cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3588298
title: Phenological metrics for Protected Area "BayerischerWald", MODIS aqua tile h18v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588299
title: 87Rb MAS NMR Spectrum of RbClO4

description: <sup>87</sup>Rb MAS echo NMR spectrum of RbClO<sub>4</sub>.
description: Dead link in CSDFE file updated
DOI: 10.7910/dvn/il0lue/0xjufw
title: product_process_patents_pred_100_ep_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/5ukaqr
title: product_process_patents_abstr_ep_semiconductors.png

description: :unav
DOI: 10.7910/dvn/il0lue/7jd1yh
title: product_process_patents_pred_100_ep_Chemical engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/dhvq06
title: product_process_patents_2_ind_100_ep_semiconductors.png

description: :unav
DOI: 10.7910/dvn/il0lue/jtnpm9
title: product_process_patents_pred_ind_100_ep_H01M.png

description: :unav
DOI: 10.7910/dvn/il0lue/lsbbxr
title: product_process_patents_pred_100_us_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/z01ps1
title: product_process_patents_2_100_us_Organic fine chemistry.png

description: :unav
DOI: 10.7910/dvn/il0lue/zhghh9
title: product_process_patents_abstr_ep_Textile and paper machines.png

description: :unav
DOI: 10.7910/dvn/il0lue/znwx98
title: product_process_patents_pred_100_ep_Biotechnology.png

description: :unav
DOI: 10.5281/zenodo.3407265
title: Data set related to the manuscript "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons"

description: Graphical files in the agr format for all the figures in the main text of the manuscript entitled "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons" (10.1021/acsami.9b16740). Example of input file for one of the systems simulated.
DOI: 10.5281/zenodo.3407266
title: Data set related to the manuscript "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons"

description: Graphical files in the agr format for all the figures in the main text of the manuscript entitled "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons" (10.1021/acsami.9b16740). Example of input file for one of the systems simulated.
DOI: 10.5281/zenodo.3588297
title: Phenological metrics for Protected Area "BayerischerWald", MODIS aqua tile h18v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.7910/dvn/il0lue/3h923a
title: product_process_patents_pred_100_ep_antibiotics.png

description: :unav
DOI: 10.7910/dvn/il0lue/amnulb
title: product_process_patents_abstr_us_Handling.png

description: :unav
DOI: 10.7910/dvn/il0lue/fzonhz
title: product_process_patents_pred_100_us_Micro-structural and nano-technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/nyd71c
title: product_process_patents_pred_ind_100_us_smartphones.png

description: :unav
DOI: 10.7910/dvn/il0lue/omlldy
title: product_process_patents_pred_100_ep_IT methods for management.png

description: :unav
DOI: 10.7910/dvn/il0lue/rm7fne
title: product_process_patents_pred_100_ep_Measurement.png

description: :unav
DOI: 10.7910/dvn/il0lue/svd6fw
title: product_process_patents_2_100_ep_semiconductors.png

description: :unav
DOI: 10.7910/dvn/il0lue/unhsmk
title: product_process_patents_pred_100_us_Medical technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/vr2ms4
title: product_process_patents_2_100_us_Basic communication processes.png

description: :unav
DOI: 10.5285/8313ce72-0d99-43bf-ae7b-1ea3904534d3
title: Glacier algal abundance, photophysiology, pigmentation, bio-optical properties growth and impacts to albedo in the Greenland Ice Sheet Dark Zone, July-August 2016

description: The abundance, photophysiology, pigmentation, bio-optical properties, cellular energy balance and instantaneous radiative forcing of glacier algal assemblages from the surface of the Greenland Ice Sheet (GrIS) are quantified throughout the 2016 ablation season. The effects of assemblages on ice surface albedo are further derived using a newly developed model of glacier algal blooms for the GrIS, radiative transfer modelling using BioSNICAR-GO, and comparisons to MODIS broadband albedo observations over the same season. Data represent a composite of in-situ observations, in-situ incubations studies, laboratory analyses, modelling and remote sensing. All in -situ work was performed at site S6 of the K-Transect in the southwestern GrIS ablation zone as part of the Black and Bloom project. Funding was provided by the NERC 'Black and Bloom' grant NE/M021025/1 and the Marie Sklodowska-Curie grant agreement No 675546.
description: Data was gathered during the 2016 Black and Bloom field campaign and processed in the LowTex and MicroLab laboratories at the University of Bristol. Details on sample collection, processing and analysis can be found in the referenced publication, and all R data analysis scripts are available here. In-situ data collection spanned June-August 2016. Model runs spanned 1st June 2016 - 1st September 2016. All in-situ observations and incubation studies were conducted in proximity to the IMAU (Utrecht) automatic weather station S6 of the K-Transect in southwest Greenland (67.04 N, 49.07W). Model runs were performed for sites S6, S8, S9 and S10 of the K-Transect.
description: Instrumentation: Algal cell abundance was quantified using a Fuchs-Rosenthal haemocytometer (Lancing, UK) on a LeicaDM 2000 epifluorescence microscope with attached MC120 HD camera (Leica, Germany). Photophysiology was assessed using a Water-PAM fluorometer with attached cuvette system (Walz GmBH, Germany). Algal pigmentation was assessed using a combination of High-Performance Liquid Chromatography (HPLC) using an Agilent 1100 HPLC equipped with a diode-array detector, and spectrophotometric wave-scans using a WPA Light-Wave II UV/Visible spectrophotometer (Biochrom, UK). Albedo modelling was achieved using the radiative transfer model BioSNICAR-GO. GrIS surface ice broadband albedo for June, July and August 2016 were derived from clear-sky MODIS MOD10A1 satellite observations at 500 m horizontal resolution. Glacier algal biomass was modelled in GrIS surface ice forced by hourly snowpack thickness, shortwave-down radiation and air temperature from re-analysis outputs produced by the regional climate model MARv3.8.1 forced with ERA -Interim at 20km resolution.
description: All analyses performed on data are available as associated script files.
DOI: 10.7910/dvn/il0lue/8egiuo
title: product_process_patents_pred_100_us_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/b8zsab
title: product_process_patents_2_ind_100_us_nanotech.png

description: :unav
DOI: 10.7910/dvn/il0lue/bpz7ut
title: product_process_patents_pred_100_us_Machine tools.png

description: :unav
DOI: 10.7910/dvn/il0lue/dkehb8
title: product_process_patents_2_100_us_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/e6mns5
title: product_process_patents_abstr_ep_Biotechnology.png

description: :unav
DOI: 10.7910/dvn/il0lue/f5trc9
title: product_process_patents_2_ind_100_us_Other special machines.png

description: :unav
DOI: 10.7910/dvn/il0lue/kug8jn
title: product_process_patents_2_100_ep_Other consumer goods.png

description: :unav
DOI: 10.7910/dvn/il0lue/okmcgi
title: product_process_patents_2_100_ep_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/p29ehz
title: product_process_patents_pred_ind_100_us_Audio-visual technology.png

description: :unav
DOI: 10.7910/dvn/gz8iwr/eox4ww
title: HH270mms1.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/o6jnxb
title: HH111mms.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/il0lue/4od8bo
title: product_process_patents_2_ind_100_ep_Control.png

description: :unav
DOI: 10.7910/dvn/il0lue/5yglfb
title: product_process_patents_2_100_ep_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/b3uayz
title: product_process_patents_2_100_ep_Transport.png

description: :unav
DOI: 10.7910/dvn/il0lue/dt9xkc
title: product_process_patents_pred_ind_100_ep_Transport.png

description: :unav
DOI: 10.7910/dvn/il0lue/fxzgbz
title: product_process_patents_2_ind_100_ep_Micro-structural and nano-technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/h3s2qi
title: product_process_patents_2_100_us_Food chemistry.png

description: :unav
DOI: 10.7910/dvn/il0lue/nmfatm
title: product_process_patents_abstr_ep_Chemical engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/tf6jpw
title: product_process_patents_pred_100_us_antibiotics.png

description: :unav
DOI: 10.7910/dvn/il0lue/vdqsua
title: product_process_patents_2_100_ep_Pharmaceuticals.png

description: :unav
DOI: 10.7910/dvn/gz8iwr/0jaf7b
title: HH270VLA1.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/4bsuax
title: HOPS-108.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/53yxaa
title: HH270mms2.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/gvzksm
title: HH212mms.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/obc9v1
title: HOPS-10.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/pm9vie
title: HOPS-102.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/pwdkwa
title: HOPS-105.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/uwa1q5
title: HOPS-100.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/v51k4w
title: HOPS-107.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/il0lue/9irj2i
title: product_process_patents_2_ind_100_ep_Analysis of biological materials.png

description: :unav
DOI: 10.7910/dvn/il0lue/dvej5m
title: product_process_patents_2_ind_100_ep_Basic materials chemistry .png

description: :unav
DOI: 10.7910/dvn/il0lue/gob93i
title: product_process_patents_pred_100_ep_Civil engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/pmf4eh
title: product_process_patents_2_100_us_Furniture, games.png

description: :unav
DOI: 10.7910/dvn/il0lue/vr9x2d
title: product_process_patents_pred_100_us_Thermal processes and apparatus.png

description: :unav
DOI: 10.7910/dvn/il0lue/ycocwf
title: product_process_patents_pred_100_us_Audio-visual technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/zbfp96
title: product_process_patents_pred_ind_100_us_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/zfmwab
title: product_process_patents_pred_100_ep_airplanes.png

description: :unav
DOI: 10.7910/dvn/gz8iwr/ackzzf
title: HOPS-117.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/boomad
title: HOPS-118.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/iqsiqp
title: HOPS-116.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/ovm1zq
title: HOPS-119.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/panzpw
title: HOPS-11.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/sjwpor
title: HOPS-115.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/tr3sx4
title: HOPS-1.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/uvroys
title: HOPS-114.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/il0lue/inbzjs
title: product_process_patents_2_100_us_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/isnlvc
title: product_process_patents_2_100_us_Thermal processes and apparatus.png

description: :unav
DOI: 10.7910/dvn/il0lue/o7hxwm
title: product_process_patents_pred_ind_100_us_IT methods for management.png

description: :unav
DOI: 10.7910/dvn/il0lue/qzc5vw
title: product_process_patents_2_ind_100_us_photovoltaics.png

description: :unav
DOI: 10.7910/dvn/il0lue/rf2oio
title: product_process_patents_2_100_us_Telecommunications.png

description: :unav
DOI: 10.7910/dvn/il0lue/sp3voy
title: product_process_patents_2_ind_100_us_Chemical engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/wgqefe
title: product_process_patents_pred_100_us_airplanes.png

description: :unav
DOI: 10.7910/dvn/il0lue/wkswhk
title: product_process_patents_2_ind_100_us_Furniture, games.png

description: :unav
DOI: 10.17632/ty7ccbygv9.1
title: Data for: Sampling biases and Paleozoic sporomorphs diversity dynamics in Western Gondwana strata

description: Table S1. Occurrence data of sporomorph genera in Middle Pennsylvanian-Lopingian time intervals for the Amazonas, Parnaíba, Paraná, Claromecó, Paganzo, Tarija, and Madre de Dios basins.
DOI: 10.5281/zenodo.3560696
title: Data set for "Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex"

description: Data set for: Sermet BS, Truschow P, Feyerabend M, Mayrhofer JM, Oram TB, Yizhar O, Staiger JF, Petersen CCH (2019) Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex. eLife 8: e52665. https://doi.org/10.7554/eLife.52665 There are 2 files in this upload: 1. The file named "2019_Sermet_eLife.pdf" is the Open Access pdf file of the manuscript published in eLife. 2. The file named "Sermet_data_code.zip" (~5 GB) is a zipped version of a folder "Sermet_data_code" (~5 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. When unzipped, the folder contains 8 Matlab '.m' files with analysis code and one '.mat' data file. In order to run the analysis of the data set, you need to execute 'PopPlot.m'.
description: {"references": ["Sermet BS, Truschow P, Feyerabend M, Mayrhofer JM, Oram TB, Yizhar O, Staiger JF, Petersen CCH (2019) Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex. eLife 8: e52665. https://doi.org/10.7554/eLife.52665"]}
DOI: 10.5281/zenodo.3560697
title: Data set for "Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex"

description: Data set for: Sermet BS, Truschow P, Feyerabend M, Mayrhofer JM, Oram TB, Yizhar O, Staiger JF, Petersen CCH (2019) Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex. eLife 8: e52665. https://doi.org/10.7554/eLife.52665 There are 2 files in this upload: 1. The file named "2019_Sermet_eLife.pdf" is the Open Access pdf file of the manuscript published in eLife. 2. The file named "Sermet_data_code.zip" (~5 GB) is a zipped version of a folder "Sermet_data_code" (~5 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. When unzipped, the folder contains 8 Matlab '.m' files with analysis code and one '.mat' data file. In order to run the analysis of the data set, you need to execute 'PopPlot.m'.
description: {"references": ["Sermet BS, Truschow P, Feyerabend M, Mayrhofer JM, Oram TB, Yizhar O, Staiger JF, Petersen CCH (2019) Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex. eLife 8: e52665. https://doi.org/10.7554/eLife.52665"]}
DOI: 10.7910/dvn/gz8iwr/4xbvzd
title: HOPS-121.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/hm75uk
title: HOPS-123.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/lqp3aw
title: HOPS-124.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/m5pfsw
title: HOPS-122.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/ndargh
title: HOPS-125.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/txq6oe
title: HOPS-120.13CO.ms.tar.gz
DOI: 10.7910/dvn/gz8iwr/wpi7vs
title: HOPS-129.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.7910/dvn/gz8iwr/ww7byj
title: HOPS-127.13CO.ms.selfcal.contsub.tar.gz
DOI: 10.5281/zenodo.10610989
title: The economic and social value of Science and Technology Parks. The case of Tecnocampus

description: This article aims to measure both the economic and social value of Tecnocampus, a Science and Technology Park in its region of influence (Mataró city in the Maresme region of Catalonia, Spain). Our results show that the impact of Tecnocampus has a socioeconomic cost–benefit ratio of 2.39. Measuring the impact of this multifaceted centre requires a diverse approach. Although the methods used are not new, the combination of them presents a novel approach to measure the impact of an institution of this nature. We have measured the economic value with the Input–Output model, including the Social Accounting Matrix. On the other hand, for social value calculations, we have used cost–benefit analysis adding measurements of firm localisation to estimate externality effects. Our main results present an economic value of more than 0.054% of the Catalan GDP, whereas the employment impact represents almost 0.37% of total employment in the region. The total economic multiplier of Tecnocampus activity is estimated to be 1.89. Social value generates an additional 0.50 euros to the multiplier according with our analysis. This additional social value represents an increase of productivity estimated in 20 million euros of operational income for Catalan firms and the creation of seven additional firms in the Maresme region as a result of knowledge spillovers. The social value also includes reduction of over-education caused by a better matching between graduates and enterprises, a more direct application of research, and an increase in consumer surplus. Finally, we discuss the policy implications of our findings to promote investments in this kind of infrastructures.
DOI: 10.5281/zenodo.10611966
title: The economic and social value of Science and Technology Parks. The case of Tecnocampus

description: This article aims to measure both the economic and social value of Tecnocampus, a Science and Technology Park in its region of influence (Mataró city in the Maresme region of Catalonia, Spain). Our results show that the impact of Tecnocampus has a socioeconomic cost–benefit ratio of 2.39. Measuring the impact of this multifaceted centre requires a diverse approach. Although the methods used are not new, the combination of them presents a novel approach to measure the impact of an institution of this nature. We have measured the economic value with the Input–Output model, including the Social Accounting Matrix. On the other hand, for social value calculations, we have used cost–benefit analysis adding measurements of firm localisation to estimate externality effects. Our main results present an economic value of more than 0.054% of the Catalan GDP, whereas the employment impact represents almost 0.37% of total employment in the region. The total economic multiplier of Tecnocampus activity is estimated to be 1.89. Social value generates an additional 0.50 euros to the multiplier according with our analysis. This additional social value represents an increase of productivity estimated in 20 million euros of operational income for Catalan firms and the creation of seven additional firms in the Maresme region as a result of knowledge spillovers. The social value also includes reduction of over-education caused by a better matching between graduates and enterprises, a more direct application of research, and an increase in consumer surplus. Finally, we discuss the policy implications of our findings to promote investments in this kind of infrastructures.
DOI: 10.5281/zenodo.10611974
title: kiunga_ballochi_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.10611975
title: kiunga_ballochi_spades_01.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/7542201
title: Global Game Jam Dataset
DOI: 10.34740/kaggle/dsv/7542225
title: Public Opinion Russia Ukraine War (Updated Daily)
DOI: 10.13020/39me-vb21
title: Supporting data for Chemically Recyclable Linear and Branched Polyethylenes Synthesized from Stoichiometrically Self-balanced Telechelic Polyethylenes

description: These files contain primary data along with associated output from instrumentation supporting all results reported in "Chemically Recyclable Linear and Branched Polyethylenes Synthesized from Stoichiometrically Self-balanced Telechelic Polyethylenes" by Jang et al. The abstract of this document is the following, High-density polyethylene (HDPE) is a widely used commercial plastic due to its excellent mechanical properties, chemical resistance, and water vapor barrier properties. However, less than 10% of HDPE is mechanically recycled, and chemical recycling of HDPE is challenging due to inherent strength of the carbon-carbon backbone bonds. Here, we report chemically recyclable linear and branched HDPE with sparse backbone ester groups synthesized from transesterification of the telechelic polyethylene macromonomers. Stoichiometrically self-balanced telechelic polyethylenes underwent transesterification polymerization to produce the PE-ester samples with high number average molar masses up to 111 kg/mol. Moreover, transesterification polymerization of the telechelic polyethylenes and the multifunctional diethyl 5-(hydroxymethyl)isophthalate generated branched PE-esters. Thermal and mechanical properties of the PE-esters were comparable to commercial HDPE and tunable through control of the ester content in the backbone. In addition, branched PE-esters showed higher levels of melt-strain hardening compared to linear versions. The PE-ester was depolymerized into telechelic macromonomers through straightforward methanolysis and the resulting macromonomers could be effectively repolymerized to generate high molar mass recycled PE-ester samples. This is a new and promising method for synthesizing and recycling high-molar-mass linear and branched PE-esters, which are competitive with HDPE and have easily tailorable properties.