Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study
Shuxia GuoClaudia BeleitesUte NeugebauerSara Abalde‐CelaNils Kristian AfsethFatima AlsamadSuresh AnandC. Araujo-AndradeSonja AškrabićErtuğ AvcıMonica BaiaMałgorzata BarańskaEnrico BariaLuís A. E. Batista de CarvalhoPhilippe de BettigniesAlois BonifacioFranck BonnierEva BrauchleHugh J. ByrneIgor ChourpaRiccardo CicchiFrederic CuisinierMustafa ÇulhaMarcel DahmsCatalina DavidLudovic DuponchelShiyamala DuraipandianSamir F. El‐MashtolyDavid I. EllisGauthier EppeGuillaume FalgayracOzren GamulinBenjamin GardnerP. GardnerKlaus GerwertEvangelos J. Giamarellos‐BourboulisSveinbjörn GizurarsonM. GnybaRoyston GoodacrePatrick GrysanOrlando Guntinas‐LichiusHelga HelgadóttirVlasta Mohaček‐GroševCatherine KendallRoman KiselevMicha KölbachChristoph KrafftSivashankar KrishnamoorthyPatrick KubryckBernhard LendlPablo Loza‐ÁlvarezFiona M. LyngSusanne MachillCédric MalherbeMónica MarroM. Paula M. MarquesEwelina MatuszykCarlo MorassoMyriam MoreauHowbeer MuhamadaliValentina MussiIoan NotingherMarta Z. PaciaFrancesco S. PavoneGuillaume PenelDennis R. PetersenOlivier PiotJulietta V. RauMarc RichterMaria K. RybarczykHamideh SalehiKatja Schenke‐LaylandSebastian SchlückerMarkus SchossererKarin SchützeValter SergoFaris SinjabJanusz SmulkoGanesh D. SockalingumClara StiebingNicholas StoneValérie UntereinerRenzo VannaKarin WielandJürgen PoppThomas Bocklitz
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Slightly processed raw data for the paper 'Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study' The processing include a spike removal to allow an interpolation to a common wavenumber axis. Always three files belong to each other: wavenumber axis file (wx_XYZ), spectral intensity file (spec_XYZ) and metadata file (meta_XYZ). The ‘XYZ’ refers to the samples measured (see the publication and its SI for details).Keywords:
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Non-Intrusive Load Monitoring (NILM) comprises of a set of techniques that provide insights into the energy consumption of households and industrial facilities. Latest contributions show significant improvements in terms of accuracy and generalisation abilities. Despite all progress made concerning disaggregation techniques, performance evaluation and comparability remains an open research question. The lack of standardisation and consensus on evaluation procedures makes reproducibility and comparability extremely difficult. In this paper, we draw attention to comparability in NILM with a focus on highlighting the considerable differences amongst common energy datasets used to test the performance of algorithms. We divide discussion on comparability into data aspects, performance metrics, and give a close view on evaluation processes. Detailed information on pre-processing as well as data cleaning methods, the importance of unified performance reporting, and the need for complexity measures in load disaggregation are found to be the most urgent issues in NILM-related research. In addition, our evaluation suggests that datasets should be chosen carefully. We conclude by formulating suggestions for future work to enhance comparability.
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