We propose a SPARQL query sharing system for Linked Open Data. Recently, many and various datasets are published as a Linked Open Data (LOD). SPARQL is an RDF query language and it provides a powerful way to access LOD. However, it is not easy to utilize them because it requires not only techniques of SPARQL but also knowledge of datasets and vocabularies that they used for users. Therefore, we propose sharing SPARQL query as a solution of this problem. Sharing SPARQL query is a simple solution but it has an important role for LOD. In this paper, we describe a difficulty of utilizing LOD and introduce our prototype system for sharing SPARQL query.

Innovators Marketplace on Data Jackets (IMDJ) is a workshop featuring a serious game designed on the metaphor of a market where the scenarios of data use are created and evaluated through interdisciplinary communication among various stakeholders. A data jacket is a metadata description template for the sharing of metadata. Data jackets are uniquely designed to allow data owners to appeal to users without disclosing full data. In this paper we propose an idea to describe with RDF the relationship between data jackets, which are open metadata, and the corresponding original data, which may be closed data. Thus data jackets as open metadata can be connected to other open data within the network of Linked Open Data. In this way, the open metadata for closed data can be searched for and referred in the same manner as open data, which let the market notice the existence of the closed data and how these data can be connected with other data in the world, while the data contents can stay unshared to the public.

Innovators Marketplace on Data Jackets is a gamified workshop for presenting creating scenarios to combine and analyze data based on shared metadata, without disclosing contents of the data. Here the least necessary digest information about given data is described in a data jacket (DJ) and published, on which latent links among datasets are visualized on a game board. On this map, participants propose, criticize, purchase, sell, and call for ideas to combine/analyze data and analysis tools that may be untouchable, i.e., confidential or hidden. Requirements for additional data and tools as well as scenarios for analysis are presented in the process of IMDJ. In this paper we present a case where Tangled String, a tool for visualizing sequential data has been created from the process.

Life Science Database Cross Search collects (=crawls) Japanese public databases for providing knowledge finding system. This database crawling needs specialized protocols to find data in deep-web sites, to select appropriate data range for user, and to make rule-based decision. This report shows methods and its results.

With the rapid development of high-throughput experimental equipments such as next generation sequencers, life science researches have progressed quickly. This has made exponential growth of published papers, and therefore made difficult for a researcher to grasp the latest research outcomes even in the field of his/her expertise. Moreover, the almost all of the significant research outcomes have been published in English, and all the more so with researchers whose mother language is Japanese. Here, we propose a search system for a researcher to find a review articles in Japanese of the latest life science research outcomes. Our system uses Medical Subject Headings (MeSH) and the Life Science Dictionary (LSD) to provide a user with a concept-based narrowing down interface. MeSH and LSD are both provided in Resource Description Framework (RDF), and LSD contains relationships between LSD and MeSH terms. We built a dataset of Japanese review articles in RDF that consists of bibliographic data and annotations using the LSD.