id	sid	tid	token	lemma	pos
wh246q21q83	1	1	scientific	scientific	ADJ
wh246q21q83	1	2	visualization	visualization	NOUN
wh246q21q83	1	3	(	(	PUNCT
wh246q21q83	1	4	scivis	scivis	PROPN
wh246q21q83	1	5	)	)	PUNCT
wh246q21q83	1	6	is	be	AUX
wh246q21q83	1	7	one	one	NUM
wh246q21q83	1	8	of	of	ADP
wh246q21q83	1	9	the	the	DET
wh246q21q83	1	10	core	core	ADJ
wh246q21q83	1	11	components	component	NOUN
wh246q21q83	1	12	in	in	ADP
wh246q21q83	1	13	supporting	support	VERB
wh246q21q83	1	14	fundamental	fundamental	ADJ
wh246q21q83	1	15	scientific	scientific	ADJ
wh246q21q83	1	16	discoveries	discovery	NOUN
wh246q21q83	1	17	and	and	CCONJ
wh246q21q83	1	18	engineering	engineering	NOUN
wh246q21q83	1	19	designs	design	NOUN
wh246q21q83	1	20	.	.	PUNCT
wh246q21q83	2	1	for	for	ADP
wh246q21q83	2	2	example	example	NOUN
wh246q21q83	2	3	,	,	PUNCT
wh246q21q83	2	4	scientists	scientist	NOUN
wh246q21q83	2	5	perform	perform	VERB
wh246q21q83	2	6	numerical	numerical	ADJ
wh246q21q83	2	7	simulations	simulation	NOUN
wh246q21q83	2	8	and	and	CCONJ
wh246q21q83	2	9	produce	produce	VERB
wh246q21q83	2	10	3d	3d	NOUN
wh246q21q83	2	11	scalar	scalar	ADJ
wh246q21q83	2	12	and	and	CCONJ
wh246q21q83	2	13	vector	vector	NOUN
wh246q21q83	2	14	data	datum	NOUN
wh246q21q83	2	15	to	to	PART
wh246q21q83	2	16	visualize	visualize	VERB
wh246q21q83	2	17	,	,	PUNCT
wh246q21q83	2	18	analyze	analyze	VERB
wh246q21q83	2	19	,	,	PUNCT
wh246q21q83	2	20	and	and	CCONJ
wh246q21q83	2	21	understand	understand	VERB
wh246q21q83	2	22	various	various	ADJ
wh246q21q83	2	23	kinds	kind	NOUN
wh246q21q83	2	24	of	of	ADP
wh246q21q83	2	25	natural	natural	ADJ
wh246q21q83	2	26	phenomena	phenomenon	NOUN
wh246q21q83	2	27	,	,	PUNCT
wh246q21q83	2	28	such	such	ADJ
wh246q21q83	2	29	as	as	ADP
wh246q21q83	2	30	climate	climate	NOUN
wh246q21q83	2	31	change	change	NOUN
wh246q21q83	2	32	and	and	CCONJ
wh246q21q83	2	33	star	star	NOUN
wh246q21q83	2	34	formation	formation	NOUN
wh246q21q83	2	35	.	.	PUNCT
wh246q21q83	3	1	however	however	ADV
wh246q21q83	3	2	,	,	PUNCT
wh246q21q83	3	3	the	the	DET
wh246q21q83	3	4	cost	cost	NOUN
wh246q21q83	3	5	of	of	ADP
wh246q21q83	3	6	these	these	DET
wh246q21q83	3	7	simulations	simulation	NOUN
wh246q21q83	3	8	is	be	AUX
wh246q21q83	3	9	expensive	expensive	ADJ
wh246q21q83	3	10	when	when	SCONJ
wh246q21q83	3	11	time	time	NOUN
wh246q21q83	3	12	,	,	PUNCT
wh246q21q83	3	13	ensemble	ensemble	ADJ
wh246q21q83	3	14	,	,	PUNCT
wh246q21q83	3	15	and	and	CCONJ
wh246q21q83	3	16	multivariate	multivariate	NOUN
wh246q21q83	3	17	are	be	AUX
wh246q21q83	3	18	involved	involve	VERB
wh246q21q83	3	19	and	and	CCONJ
wh246q21q83	3	20	the	the	DET
wh246q21q83	3	21	scientific	scientific	ADJ
wh246q21q83	3	22	data	datum	NOUN
wh246q21q83	3	23	are	be	AUX
wh246q21q83	3	24	presented	present	VERB
wh246q21q83	3	25	in	in	ADP
wh246q21q83	3	26	diverse	diverse	ADJ
wh246q21q83	3	27	forms	form	NOUN
wh246q21q83	3	28	including	include	VERB
wh246q21q83	3	29	streamline	streamline	ADJ
wh246q21q83	3	30	,	,	PUNCT
wh246q21q83	3	31	pathline	pathline	NOUN
wh246q21q83	3	32	,	,	PUNCT
wh246q21q83	3	33	stream	stream	NOUN
wh246q21q83	3	34	surface	surface	NOUN
wh246q21q83	3	35	,	,	PUNCT
wh246q21q83	3	36	volume	volume	NOUN
wh246q21q83	3	37	,	,	PUNCT
wh246q21q83	3	38	and	and	CCONJ
wh246q21q83	3	39	isosurface	isosurface	NOUN
wh246q21q83	3	40	.	.	PUNCT
wh246q21q83	4	1	a	a	DET
wh246q21q83	4	2	core	core	NOUN
wh246q21q83	4	3	problem	problem	NOUN
wh246q21q83	4	4	in	in	ADP
wh246q21q83	4	5	scivis	scivis	PROPN
wh246q21q83	4	6	is	be	AUX
wh246q21q83	4	7	how	how	SCONJ
wh246q21q83	4	8	to	to	PART
wh246q21q83	4	9	efficiently	efficiently	ADV
wh246q21q83	4	10	and	and	CCONJ
wh246q21q83	4	11	effectively	effectively	ADV
wh246q21q83	4	12	produce	produce	VERB
wh246q21q83	4	13	and	and	CCONJ
wh246q21q83	4	14	analyze	analyze	VERB
wh246q21q83	4	15	these	these	DET
wh246q21q83	4	16	diversified	diversify	VERB
wh246q21q83	4	17	data	datum	NOUN
wh246q21q83	4	18	.	.	PUNCT
wh246q21q83	5	1	in	in	ADP
wh246q21q83	5	2	this	this	DET
wh246q21q83	5	3	dissertation	dissertation	NOUN
wh246q21q83	5	4	,	,	PUNCT
wh246q21q83	5	5	i	i	PRON
wh246q21q83	5	6	develop	develop	VERB
wh246q21q83	5	7	novel	novel	ADJ
wh246q21q83	5	8	deep	deep	ADJ
wh246q21q83	5	9	learning	learning	NOUN
wh246q21q83	5	10	methods	method	NOUN
wh246q21q83	5	11	to	to	PART
wh246q21q83	5	12	enable	enable	VERB
wh246q21q83	5	13	more	more	ADV
wh246q21q83	5	14	effective	effective	ADJ
wh246q21q83	5	15	and	and	CCONJ
wh246q21q83	5	16	efficient	efficient	ADJ
wh246q21q83	5	17	frameworks	framework	NOUN
wh246q21q83	5	18	for	for	ADP
wh246q21q83	5	19	scientific	scientific	ADJ
wh246q21q83	5	20	data	datum	NOUN
wh246q21q83	5	21	representation	representation	NOUN
wh246q21q83	5	22	and	and	CCONJ
wh246q21q83	5	23	generation.in	generation.in	PUNCT
wh246q21q83	5	24	scientific	scientific	ADJ
wh246q21q83	5	25	data	datum	NOUN
wh246q21q83	5	26	representation	representation	NOUN
wh246q21q83	5	27	,	,	PUNCT
wh246q21q83	5	28	i	i	PRON
wh246q21q83	5	29	propose	propose	VERB
wh246q21q83	5	30	a	a	DET
wh246q21q83	5	31	unified	unified	ADJ
wh246q21q83	5	32	framework	framework	NOUN
wh246q21q83	5	33	that	that	PRON
wh246q21q83	5	34	processes	process	VERB
wh246q21q83	5	35	both	both	PRON
wh246q21q83	5	36	streamlines	streamline	NOUN
wh246q21q83	5	37	and	and	CCONJ
wh246q21q83	5	38	stream	stream	VERB
wh246q21q83	5	39	surfaces	surface	NOUN
wh246q21q83	5	40	through	through	ADP
wh246q21q83	5	41	auto	auto	NOUN
wh246q21q83	5	42	-	-	PUNCT
wh246q21q83	5	43	encoder	encoder	NOUN
wh246q21q83	5	44	decoder	decoder	NOUN
wh246q21q83	5	45	structure	structure	NOUN
wh246q21q83	5	46	.	.	PUNCT
wh246q21q83	6	1	moreover	moreover	ADV
wh246q21q83	6	2	,	,	PUNCT
wh246q21q83	6	3	i	i	PRON
wh246q21q83	6	4	build	build	VERB
wh246q21q83	6	5	an	an	DET
wh246q21q83	6	6	interface	interface	NOUN
wh246q21q83	6	7	that	that	PRON
wh246q21q83	6	8	allows	allow	VERB
wh246q21q83	6	9	users	user	NOUN
wh246q21q83	6	10	to	to	PART
wh246q21q83	6	11	explore	explore	VERB
wh246q21q83	6	12	the	the	DET
wh246q21q83	6	13	relationships	relationship	NOUN
wh246q21q83	6	14	between	between	ADP
wh246q21q83	6	15	the	the	DET
wh246q21q83	6	16	learned	learn	VERB
wh246q21q83	6	17	features	feature	NOUN
wh246q21q83	6	18	and	and	CCONJ
wh246q21q83	6	19	visual	visual	ADJ
wh246q21q83	6	20	representations	representation	NOUN
wh246q21q83	6	21	.	.	PUNCT
wh246q21q83	7	1	i	i	PRON
wh246q21q83	7	2	also	also	ADV
wh246q21q83	7	3	utilize	utilize	VERB
wh246q21q83	7	4	geometric	geometric	ADJ
wh246q21q83	7	5	deep	deep	ADJ
wh246q21q83	7	6	learning	learning	NOUN
wh246q21q83	7	7	(	(	PUNCT
wh246q21q83	7	8	e.g.	e.g.	ADV
wh246q21q83	7	9	,	,	PUNCT
wh246q21q83	7	10	graph	graph	NOUN
wh246q21q83	7	11	neural	neural	ADJ
wh246q21q83	7	12	network	network	NOUN
wh246q21q83	7	13	)	)	PUNCT
wh246q21q83	7	14	to	to	PART
wh246q21q83	7	15	extract	extract	VERB
wh246q21q83	7	16	node	node	NOUN
wh246q21q83	7	17	-	-	PUNCT
wh246q21q83	7	18	level	level	NOUN
wh246q21q83	7	19	and	and	CCONJ
wh246q21q83	7	20	surface	surface	NOUN
wh246q21q83	7	21	-	-	PUNCT
wh246q21q83	7	22	level	level	NOUN
wh246q21q83	7	23	features	feature	NOUN
wh246q21q83	7	24	in	in	ADP
wh246q21q83	7	25	an	an	DET
wh246q21q83	7	26	unsupervised	unsupervised	ADJ
wh246q21q83	7	27	fashion	fashion	NOUN
wh246q21q83	7	28	for	for	ADP
wh246q21q83	7	29	node	node	NOUN
wh246q21q83	7	30	clustering	clustering	NOUN
wh246q21q83	7	31	and	and	CCONJ
wh246q21q83	7	32	surface	surface	NOUN
wh246q21q83	7	33	selection	selection	NOUN
wh246q21q83	7	34	tasks	task	NOUN
wh246q21q83	7	35	.	.	PUNCT
wh246q21q83	8	1	in	in	ADP
wh246q21q83	8	2	scientific	scientific	ADJ
wh246q21q83	8	3	data	datum	NOUN
wh246q21q83	8	4	generation	generation	NOUN
wh246q21q83	8	5	,	,	PUNCT
wh246q21q83	8	6	i	i	PRON
wh246q21q83	8	7	introduce	introduce	VERB
wh246q21q83	8	8	a	a	DET
wh246q21q83	8	9	comprehensive	comprehensive	ADJ
wh246q21q83	8	10	pipeline	pipeline	NOUN
wh246q21q83	8	11	for	for	ADP
wh246q21q83	8	12	variable	variable	ADJ
wh246q21q83	8	13	selection	selection	NOUN
wh246q21q83	8	14	and	and	CCONJ
wh246q21q83	8	15	translation	translation	NOUN
wh246q21q83	8	16	through	through	ADP
wh246q21q83	8	17	feature	feature	NOUN
wh246q21q83	8	18	learning	learning	NOUN
wh246q21q83	8	19	,	,	PUNCT
wh246q21q83	8	20	translation	translation	NOUN
wh246q21q83	8	21	graph	graph	NOUN
wh246q21q83	8	22	construction	construction	NOUN
wh246q21q83	8	23	,	,	PUNCT
wh246q21q83	8	24	and	and	CCONJ
wh246q21q83	8	25	variable	variable	ADJ
wh246q21q83	8	26	translation	translation	NOUN
wh246q21q83	8	27	.	.	PUNCT
wh246q21q83	9	1	this	this	DET
wh246q21q83	9	2	framework	framework	NOUN
wh246q21q83	9	3	can	can	AUX
wh246q21q83	9	4	serve	serve	VERB
wh246q21q83	9	5	as	as	ADP
wh246q21q83	9	6	a	a	DET
wh246q21q83	9	7	data	data	NOUN
wh246q21q83	9	8	extrapolation	extrapolation	NOUN
wh246q21q83	9	9	and	and	CCONJ
wh246q21q83	9	10	compression	compression	NOUN
wh246q21q83	9	11	solution	solution	NOUN
wh246q21q83	9	12	to	to	PART
wh246q21q83	9	13	reduce	reduce	VERB
wh246q21q83	9	14	simulation	simulation	NOUN
wh246q21q83	9	15	costs	cost	NOUN
wh246q21q83	9	16	.	.	PUNCT
wh246q21q83	10	1	besides	besides	ADV
wh246q21q83	10	2	,	,	PUNCT
wh246q21q83	10	3	i	i	PRON
wh246q21q83	10	4	develop	develop	VERB
wh246q21q83	10	5	an	an	DET
wh246q21q83	10	6	end	end	NOUN
wh246q21q83	10	7	-	-	PUNCT
wh246q21q83	10	8	to	to	ADP
wh246q21q83	10	9	-	-	PUNCT
wh246q21q83	10	10	end	end	NOUN
wh246q21q83	10	11	generative	generative	ADJ
wh246q21q83	10	12	framework	framework	NOUN
wh246q21q83	10	13	that	that	PRON
wh246q21q83	10	14	can	can	AUX
wh246q21q83	10	15	synthesize	synthesize	VERB
wh246q21q83	10	16	spatiotemporal	spatiotemporal	ADJ
wh246q21q83	10	17	super	super	ADJ
wh246q21q83	10	18	-	-	ADJ
wh246q21q83	10	19	resolution	resolution	ADJ
wh246q21q83	10	20	volumes	volume	NOUN
wh246q21q83	10	21	with	with	ADP
wh246q21q83	10	22	high	high	ADJ
wh246q21q83	10	23	fidelity	fidelity	NOUN
wh246q21q83	10	24	.	.	PUNCT
wh246q21q83	11	1	further	far	ADV
wh246q21q83	11	2	,	,	PUNCT
wh246q21q83	11	3	to	to	PART
wh246q21q83	11	4	improve	improve	VERB
wh246q21q83	11	5	network	network	NOUN
wh246q21q83	11	6	generalization	generalization	NOUN
wh246q21q83	11	7	,	,	PUNCT
wh246q21q83	11	8	i	i	PRON
wh246q21q83	11	9	propose	propose	VERB
wh246q21q83	11	10	an	an	DET
wh246q21q83	11	11	unsupervised	unsupervised	ADJ
wh246q21q83	11	12	pre	pre	ADJ
wh246q21q83	11	13	-	-	ADJ
wh246q21q83	11	14	training	training	ADJ
wh246q21q83	11	15	stage	stage	NOUN
wh246q21q83	11	16	using	use	VERB
wh246q21q83	11	17	cycle	cycle	NOUN
wh246q21q83	11	18	loss	loss	NOUN
wh246q21q83	11	19	.	.	PUNCT
wh246q21q83	12	1	this	this	DET
wh246q21q83	12	2	spatiotemporal	spatiotemporal	ADJ
wh246q21q83	12	3	super	super	ADJ
wh246q21q83	12	4	-	-	ADJ
wh246q21q83	12	5	resolution	resolution	ADJ
wh246q21q83	12	6	approach	approach	NOUN
wh246q21q83	12	7	can	can	AUX
wh246q21q83	12	8	upscale	upscale	ADJ
wh246q21q83	12	9	data	datum	NOUN
wh246q21q83	12	10	up	up	ADP
wh246q21q83	12	11	to	to	PART
wh246q21q83	12	12	512	512	NUM
wh246q21q83	12	13	times	time	NOUN
wh246q21q83	12	14	in	in	ADP
wh246q21q83	12	15	spatial	spatial	ADJ
wh246q21q83	12	16	dimension	dimension	NOUN
wh246q21q83	12	17	and	and	CCONJ
wh246q21q83	12	18	11	11	NUM
wh246q21q83	12	19	times	time	NOUN
wh246q21q83	12	20	in	in	ADP
wh246q21q83	12	21	temporal	temporal	ADJ
wh246q21q83	12	22	dimension	dimension	NOUN
wh246q21q83	12	23	,	,	PUNCT
wh246q21q83	12	24	which	which	PRON
wh246q21q83	12	25	offers	offer	VERB
wh246q21q83	12	26	scientists	scientist	NOUN
wh246q21q83	12	27	an	an	DET
wh246q21q83	12	28	option	option	NOUN
wh246q21q83	12	29	to	to	PART
wh246q21q83	12	30	reduce	reduce	VERB
wh246q21q83	12	31	data	datum	NOUN
wh246q21q83	12	32	storage	storage	NOUN
wh246q21q83	12	33	.	.	PUNCT