A plant operation data monitoring device, comprising: an input section that is adapted to receive operation data (D) on a plant; and a calculator that includes databases (DB) for storing the operation data (D) received, and a computing section for executing a program (Pg), wherein the computing section is adapted to store the operation data (D) received in a first database (DBA) of the databases (DB) in time series, characterized in that the computing section is adapted to determine from peak values (A1-A4, B1-B4) of the stored operation data (D) whether gradients (dn1, dn2, da1, da2) of the operation data (D) are positive or negative, and then store the positive gradients (dn1, da1), in time series, in a second database for positive gradients (DBB+) and store the negative gradients (dn2, da2), in time series, in a second database for negative gradients (DBB-), wherein the second database for positive gradients (DBB+) and the second database for negative gradients (DBB-) are part of said databases (DB), and the computing section is adapted to determine threshold values for abnormality determination for each of the positive and negative gradients (dn1, dn2, da1, da2), divide each of the positive gradients (dn1, da1) and the negative gradients (dn2, da2) into normal values (dn1, dn2) and abnormal values (da1, da2) based on the determined threshold values, and additionally store, for each of the divided gradients of the positive gradients (dn1, da1), the determination result as a normality/abnormality determination flag (D14) in the second database for positive gradients (DBB+) and store, for each of the divided gradients of the negative gradients (dn2, da2), the determination result as a normality/abnormality determination flag (D14) in the second database for negative gradients (DBB-). an input section that is adapted to receive operation data (D) on a plant; and a calculator that includes databases (DB) for storing the operation data (D) received, and a computing section for executing a program (Pg), wherein the computing section is adapted to store the operation data (D) received in a first database (DBA) of the databases (DB) in time series, characterized in that the computing section is adapted to determine from peak values (A1-A4, B1-B4) of the stored operation data (D) whether gradients (dn1, dn2, da1, da2) of the operation data (D) are positive or negative, and then store the positive gradients (dn1, da1), in time series, in a second database for positive gradients (DBB+) and store the negative gradients (dn2, da2), in time series, in a second database for negative gradients (DBB-), wherein the second database for positive gradients (DBB+) and the second database for negative gradients (DBB-) are part of said databases (DB), and the computing section is adapted to determine threshold values for abnormality determination for each of the positive and negative gradients (dn1, dn2, da1, da2), divide each of the positive gradients (dn1, da1) and the negative gradients (dn2, da2) into normal values (dn1, dn2) and abnormal values (da1, da2) based on the determined threshold values, and additionally store, for each of the divided gradients of the positive gradients (dn1, da1), the determination result as a normality/abnormality determination flag (D14) in the second database for positive gradients (DBB+) and store, for each of the divided gradients of the negative gradients (dn2, da2), the determination result as a normality/abnormality determination flag (D14) in the second database for negative gradients (DBB-). <EOS>