The Linked Open Data Cloud (LOD Cloud) is the constellation of available interlinked open dataset... more The Linked Open Data Cloud (LOD Cloud) is the constellation of available interlinked open datasets which has become one of the biggest repositories on the web. An increasing number of spatial semantically annotated datasets provide a huge potential source of knowledge for data enrichment in a spatial context. Yet, there is lack of information about the structure of the spatial datasets in the LOD Cloud which can discourage the integration efforts. In addition, most of the existing studies of link discovery have yet to exploit spatial information richness (topology and geometry). Thus, a structured way to assess spatial datasets and to integrate linked spatial data is required. This study aims to evaluate the LOD Cloud by assessing the data structure and the representation of linked spatial data, in order to support exploration and integration purposes. To achieve this objective, this study proposes: (i) a workflow for analyzing linked spatial data resources in the LOD Cloud, which consists of the identification of the linked spatial data sources, strategies for dataset retrieval, pipeline design for data processing, and linked data quality principles and metrics analysis; (ii) a review of linked data visualization systems, which includes an assessment of the current LOD Cloud Diagram based on expert opinion with respect to key requirements for visual representation and analytics for linked data consumption; and (iii) a workflow for linked spatial data integration. The main contribution of this thesis is the provision of case studies of integrating various spatial data sources. We presented two case studies, geometry-based integration using the spatial extension of Silk Link Discovery, and toponym-based integration using Similarity Measure. The datasets of Basisregistratie Topografie (BRT) Kadaster, Natura2000, and Geonames were used for the data integration. The results of the study include: (i) a structured way to consume and extract spatial information from linked data resources. In this thesis, we proposed one metric to assess linked spatial data, namely the existence of geospatial ontology – vocabulary in the linked data resources; (ii) identification of suitable visualization element for exploration and discovery, especially for spatial data. The top-level relationship (overview) visualization is potentially facilitating an effective datasets discovery and also able to expose the spatial content and relationship in a sensible way. This study discovered that the linkset concept in the level of the dataset, subset, and distribution could be used as basis information for overview visualization; and finally, (iii) findings of spatial components (geometry and toponym) that can be used as important “hook” for integrating different datasets. The commonly used geospatial ontology and vocabulary also enable semantic interoperability to support data integration.
Pertambahan penduduk Kota Yogyakarta terus meningkat dari tahun ke tahun. Berdasarkan sensus pend... more Pertambahan penduduk Kota Yogyakarta terus meningkat dari tahun ke tahun. Berdasarkan sensus penduduk tahun 2010, jumlah penduduk Kota Yogyakarta 3. 457. 491 jiwa, dengan kepadatan penduduk sebesar 1.085,28 jiwa/km2. Pertambahan penduduk yang semakin meningkat akan mendorong kegiatan sosial ekonomi di daerah Kota Yogyakarta yang selanjutnya menjadi pendorong utama dalam Perubahan penggunaan lahan untuk memenuhi kebutuhan kegiatan tersebut. Pola Perubahan penggunaan lahan tersebut dapat diprediksi dari beberapa faktor seperti adanya Central Business District (CBD), jalan (jalan utama, jalan lokal, jalan lain), dan sungai (Susilo, 2006). Perubahan penggunaan lahan yang tidak terkontrol akan berpengaruh pada penurunan kualitas lingkungan, seperti berkurangnya ketersediaan air tanah. Oleh karena itu, perlu diketahui pola dan arah Perubahan penggunaan lahan sebagai dasar untuk perencanaan penggunaan lahan yang lebih terkontrol. Perubahan penggunaan lahan Kota Yogyakarta dapat dianalisis ...
Proceedings of The International Conference on Data Science and Official Statistics, 2022
Satu Data Indonesia is a policy contrive to encourage the problem of inadequate data governance i... more Satu Data Indonesia is a policy contrive to encourage the problem of inadequate data governance in Indonesia. This policy makes 4 main principles, namely metadata, data standards, reference codes, and interoperability as metrics of success in its implementation. In this study, we analyze the satu data Indonesia implementation in Kutai Timur Regency. We found that the integration of the satu data principle is challenging to apply technically because sectoral data in Indonesia has 2 characteristics based on the preparation of the list of data needs, namely the centralized data list, and the decentralized data list. Decentralized data list is a list of data that is partially prepared in each agency without any coordination with other stakeholders for completing the satu data principles. To accommodating this condition, we design the Satu Data Metadata Framework (SDMF) a data standard framework that is in accordance with the conditions of data governance in Indonesia. SDMF utilizes cont...
The Linked Open Data Cloud (LOD Cloud) is the constellation of available interlinked open dataset... more The Linked Open Data Cloud (LOD Cloud) is the constellation of available interlinked open datasets which has become one of the biggest repositories on the web. An increasing number of spatial semantically annotated datasets provide a huge potential source of knowledge for data enrichment in a spatial context. Yet, there is lack of information about the structure of the spatial datasets in the LOD Cloud which can discourage the integration efforts. In addition, most of the existing studies of link discovery have yet to exploit spatial information richness (topology and geometry). Thus, a structured way to assess spatial datasets and to integrate linked spatial data is required. This study aims to evaluate the LOD Cloud by assessing the data structure and the representation of linked spatial data, in order to support exploration and integration purposes. To achieve this objective, this study proposes: (i) a workflow for analyzing linked spatial data resources in the LOD Cloud, which consists of the identification of the linked spatial data sources, strategies for dataset retrieval, pipeline design for data processing, and linked data quality principles and metrics analysis; (ii) a review of linked data visualization systems, which includes an assessment of the current LOD Cloud Diagram based on expert opinion with respect to key requirements for visual representation and analytics for linked data consumption; and (iii) a workflow for linked spatial data integration. The main contribution of this thesis is the provision of case studies of integrating various spatial data sources. We presented two case studies, geometry-based integration using the spatial extension of Silk Link Discovery, and toponym-based integration using Similarity Measure. The datasets of Basisregistratie Topografie (BRT) Kadaster, Natura2000, and Geonames were used for the data integration. The results of the study include: (i) a structured way to consume and extract spatial information from linked data resources. In this thesis, we proposed one metric to assess linked spatial data, namely the existence of geospatial ontology – vocabulary in the linked data resources; (ii) identification of suitable visualization element for exploration and discovery, especially for spatial data. The top-level relationship (overview) visualization is potentially facilitating an effective datasets discovery and also able to expose the spatial content and relationship in a sensible way. This study discovered that the linkset concept in the level of the dataset, subset, and distribution could be used as basis information for overview visualization; and finally, (iii) findings of spatial components (geometry and toponym) that can be used as important “hook” for integrating different datasets. The commonly used geospatial ontology and vocabulary also enable semantic interoperability to support data integration.
Pertambahan penduduk Kota Yogyakarta terus meningkat dari tahun ke tahun. Berdasarkan sensus pend... more Pertambahan penduduk Kota Yogyakarta terus meningkat dari tahun ke tahun. Berdasarkan sensus penduduk tahun 2010, jumlah penduduk Kota Yogyakarta 3. 457. 491 jiwa, dengan kepadatan penduduk sebesar 1.085,28 jiwa/km2. Pertambahan penduduk yang semakin meningkat akan mendorong kegiatan sosial ekonomi di daerah Kota Yogyakarta yang selanjutnya menjadi pendorong utama dalam Perubahan penggunaan lahan untuk memenuhi kebutuhan kegiatan tersebut. Pola Perubahan penggunaan lahan tersebut dapat diprediksi dari beberapa faktor seperti adanya Central Business District (CBD), jalan (jalan utama, jalan lokal, jalan lain), dan sungai (Susilo, 2006). Perubahan penggunaan lahan yang tidak terkontrol akan berpengaruh pada penurunan kualitas lingkungan, seperti berkurangnya ketersediaan air tanah. Oleh karena itu, perlu diketahui pola dan arah Perubahan penggunaan lahan sebagai dasar untuk perencanaan penggunaan lahan yang lebih terkontrol. Perubahan penggunaan lahan Kota Yogyakarta dapat dianalisis ...
Proceedings of The International Conference on Data Science and Official Statistics, 2022
Satu Data Indonesia is a policy contrive to encourage the problem of inadequate data governance i... more Satu Data Indonesia is a policy contrive to encourage the problem of inadequate data governance in Indonesia. This policy makes 4 main principles, namely metadata, data standards, reference codes, and interoperability as metrics of success in its implementation. In this study, we analyze the satu data Indonesia implementation in Kutai Timur Regency. We found that the integration of the satu data principle is challenging to apply technically because sectoral data in Indonesia has 2 characteristics based on the preparation of the list of data needs, namely the centralized data list, and the decentralized data list. Decentralized data list is a list of data that is partially prepared in each agency without any coordination with other stakeholders for completing the satu data principles. To accommodating this condition, we design the Satu Data Metadata Framework (SDMF) a data standard framework that is in accordance with the conditions of data governance in Indonesia. SDMF utilizes cont...
Uploads
This study aims to evaluate the LOD Cloud by assessing the data structure and the representation of linked spatial data, in order to support exploration and integration purposes. To achieve this objective, this study proposes: (i) a workflow for analyzing linked spatial data resources in the LOD Cloud, which consists of the identification of the linked spatial data sources, strategies for dataset retrieval, pipeline design for data processing, and linked data quality principles and metrics analysis; (ii) a review of linked data visualization systems, which includes an assessment of the current LOD Cloud Diagram based on expert opinion with respect to key requirements for visual representation and analytics for linked data consumption; and (iii) a workflow for linked spatial data integration. The main contribution of this thesis is the provision of case studies of integrating various spatial data sources. We presented two case studies, geometry-based integration using the spatial extension of Silk Link Discovery, and toponym-based integration using Similarity Measure. The datasets of Basisregistratie Topografie (BRT) Kadaster, Natura2000, and Geonames were used for the data integration.
The results of the study include: (i) a structured way to consume and extract spatial information from linked data resources. In this thesis, we proposed one metric to assess linked spatial data, namely the existence of geospatial ontology – vocabulary in the linked data resources; (ii) identification of suitable visualization element for exploration and discovery, especially for spatial data. The top-level relationship (overview) visualization is potentially facilitating an effective datasets discovery and also able to expose the spatial content and relationship in a sensible way. This study discovered that the linkset concept in the level of the dataset, subset, and distribution could be used as basis information for overview visualization; and finally, (iii) findings of spatial components (geometry and toponym) that can be used as important “hook” for integrating different datasets. The commonly used geospatial ontology and vocabulary also enable semantic interoperability to support data integration.
This study aims to evaluate the LOD Cloud by assessing the data structure and the representation of linked spatial data, in order to support exploration and integration purposes. To achieve this objective, this study proposes: (i) a workflow for analyzing linked spatial data resources in the LOD Cloud, which consists of the identification of the linked spatial data sources, strategies for dataset retrieval, pipeline design for data processing, and linked data quality principles and metrics analysis; (ii) a review of linked data visualization systems, which includes an assessment of the current LOD Cloud Diagram based on expert opinion with respect to key requirements for visual representation and analytics for linked data consumption; and (iii) a workflow for linked spatial data integration. The main contribution of this thesis is the provision of case studies of integrating various spatial data sources. We presented two case studies, geometry-based integration using the spatial extension of Silk Link Discovery, and toponym-based integration using Similarity Measure. The datasets of Basisregistratie Topografie (BRT) Kadaster, Natura2000, and Geonames were used for the data integration.
The results of the study include: (i) a structured way to consume and extract spatial information from linked data resources. In this thesis, we proposed one metric to assess linked spatial data, namely the existence of geospatial ontology – vocabulary in the linked data resources; (ii) identification of suitable visualization element for exploration and discovery, especially for spatial data. The top-level relationship (overview) visualization is potentially facilitating an effective datasets discovery and also able to expose the spatial content and relationship in a sensible way. This study discovered that the linkset concept in the level of the dataset, subset, and distribution could be used as basis information for overview visualization; and finally, (iii) findings of spatial components (geometry and toponym) that can be used as important “hook” for integrating different datasets. The commonly used geospatial ontology and vocabulary also enable semantic interoperability to support data integration.