every routinely patent-eligible claim involving physical products
and actions involves a law of nature and/or natural
phenomenon—after all, they take place in the physical world.
See Mayo, 132 S. Ct. at 1293 (“For all inventions at some level
embody, use, reflect, rest upon, or apply laws of nature, natural
phenomena, or abstract ideas.”). Rather, the “directed to”
inquiry applies a stage-one filter to claims, considered in light of
the specification, based on whether “their character as a whole is
directed to the excluded subject matter.”
Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir. 2016); see
also Diehr, 450 U.S. at 188 (“In determining the eligibility of respondents’
claimed process for patent protection under § 101, their claims must be
considered as a whole.”); McRO, Inc. v. Bandai Namco Games Am. Inc., 837
F.3d 1299, 1314 (Fed. Cir. 2016) (the question is whether the claims as a
whole “focus on a specific means or method that improves the relevant
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technology or are instead directed to a result or effect that itself is the
abstract idea and merely invoke generic processes and machinery”).
Therefore, we proceed to Step 2A, Prong 2 of the Guidance to
determine whether additional elements of claim 1 integrate an abstract idea,
such as mental processes, into a practical application. Such additional
elements may reflect an improvement to a technology or technical field. See
Guidance, 84 Fed. Reg. at 55. Here we look to see if, for example, (i) any
additional elements of the claims reflects an improvement in the functioning
of a computer or to another technological field, (ii) an application of the
judicial exception with, or by use of, a particular machine, (iii) a
transformation or reduction of a particular article to a different state or thing,
or (iv) a use of the judicial exception in some other meaningful way beyond
generally linking the use of the judicial exception to a particular
technological environment. See MPEP § 2106.05(a)–(c), (e)–(h).
We determine additional elements of claim 1 integrate the abstract
idea into a practical application, because those elements (“an RDF data
store,” “a non-SPARQL query engine that receives commands in a format to
specific to the non-SPARQL query engine, . . .; performs instructions for
accessing the RDF data store . . .; provides results . . .;” and “a translated
SPARQL processor that “receives . . . SPARQL query expressed using
SPARQL algebra; processes the translated SPARQL query to generate
commands in a format specific to the non-SPARQL query engine, . . .; sends
to the non-SPARQL query engine the generated command; receives . . . the
results of the generated commands; and provides the results to the SPARQL
front end”) reflect specific technology improvements. In fact the recited
elements enable a user of a SPARQL system that may not have the data
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storage capacity and computational power to continue using the SPARQL
front end and RDF data store. See claim 1, Spec. ¶ 5. The recited elements
provide a solution that exists in the interface between the SPARQL query
engines and RDF data stores, which is rooted in computer technology. See
DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1257 (Fed. Cir.
2014) (holding the claims satisfy Alice step two because “the claimed
solution is necessarily rooted in computer technology in order to overcome a
problem specifically arising in the realm of computer networks”).
Appellant’s Specification supports our determination by describing
the prior art problem of the interfaces between the SPARQL query engines
and their RDF data stores:
To meet their changing needs, users may want to
replace their existing query engine and RDF data store with a
more powerful system. These more powerful systems, however,
may provide a query engine that is not compatible with the user’s
SPARQL front end and may not even be designed to handle
SPARQL queries. The interfaces between the SPARQL query
engines and their corresponding SPARQL front ends typically
use very different protocol. Thus, one SPARQL query engine
could not be substituted for another. Similarly, the interfaces
between the SPARQL query engines and their RDF data stores
may also use very different protocols and one RDF data store
could not be substituted for another. Figure 2 is a block diagram
that illustrates one approach for allowing the use of a SPARQL
front end with a powerful non-SPARQL query engine. A
SPARQL front end 211 and a SPARQL query engine 212 are
components of one SPARQL system, and a SPARQL front end
221 and a SPARQL query engine 222 are components of another
SPARQL system. Since the interfaces between the SPARQL
query engines and their RDF data stores are not compatible with
each other, mappers 213 and 223 need to be developed to map
their commands to the commands of non-SPARQL query engine
250 and its RDF data store 260. The mappers also need to be
able to translate the results of the non-SPARQL query engine to
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the format expected by the corresponding SPARQL query
engine. Mappers could also be developed to interface a
SPARQL front end with the non-SPARQL query engine without
using the SPARQL query engine.
Spec. ¶ 6.
Figure 3 is a block diagram that illustrates a tSPARQL
processor interfacing with various SPARQL systems. A
tSPARQL processor 300 receives tSPARQL queries that are
output by various SPARQL query engines 212 and 222. The
tSPARQL processor translates the tSPARQL query into
commands for the non-SPARQL query engine 250, which
accesses RDF data store 260. When the non-SPARQL query
engine receives the results, it provides them to the appropriate
SPARQL front end 211 and 221.
. . .
The command generated by the tSPARQL processor may be
implemented as an invocation of a function of an application
programming interface (“API”) provided by the non-SPARQL
query engine.
Spec. ¶ 14.
Because the additional elements of claim 1 integrate an abstract
idea, such as mental processes, into a practical application, we determine
claim 1 is not directed to an abstract idea. See Guidance, Step 2A, Prong
2. For similar reasons, each of claims 7 and 13 integrates the mental
processes into a practical application, and is not directed to an abstract
idea.
Therefore, we do not sustain the rejection of claims 1, 7, and 13 under
35 U.S.C. § 101.
SECTION 103 REJECTION
We disagree with Appellant’s arguments, and agree with and adopt
the Examiner’s findings and conclusions in (i) the action from which this
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appeal is taken (Non-final Act. 8–24) and (ii) the Answer (Ans. 3–8) to the
extent they are consistent with our analysis below.
Claim 1
Appellant contends that the Examiner “provides no explanation as to
the relevance of the quoted language of a reference to the quoted claim
language” nor “established even a prima facie case that the claims are
obvious.” Appeal Br. 12–13. Additionally, Appellant argues the Examiner
“fails to provide any explanation as to how one reference could possibly be
modified based on the teaching of another reference so as to have the
advantage claimed by the other reference. Appeal Br. 13. In particular,
Appellant argues:
Paragraphs 0050-51 describe converting “SPARQL
queries into native SQL query language of the RDF data store.”
Thus, the paragraphs describe SPARQL queries and SQL
queries. Clearly, Krishnamoorthy’s SPARQL query corresponds
to the claimed SPARQL query. It is not clear, however, whether
the Examiner is taking the position that Krishnamoorthy’s SQL
query corresponds to the claimed “translated SPARQL query” or
the generated “commands.”
. . .
But, whatever position the Examiner may take, it is clear that
Krishnamoorthy’s SQL query cannot correspond to both a
“translated SPARQL query” and generated “commands,” which
are distinct claim elements. If Krishnamoorthy’s query were to
correspond to both, then Krishnamoorthy would need to describe
“process[ing] the [SQL query] to generate [SQL queries] in a
format specific to the non-SPARQL query engine.”
Appeal Br. 16–18; see also Reply Br. 3–4. Appellant further argues
Krishnamoorthy “actually does describe a non-SPARQL query engine” and
“directly converts a SPARQL query to an SQL query,” which makes it
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unclear as to how adding a SPARQL query engine would improve the
system of Krishnamoorthy. See Appeal Br. 15; Reply Br. 5.
Appellant has not persuaded us of error. First, the Examiner finds
Krishnamoorthy is relied on as disclosing the recited computing system for
executing SPARQL protocol in searching an RDF data store Non-final
Act. 8 (citing Krishnamoorthy ¶ 39)) wherein a non-SPARQL query engine
receives commands and performs instructions for accessing an RDF data
store and providing the results (Non-final Act. 8–11 (citing Krishnamoorthy
¶¶ 50, 51, Figs. 7–9)). Similarly, the Examiner finds Krishnamoorthy
discloses a translated SPARQL processor that receives and processes the
translated SPARQL query to generate a command for accessing the RDF
data store and executing the SPARQL query (Non-final Act. 11–14 (citing
Krishnamoorthy ¶¶ 50, 51, 54, Figs. 7–9)). The Examiner relies on Liu as
disclosing the translated SPARQL query, and on Elliott as disclosing the
SPARQL queries that are expressed in the SPARQL algebra by
implementing SPARQL algebra operator. Non-final Act. 14–16 (citing Liu
¶ 19 and Elliott pp. 31–32). Finally, the Examiner finds ARQtick discloses
executing “SPARQL queries for different types of SPARQL systems that
output translated SPARQL queries expressed in the SPARQL algebra.”
Non-final Act. 16–17 (citing ARQtick pp. 2–3); see also Ans. 3–4
(discussing Liu and Elliott). Therefore, the Examiner has mapped the
claimed limitations to the specific portions of the applied prior art.
Second, the Examiner has explained how the proposed modifications
to Krishnamoorthy would have been obvious to one of ordinary skill in the
art, based on the cited teachings of the references. For example, the
Examiner finds the transformed queries taught in Liu would improve the
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conversion of SPARQL queries to SQL (non-SPARQL) format or
processing “the translated SPARQL query to generate commands in a format
specific to the non-SPARQL query engine” in Krishnamoorthy. Non-final
Act. 14–15; Ans. 3. Additionally, the Examiner reasons that adding the
teachings of Elliott with respect to expressing the translated SPARQL query
using a SPARQL algebra results in generating efficient SQL queries. Non-
final Act. 15–16; Ans. 3–4. By adding ARQtick, the Examiner further finds
the converted SPARQL queries of Krishnamoorthy would have additional
enhanced capabilities and reduced network traffic. Non-final Act. 16–17.
Appellant’s arguments challenging the proposed combination of the
references are unpersuasive, because they are not directed to the Examiner’s
specific findings. The Examiner cites specific portions of each reference for
teaching or suggesting the disputed limitation with sufficient details and
states a reasonable rationale for combining those teachings. See Non-final
Act. 8–17.
Appellant’s argument that Krishnamoorthy cannot disclose both a
translated SPARQL query and the command for execution of a SPARQL
query (Appeal Br. 13–14) is also unpersuasive. We agree with the
Examiner’s finding that the claim recites the processor “processes the
translated SPARQL query to generate commands in a format specific to the
non-SPARQL query engine,” and not receiving or generating both
commands and the translated query together and as separate entities. See
Ans. 4. We also agree with the Examiner that the “SQL query contains the
execution commands,” which implies the translated SPARQL query includes
the search commands or suggests that such commands are generated as the
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converted SPARQL query is processed. Id. 3 In other words, a query
conversion engine 120 provides the translated SPARQL query by converting
SPARQL queries to native SQL queries which performs the query such that
the RDF data store is accessed. See Krishnamoorthy ¶ 51.
Appellant’s argument (Appeal Br. 14–15) that the proposed
combination is in error because Krishnamoorthy avoids using a SPARQL
query engine, is also unpersuasive. As explained by the Examiner, “[u]nder
the broadest reasonable interpretation, ‘SPARQL query engine’ can be
broadly interpreted as any device in combination of software that can
process SPARQL query engine.” Ans. 6. As such, the Examiner correctly
finds that Krishnamoorthy’s query conversion engine, together with the
incoming SPARQL queries, meet the recited limitation. Id. (citing
Krishnamoorthy Fig. 1, ¶ 63). That is, the conversion engine must receive
SPARQL queries from a SPARQL query engine before the translation to
non-SPARQL query takes place.
Similarly, we are unpersuaded by Appellant’s contention that one of
ordinary skill in the art would not have added a SPARQL query engine, as
disclosed in Liu, to Krishnamoorthy. See Appeal Br. 15–16. We agree with
the Examiner’s rationale that because converting the SPARQL queries is
taught by Krishnamoorthy, adding the teachings of Liu with respect to the
functions of a SPARQL query engine would have been obvious to one of

3 The Examiner alternatively cites Krishnamoorthy’s paragraph 63 as further
disclosing how the SPARQL query is converted to SQL query which
contains commands for performing the query. Additionally, the Examiner
finds Elliott discusses using a SPARQL algebra for SQL-based algorithms
which implies including commands the SQL statements that are processed
by the query engine. Ans. 5.
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ordinary skill in the art because RDL data stores can be more accessible
when SPARQL queries are received and then processed to be converted to
SQL queries.
Regarding Appellant’s argument that Krishnamoorthy and Elliott
cannot be combined because both convert SPARQL queries to SQL queries,
we are also unpersuaded. See Appeal Br. 16–17. The Examiner responds
that the proposed combination would have improved the conversion taught
in Krishnamoorthy because “Elliott discloses during converting SPARQL
query to SQL query, converting SPARQL with SPARQL algebra, then to
SQL query is more efficient.” Ans. 7. We agree.
With respect to the teachings of ARQtick, we are also unpersuaded by
Appellant’s argument that the algebra taught in ARQtick is used internally
when the SPARQL query is sent to a remote device, but does not send the
algebra. Appeal Br. 17. As explained by the Examiner, ARQtick discloses
using extended algebra for building a query to access remote RDF data,
which, together with Elliott, suggest using SPARQL algebra on different
types of SPARQL systems, such as those using extended and non-extended
algebra. See Ans. 7–8.
On this record, we are unpersuaded that the Examiner has erred in
concluding that the combination of Krishnamoorthy, Liu, Elliott, and
ARQtick renders independent claim 1 obvious.
Remaining Claims
Independent claims 7 and 13 recite limitations similar to those of
claim 1. Appellant argues the rejection of claims 7 and 13 based on
reasoning similar to those discussed above. For similar reasons stated for
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the rejection of claim 1, we are unpersuaded of Examiner error in rejecting
claims 7 and 13.
DECISION SUMMARY
In summary:
Claims
Rejected
35 U.S.C.
§
Reference(s)/Basis Affirmed Reversed
1, 7, 13 § 101 Eligibility 1, 7, 13
1, 7, 13 § 103 Krishnamoorthy,
Liu, Elliott,
ARQtick
1, 7, 13
Overall
Outcome
1, 7, 13

FINALITY AND RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(1)(iv).
AFFIRMED