Patent application EP20178735A (EP), filed 2020-06-08
Publication number: EP3748516A1
Title: TIME SERIES DATABASES
Abstract: Method and systems, performed by one or more processors, are disclosed. A method, performed by one or more processors, may comprise receiving a query for performing one or more computational operations on one or more multi-dimensional data sets representing multi-dimensional time series data collected in real-time from one or more sensors associated with one or more technical systems. The method may also comprise identifying the location of the one or more multi-dimensional time series data sets in one or more databases, retrieving the one or more multi-dimensional time series data sets from the identified one or more databases, and performing the one or more computational operations on the retrieved one or more multi-dimensional time series data sets. The method may also comprise generating output based on the result of the one or more computational operations indicative of one or more states of the one or more technical systems with respect to time.
IPC codes: G06F  16/  2458            A I
G06F  16/    28            A I
Claims: number: 1
text: A method, performed by one or more processors, the method comprising:
number: 2
text: The method of claim 1, performed by a middleware analysis platform, independently of real-time data collection by the one or more multi-dimensional databases.
number: 3
text: The method of claim 2, wherein the middleware analysis platform performs retrieval and computation substantially in real time from receiving the query.
number: 4
text: The method of claim 2, wherein the middleware analysis platform identifies the location of the one or more multi-dimensional time series data sets in the one or more databases by accessing metadata associated with the one or more multi-dimensional time series data sets in the one or more databases, said one or more databases being pre-registered with the middleware analysis platform, the metadata including an identifier of the one or more multi-dimensional time series data sets and their respective storage location in the one or more databases.
number: 5
text: The method of claims 2 to 4, wherein middleware analysis platform converts the received query into an expression for performing the one or more computational operations locally.
number: 6
text: The method of any of claims 2 to 5, wherein the middleware analysis platform generates multi-dimensional output from the one or more computations which are presented on one or more multi-dimensional graphs.
number: 7
text: The method of claim 6, wherein a plurality of multi-dimensional graphs are presented, representing a sequence of time slices.
number: 8
text: The method of any preceding claim, wherein the one or more computations include one or more of correlation, regression and derivatives.
number: 9
text: The method of any preceding claim, further comprising monitoring the output against an predetermined condition, and issuing an alert and/or performing an automatic operation on the one or more technical systems responsive to the condition being detected.
number: 10
text: The method of any preceding claim, further comprising:
number: 11
text: The method of claim 11, wherein the real-time streaming data comprises a plurality of streams, each associated with a respective sensor, the respective dimension relating to a time-varying quantity or parameter measured or detected by the sensor at a plurality of time intervals.
number: 12
text: The method of any of claims 11 to 13, wherein parsing comprises structuring the real-time streaming data using an ontology associated with the respective sensor from which the streaming data is received, prior to storing in the one or more time series databases, and, optionally, wherein the receiving, parsing and storing is performed substantially in real time.
number: 13
text: The method of any of claims 10 to 12, further comprising storing the received real-time streaming data, prior to parsing, in a cold storage means and, in response to subsequently identifying one or more sets of missing data stored in the one or more time series databases, identifying and retrieving data corresponding to the missing data from the cold storage means and inserting said retrieved data into the parsed data to provide updated data in the time series databases.
number: 14
text: A computer program, optionally stored on a non-transitory computer readable medium program which, when executed by one or more processors of a data processing apparatus, causes the data processing apparatus to carry out a method according to any preceding claim.
number: 15
text: Apparatus configured to carry out the method according to any preceding claim, the apparatus comprising one or more processors or special-purpose computing hardware.
Office action: search_report, dated 2020-12-09
Rejection reasons: novelty_epc_54
Prior art cited: ref_id: EP3444733A1
ref_type: patent
severity: background
ref_id: US2018293284A1
ref_type: patent
severity: background
ref_id: EP2779082A1
ref_type: patent
severity: background
ref_id: - SHUAI ZHANG ET AL: "Semantically Enhanced Time Series Databases in IoT-Edge-Cloud Infrastructure", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 10 February 2019 (2019-02-10), pages 1 - 12, XP081027330
ref_type: npl
severity: background
ref_id: EP2779082
ref_type: patent
severity: background
ref_id: US2018293284
ref_type: patent
severity: background
ref_id: EP3444733
ref_type: patent
severity: novelty_destroying
Final disposition: pending (2020-12-09)