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Methods, devices, and systems that aggregate and retrieve network sensor data. In one approach, an exemplary method includes receiving a plurality of instances of correlated sensor data from a plurality of remote data storages, each instance of sensor data respectively correlating to an occurrence.

Methods, devices, and systems that aggregate and retrieve network sensor data. In one approach, an exemplary method includes receiving a plurality of instances of correlated sensor data from a plurality of remote data storages, each instance of sensor data respectively correlating to an occurrence. In another approach, an exemplary method includes receiving from an input-selector an input selection corresponding to a target-occurrence having at least one representative feature, and searching stored sensor data for sensor data correlating to the target-occurrence.

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What is claimed is: 1. A data system, comprising: (a) a computing device operable to communicate with a local data storage device and with a remote data storage operable to store a plurality of instances of mote data, each instance of mote data correlating to a respective occurrence; and (b) instru

What is claimed is: 1. A data system, comprising: (a) a computing device operable to communicate with a local data storage device and with a remote data storage operable to store a plurality of instances of mote data, each instance of mote data correlating to a respective occurrence; and (b) instructions, which when implemented in a computing device, cause the computing device to perform steps including: (i) receive the plurality of instances of mote data from the remote storage device; (ii) store the received plurality of instances of correlated mote data in the local data storage device; (iii) receive an input selection corresponding to a target-occurrence having at least one representative feature; (iv) automatically search the stored plurality of instances of mote data for mote data correlating to the target-occurrence; and (v) if mote data correlating to the target-occurrence is found, provide the correlating mote data. 2. The system of claim 1, wherein the search for mote data correlating to the target-occurrence includes correlating to at least one representative feature of the occurrence. 3. The system of claim 1, wherein at least one occurrence includes a real world event. 4. The system of claim 1, wherein at least one occurrence includes a real world incident. 5. The system of claim 1, wherein at least one occurrence includes a change in a data sequence. 6. The system of claim 1, wherein at least one occurrence includes a change in a time domain. 7. The system of claim 1, wherein the plurality of instances of mote data include a first instance of mote data correlating to a respective first occurrence and a second instance of mote data correlating to a respective second occurrence. 8. The system of claim 7, wherein the first and second occurrences relate to substantially a common time. 9. The system of claim 7, wherein the first and second occurrences relate to substantially a same location. 10. The system of claim 7, wherein the first and second occurrences include an at least substantially similar representative feature. 11. The system of claim 7, wherein the mote data of the first occurrence relates a first matter and the mote data of the second occurrence relates to a second matter. 12. The system of claim 11, wherein the first and second matters are substantially similar. 13. The system of claim 1, wherein the representative feature is a frequency characteristic. 14. The system of claim 13, wherein the frequency characteristic is an acoustic frequency characteristic. 15. The system of claim 14, wherein the acoustic frequency characteristic includes an acoustic signature of a known event. 16. The system of claim 13, wherein the frequency characteristic is a light frequency characteristic. 17. The system of claim 1, wherein the representative feature is an amplitude characteristic. 18. The system of claim 1, wherein the representative feature includes a frequency characteristic and an amplitude characteristic. 19. The system of claim 1, wherein the representative feature is a magnetic characteristic. 20. The system of claim 1, wherein the representative feature includes a repetitive sequence. 21. The system of claim 20, wherein the repetitive sequence includes a chronological sequence. 22. An occurrence-data archival system, comprising: (a) a computing device operable to communicate with a local data storage and a plurality of remote data storages; and (b) instructions that cause a computing device to perform steps including: (i) receive a plurality of instances of correlated mote data from the plurality of remote data storages, each instance of mote data respectively correlating to an occurrence; and (ii) store the received plurality of instances of correlated mote data in the archival data storage; wherein at least one instance of the received mote data includes an associated tentative occurrence-identifier; and wherein the tentative occurrence-identifier is associated by a method including; receiving an input selection corresponding to a target-occurrence having at least one representative feature; automatically selecting a pattern recognition criteria corresponding to at least one representative feature of the target-occurrence; search mote data for data correlating to the target-occurrence using the selected pattern recognition criteria; and if mote data correlating to the target-occurrence representative feature is found, associating the tentative occurrence-identifier with the correlating mote data. 23. The system of claim 22, further including (c) a local data storage device. 24. The system of claim 23, wherein the local data storage device is operable as an archival data storage. 25. The system of claim 22, wherein the correlating to an occurrence includes correlating to at least one representative feature of the occurrence. 26. The system of claim 25, wherein the at least one representative feature includes a sequence. 27. The system of claim 22, wherein the occurrence includes a real world event. 28. The system of claim 22, wherein the occurrence includes a real world incident. 29. The system of claim 22, wherein the plurality of instances of mote data include a first instance of mote data correlating to a respective first occurrence and a second instance of mote data correlating to a respective second occurrence. 30. The system of claim 29, wherein the mote data of the first occurrence relates a first matter and the mote data of the second occurrence relates to a second matter. 31. The system of claim 30, wherein the first and second matters are substantially similar. 32. The system of claim 22, wherein each instance of mote data includes a respective sequence. 33. The system of claim 32, wherein the sequence includes a chronological sequence. 34. The system of claim 22, wherein each instance of mote data was acquired by at least one mote of a plurality of distributed motes. 35. The system of claim 34, wherein each mote is part of a network of motes. 36. The system of claim 22, wherein at least one instance of the mote data was acquired by a mote operable to sense at least one parameter. 37. The system of claim 22, further including (c) an information security measure operable to protect the plurality of instances of mote data stored in the local data storage. 38. The system of claim 37, wherein the information security measure protects by providing at least one item selected from a group consisting of information confidentiality, information integrity, and access control. 39. The system of claim 22, wherein the instructions further include (iii) delete a portion of the stored data from the at least one remote data storage. 40. A method implemented in a computing device, the method comprising: (a) receiving a plurality of instances of correlated mote data from a plurality of remote data storages, each instance of mote data respectively correlating to an occurrence; (b) storing the received plurality of instances of correlated mote data in a local storage device; and (c) protecting the stored plurality of instances of correlated mote data with an information security measure; wherein the information security measure protects the plurality of received instances of mote data by providing at least one selected from a group consisting of information confidentiality, information integrity, and access control. 41. The method of claim 40, wherein the receiving step further includes receiving the plurality of instances of mote data in response to a data push. 42. The method of claim 40, further comprising (d) requesting the plurality of instances of mote data from the remote data storage. 43. The method of claim 40, wherein the occurrence includes a real world event. 44. The method of claim 40, wherein the occurrence includes a real world incident. 45. The method of claim 40, wherein the occurrence includes a change in a data sequence. 46. The method of claim 40, wherein the occurrence includes a change in a time domain. 47. The method of claim 40, wherein the plurality of instances of mote data include a first instance of mote data correlating to a respective first occurrence and a second instance of mote data correlating to a respective second occurrence. 48. The method of claim 47, wherein the first and second occurrences happened at substantially a same time. 49. The method of claim 47, wherein the first and second occurrences happened at substantially a same location. 50. The method of claim 47, wherein the first and second occurrences include an at least substantially similar representative feature. 51. The method of claim 47, wherein the mote data of the first occurrence relates a first matter and the mote data of the second occurrence relates to a second matter. 52. The method of claim 51, wherein the first and second matters are substantially similar. 53. The method of claim 47, wherein each instance of mote data includes a respective sequence. 54. The method of claim 53, wherein the sequence includes a Chronological sequence. 55. The method of claim 47, wherein each occurrence includes a sequence and representative feature. 56. The method of claim 47, wherein each instance of mote data includes an associated tentative occurrence-identifier. 57. The method of claim 47, further comprising (d) deleting at least one of the plurality of instances of mote data from its respective remote data storage. 58. A communication storage media containing computer instructions, which, run on a computing device, cause the computing device to perform the method comprising: (a) receiving a plurality of instances of correlated mote data from a plurality of remote data storages, each instance of mote data respectively correlating to an occurrence; (b) storing the received plurality of instances of correlated mote data in a local data storage device; and (c) protecting the stored plurality of instances of correlated mote data with an information security measure; wherein the plurality of instances of mote data include a first instance of mote data correlating to a respective first occurrence and a second instance of mote data correlating to a respective second occurrence. 59. A method comprising: (a) moving a portable central computing device to location such that the portable central computing device communicates with at least one mote of a network of distributed motes, each mote operable to sense and store a plurality of data sets each respectively representing a respective feature, each respective feature having a correlation to an occurrence; and (b) causing the central computing device to acquire at least one mote data set; wherein each mote further includes operability to filter the plurality of data sets for a feature correlating to a target-occurrence; and wherein causing the central computing device to acquire at least one data set further includes causing the central computing device to acquire at least one data set having a feature correlating to the target occurrence. 60. The method of claim 59, further including (c) selecting through the central computing device a mote data set to be transmitted from the at least one mote to the central computing device. 61. The method of claim 60, further including (d) confirming that the at least one selected mote data set is acquired by the central computing device. 62. An occurrence-data retrieval system, comprising: (a) a computing device operable to communicate with a data storage operable to store a plurality of instances of mote data acquired by at least one mote of a mote network, each instance of mote data correlating to a respective occurrence; and (b) instructions, which when implemented in a computing device, cause the computing device to perform steps including: (i) receive from an input-selector an input selection corresponding to a target-occurrence; (ii) automatically search the plurality of instances of mote data stored in the data storage for mote data correlating to the target-occurrence; and (iii) if mote data correlating to the target-occurrence is found, provide the correlating mote data. 63. The system of claim 62, wherein each occurrence includes a representative feature. 64. The system of claim 62, wherein the data storage is remote to the computing device. 65. The system of claim 64, wherein the computing device communicates with at least one remote data storage through an intermediate computing device. 66. The system of claim 62, wherein the data storage is local to the computing device. 67. The system of claim 62, wherein the provide instruction further includes provide the correlating mote data to the input-selector. 68. The system of claim 62, wherein the provide instruction further includes provide the correlating mote data to a third party. 69. The system of claim 62, wherein the instructions further include: (iv) receive the plurality of instances of mote data from at least one remote data storage; and (v) store the received plurality of instances of correlated mote data in a local data storage. 70. An occurrence-data retrieval system, comprising: (a) a local digital data storage device operable to store a plurality of instances of mote data acquired from a plurality of motes of a network of distributed motes, each instance of mote data correlating to at least one representative feature of an occurrence; (b) a central computing device operable to communicate with the local digital data storage device; and (c) instructions that cause the computing device to perform steps, including: (i) receive from an input-selector an input selection corresponding to a target-occurrence having at least one representative feature; (ii) automatically select a pattern recognition criteria corresponding to at least one representative feature of the target-occurrence; (iii) in response to the input selection corresponding to the target-occurrence, automatically search the plurality of instances of stored mote data for data correlating to the target-occurrence using the selected pattern recognition criteria; and (iv) if mote data correlating to the target-occurrence representative feature is found, provide the correlating mote data. 71. The system of claim 70, wherein the input-selector includes a machine. 72. The system of claim 70, wherein the input-selector includes a user. 73. The system of claim 70, wherein the pattern recognition criteria is automatically selected by the instructions in response to the target-occurrence. 74. The system of claim 70, wherein the input selection further includes a selection of a representative feature of the target-occurrence. 75. The system of claim 74, wherein the pattern recognition criteria is automatically selected by the instructions in response to the input-selected representative feature. 76. The system of claim 75, wherein the automatic search instruction includes using the pattern recognition criteria selected in response to the input-selected representative feature. 77. The system of claim 70, wherein the instructions further include (v) protect the plurality of instances of mote data stored in the local digital data storage device from unauthorized access. 78. An occurrence-data retrieval system, comprising: (a) a computing device operable to communicate with a plurality of data storage devices, each data storage device being a respective part of a mote of a network of distributed remote motes and operable to store plurality of instances of mote data, and each instance of mote data representing a feature sensed by the mote and correlating to a respective occurrence; and (b) instructions, which when implemented in a computing device, cause the computing device to perform steps including: (i) receive from an input-selector an input selection corresponding to a target-occurrence having a representative feature, a recipient selection, and a tendered access authorization; (ii) in response to the tendered access authorization, determine if at least one of the input-selector and recipient have an access right; (iii) automatically select a pattern recognition criteria corresponding to the representative feature of the target-occurrence; (iv) in response to the input selection corresponding to the target-occurrence, automatically search the plurality of instances of mote data stored in the data storage device for data correlating to the target-occurrence using the selected pattern recognition criteria; and (v) if mote data correlating to the target-occurrence representative feature is found, and if at least one of the input-selector and recipient have an access right, provide the correlating mote data to the recipient. 79. The system of claim 78, wherein the input-selector includes a machine. 80. The system of claim 78, wherein the input-selector includes a user. 81. The system of claim 78, wherein the input-selector and the recipient are a same party. 82. The system of claim 78, wherein the recipient is a user. 83. The system of claim 78, wherein the recipient is a program running on another computing device. 84. The system of claim 78, wherein the data storage device includes a device selected from a group consisting of a local data storage device and a remote data storage device. 85. The system of claim 78, wherein the instructions further include, if neither the input-selector and recipient have an access right, not providing the correlating mote data. 86. The system of claim 78, further including an information security measure protecting the mote data stored in the data storage device from unauthorized access. 87. The system of claim 86, wherein the information security access allows access to the mote data upon receipt of a recognized data entry by the input-selector. 88. The system of claim 87, wherein the recognized data entry includes a password. 89. The system of claim 86, wherein the information security access allows access to the mote data upon receipt of a recognized biometric. 90. The system of claim 89, wherein the biometric includes at least one selected from a group consisting of a voice, finger, hand, face, and eye recognition. 91. An occurrence-data retrieval system, comprising: (a) a data storage operable to store a plurality of instances of mote data, each instance of mote data correlating to at least one representative feature of a respective occurrence and including an associated tentative occurrence-identifier; (b) a computing device operable to communicate with at the least one data storage device; (c) an information security measure that controls access to the stored plurality of instances of mote data; and (d) instructions, which when implemented in a computing device, cause the computing device to perform steps including: (i) store the plurality of instances of mote data in the data storage; (ii) receive from an input-selector an input selection corresponding to a target tentative occurrence-identifier, and a tender of access authorization; (iii) in response to the input selection corresponding to the target tentative occurrence-identifier, automatically search the plurality of instances of mote data for tentative occurrence-identifiers correlating to the target tentative occurrence-identifier; and (iv) if mote data correlating to the target tentative occurrence-identifier is found, and if at least one of the input-selector and recipient possess an access right, provide the correlating mote data. 92. The system of claim 91, wherein the data storage device includes a device selected from a group consisting of a local data storage device and a remote data storage device. 93. The system of claim 91, wherein the instructions further include, if neither the input-selector and recipient have an access right, not providing the correlating mote data. 94. The system of claim 91, further including an information security measure protecting the mote data stored in the data storage device from unauthorized access. 95. A method comprising: (a) receiving from an input-selector an input selection corresponding to a target-occurrence having at least one representative feature; (b) automatically searching a plurality of instances mote data for mote data correlating to the target-occurrence, each instance of mote data correlating to an occurrence having at least one representative feature; and (c) if mote data correlating to the target-occurrence is found, providing the correlating mote data; wherein the providing further includes indicating a ranking of at least two instances of the correlating mote data in a hierarchy of the found correlating mote data. 96. The method of claim 95, wherein the plurality of instances of mote data are stored in a data storage. 97. The method of claim 96, wherein the data storage includes a device selected from a group consisting of a data storage device local to the computing device and a data storage device remote to the computing device. 98. A communication storage media containing computer instructions which, when run on a computing device, cause the computing device to perform the method comprising: (a) receiving from an input-selector an input selection corresponding to a target-occurrence having at least one representative feature; (b) automatically searching a plurality of instances mote data for mote data correlating to the target-occurrence. each instance of mote data correlating to an occurrence having at least one representative feature; and (c) if mote data correlating to the target-occurrence is found, providing the correlating mote data. 99. A method implemented in a computing device, the method comprising: (a) receiving an input selection from an input-selector corresponding to a target-occurrence having a representative feature, a recipient selection, and a tendered access authorization; (b) automatically selecting a pattern recognition criteria corresponding to the representative feature of the target-occurrence; (c) in response to the input selection corresponding to the target-occurrence, automatically searching a plurality of instances of correlated mote data for data correlating to the target-occurrence using the selected pattern recognition criteria, each instance of mote data correlating to at least one representative feature of a respective occurrence; (d) in response to the tendered access authorization, determine if at least one of the input-selector and the recipient posses an access right; and (e) if mote data correlating to the target-occurrence representative feature is found, and if at least one of the input-selector and the recipient have an access right, providing the correlating mote data. 100. The method of claim 99, wherein the plurality of instances correlated mote data are stored in a data storage device. 101. The method of claim 100, wherein the data storage device is local to the computing device. 102. A method implemented in a computing device, the method comprising: (a) receiving an input selection from an input-selector corresponding to a tentative target-occurrence identifier, the target-occurrence having at least one representative feature, a recipient selection, and a tendered access authorization; (b) in response to the input selection corresponding to the tentative target-occurrence identifier, automatically searching a plurality of instances of stored correlated mote data for data correlating to the tentative target-occurrence identifier; and (c) if mote data correlating to the tentative target-occurrence identifier is found, providing the correlating mote data. 103. The method of claim 102, wherein the instances of correlated mote data are stored in a data storage device local to the computing device. 104. A data retrieval system, comprising: (a) a local data storage device operable to store mote data sets from remote data storage devices, each mote data set representing a respective feature sensed by its respective remote storage device and having a correlation to a reference; (b) a computing device operable to communicate with a local data storage device; and (c) instructions, which when implemented in a computing device, cause the computing device to perform steps including: (i) receive from an input-selector an input selection corresponding to a target-reference; (ii) automatically search the instances of mote data stored in the data storage device for mote data correlating to the target-reference; and (iii) if mote data correlating to the target-reference is found, provide the correlating mote data.